gestational diabetes mellitus case study slideshare

• My presentations

Auth with social network:

Download presentation

We think you have liked this presentation. If you wish to download it, please recommend it to your friends in any social system. Share buttons are a little bit lower. Thank you!

Presentation is loading. Please wait.

Gestational Diabetes Mellitus

Published by Linda Meneses Álvares Modified over 5 years ago

Similar presentations

Presentation on theme: "Gestational Diabetes Mellitus"— Presentation transcript:

Diabetes in pregnancy Dr Than Than Yin.

Dr. Amel F. Al-Sayed Asst. Prof. & Consultant Department of Obstetrics & Gynecology.

The risk of Insulin Resistence and Metabolic Syndrome among overweight/obese children born of mothers with Gestational Diabetes Mosca A., Vania A Dept.

Diabetes Mellitus It is a syndrome characterized by disturbance of carbohydrates, fats, proteins, minerals and water caused by absolute or relative deficiency.

Diabetes during pregnancy

Diabetes and Pregnancy

Diabetes in Pregnancy Screening.

Diabetes in Pregnancy L.Sekhavat MD.

Update in Diagnosis and Management

Gestational diabetes mellitus (GDM), a common medical complication of pregnancy, is defined as “any degree of glucose intolerance with onset or first.

EPIDEMIOLOGY IN GESTATIONAL DIABETES MELLITUS Methodology Dr. Nam-Han Cho Associate Professor of Preventive Medicine Director of Center for Clinical Epidemiology.

DR. TARIK Y. ZAMZAMI MD, CABOG, FICS ASSOCIATE PROFESSOR CONSULTANT OB/GYN

Gestational Diabetes Mellitus (GDM)

Medical Nutrition Therapy in Gestational Diabetes Mellitus

Assistant Professor & Consultant Department of Obstetrics & Gynecology

Diabetes in pregnancy Dr. Lubna Maghur MRCOG. Diabetes is a common medical disorder effecting 2-5% of pregnancies. Diabetes is a common medical disorder.

Normal physiology of pregnancy First trimester-Increased insulin sensitivity. Late 2 nd and 3 rd trimester insulin resistance possible associated with.

Diabetes in pregnancy James Penny Consultant Obstetrician & Gynaecologist Surrey & Sussex NHS Trust.

GDM Gestational Diabetes Mellitus Dr. R V S N Sarma., M.D., M.Sc., (Canada) Consultant Physician & Chest Specialist Visit us at:

Life Cycle: Maternal and Infant Nutrition BIOL 103, Chapter 12-1.

About project

© 2024 SlidePlayer.com Inc. All rights reserved.

• Previous Article
• Next Article

Presentation

Clinical pearls, case study: complicated gestational diabetes results in emergency delivery.

• Split-Screen
• Article contents
• Figures & tables
• Supplementary Data
• Peer Review
• Open the PDF for in another window
• Cite Icon Cite
• Get Permissions

Ginny Lewis; Case Study: Complicated Gestational Diabetes Results in Emergency Delivery. Clin Diabetes 1 January 2001; 19 (1): 25–26. https://doi.org/10.2337/diaclin.19.1.25

Download citation file:

• Ris (Zotero)
• Reference Manager

A.R. is a 33-year-old caucasian woman initially diagnosed with diabetes during a recent pregnancy. The routine glucose challenge test performed between 28 and 29 weeks gestation was elevated at 662 mg/dl. A random glucose completed 1–2 days later was also elevated at 500 mg/dl. A follow-up HbA 1c was elevated at 11.6%. Additional symptoms included a 23-lb weight loss over the past 3–4 weeks with ongoing “flu-like” symptoms, including fatigue, nausea, polyuria, and polydypsia.

A.R. had contacted her obstetrician’s office when her symptoms first appeared and was told to contact her primary care provider for the “flu” symptoms. She had called a nurse triage line several times over the previous 2–3 weeks with ongoing symptoms and was told to rest and take fluids.

She presented to her primary care provider 3 days after the HbA 1c was drawn for ongoing evaluation of hyperglycemia. At that time, she was symptomatic for diabetic ketoacidosis. She was hospitalized and started on an insulin drip.

A.R.’s hospitalization was further complicated with gram-negative sepsis, adult respiratory distress syndrome, and Crohn’s disease with a new rectovaginal fistula. She was intubated as her respiratory status continued to decline and was transferred to a tertiary medical center for ongoing management. She required an emergency Caesarian section at 30 1/7 weeks gestation due to increased fetal distress.

A.R. had no family history of diabetes with the exception of one sister who had been diagnosed with gestational diabetes. Her medical history was significant for Crohn’s disease diagnosed in 1998 with no reoccurrence until this hospitalization. Her pre-pregnancy weight was 114–120 lb. She had gained 25 lb during her pregnancy and lost 23 lb just before diagnosis.

A.R.’s blood glucose levels improved postpartum, and the insulin drip was gradually discontinued. She was discharged on no medications.

At her 2-week postpartum visit, home blood glucose monitoring indicated that values were ranging from 72 to 328 mg/dl, with the majority of values in the 200–300 mg/dl range. A repeat HbA 1c was 8.7%. She was restarted on insulin.

1.  What is the differential diagnosis of gestational diabetes versus type 1 diabetes?

2.  At what point during pregnancy should insulin therapy be instituted for blood glucose control?

3.  How can communication systems be changed to provide for integration of information between multiple providers?

Gestational diabetes is defined as “any degree of carbohydrate intolerance with onset first recognized during pregnancy. This definition applies whether insulin ... is used for treatment and whether or not the condition persists after pregnancy.” 1 Risk assessment is done early in the pregnancy, with average-risk women being tested at 24–28 weeks’ gestation and low-risk women requiring no additional testing. 1 , 2 A.R. met the criteria for average risk based on age and a first-degree family member with a history of gestational diabetes.

Screening criteria for diagnosing diabetes include 1 ) symptoms of diabetes plus casual plasma glucose >200 mg/dl (11.1 mmol/l), or   2 ) fasting plasma glucose >126 mg/dl (7.0 mmol/l), or   3 ) 2-h plasma glucose >200 mg/dl (11.1 mmol/l) during an oral glucose tolerance test (OGTT). 3 For women who do not meet the first two criteria, a glucose challenge test (GCT) measuring a 1-h plasma glucose following a 50-g oral glucose load is acceptable. For those women who fail the initial screen, practitioners can then proceed with the OGTT. 1  

In A.R.’s case, she most likely would have met the first criterion if a casual blood glucose had been measured. She had classic symptoms with weight loss, fatigue, polyuria, and polydypsia. Her 1-h plasma glucose following the glucose challenge was >600 mg/dl, which suggests that her casual glucose would also have been quite high.

Medical nutrition therapy (MNT) is certainly a major part of diabetes management. However, with this degree of hyperglycemia, MNT would not be adequate as monotherapy. Treatment for gestational diabetes includes the use of insulin if fasting blood glucose levels are >95 mg/dl (5.3 mmol/l) or 2-h postprandial values are >120 mg/dl (6.7 mmol/l). 1  

Several days passed from the time of A.R.’s initial elevated blood glucose value and the initiation of insulin therapy. While HbA 1c values cannot be used for diagnostic purposes, in this case they further confirmed the significant degree of hyperglycemia.

Plasma blood glucose values initially improved in the immediate postpartum period. A.R. was sent home without medications but instructed to continue home glucose monitoring.

At her 2-week postpartum visit, whole blood glucose values were again indicating progressive hyperglycemia, and insulin was restarted. A.R.’s postpartum weight was 104 lb—well below her usual pre-pregnancy weight of 114–120 lb. Based on her ethnic background, weight loss, abrupt presentation with classic diabetes symptoms, and limited family history, she was reclassified as having type 1 diabetes.

In immune-mediated, or type 1, diabetes, b-cell destruction can be variable, with a slower destruction sometimes seen in adults. 3 Presentation of type 1 diabetes can also vary with modest fasting hyperglycemia that can quickly change to severe hyperglycemia and/or ketoacidosis in the presence of infection or other stress. 3 A.R. may have had mild hyperglycemia pre-pregnancy that increased in severity as the pregnancy progressed.

The final issue is communication among multiple health care providers. A.R. was part of a system that uses primary care providers, specialists, and triage nurses. She accessed all of these providers as instructed. However, the information did not seem to be clearly communicated among these different types of providers. A.R. called triage nurses several times with her concerns of increased fatigue, nausea, and weight loss. The specialist performed her glucose challenge with follow-up through the primary care office. It seems that if all of these providers had the full information about this case, the diagnosis could have been made more easily, and insulin could have been initiated more quickly.

1.  Hyperglycemia diagnosed during pregnancy is considered to be gestational diabetes until it is reclassified in the postpartum period. Immune-mediated diabetes can cause mild hyperglycemia that is intensified with the increased counterregulatory hormone response during pregnancy.

2.  Insulin therapy needs to be instituted quickly for cases in which MNT alone is inadequate.

3.  The GCT is an appropriate screening test for an average-risk woman with no symptoms of diabetes. In the face of classic symptoms of diabetes, a casual plasma glucose test can eliminate the need for the glucose challenge.

4.  As part of the health care industry, we need to continue to work on information systems to track patient data and share data among multiple providers. Patients can become lost in an ever-expanding system that relies on “protocols” and does not always allow for individual differences or for cases with unusual presentation.

Ginny Lewis, ARNP, FNP, CDE, is a nurse practitioner at the Diabetes Care Center of the University of Washington School of Medicine in Seattle.

Email alerts

• Online ISSN 1945-4953
• Print ISSN 0891-8929
• Diabetes Care
• Clinical Diabetes
• Diabetes Spectrum
• Standards of Medical Care in Diabetes
• Scientific Sessions Abstracts
• BMJ Open Diabetes Research & Care
• ShopDiabetes.org
• ADA Professional Books

Clinical Compendia

• Clinical Compendia Home
• Latest News
• DiabetesPro SmartBrief
• Special Collections
• DiabetesPro®
• Diabetes Food Hub™
• Insulin Affordability
• Know Diabetes By Heart™
• About the ADA
• Journal Policies
• For Reviewers
• Advertising in ADA Journals
• Reprints and Permission for Reuse
• Copyright Notice/Public Access Policy
• ADA Professional Membership
• ADA Member Directory
• Diabetes.org
• X (Twitter)
• Cookie Policy
• Accessibility
• Terms & Conditions
• Get Adobe Acrobat Reader
• © Copyright American Diabetes Association

This Feature Is Available To Subscribers Only

Sign In or Create an Account

Gestational diabetes mellitus

Mar 21, 2019

950 likes | 2.42k Views

Gestational diabetes mellitus. Dr. Kanakamani Madhivanan, M.D., D.M. (Endocrinology), Assistant Professor Department of Endocrinology, Diabetes, Metabolism Christian Medical College, Vellore. Plan of presentation. Introduction Physiology of fuel metabolism in normal pregnancy

Share Presentation

• insulin requirement
• universal screening
• approximately 2 percent
• normal prepregnancy body weight

Presentation Transcript

Gestational diabetes mellitus Dr. Kanakamani Madhivanan, M.D., D.M. (Endocrinology), Assistant Professor Department of Endocrinology, Diabetes, Metabolism Christian Medical College, Vellore

Plan of presentation • Introduction • Physiology of fuel metabolism in normal pregnancy • Pathophysiology of GDM • Epidemiology of GDM • Screening and diagnosis • Maternal and fetal risks • Management of GDM • Obstetric management

Introduction

Introduction • Global increase in prevalence of DM • Individual importance - Hyperglycemia in pregnancy has adverse effects on both mother and fetus • Public health importance – rising epidemic of DM in part attributed to the diabetic pregnancies • Prevention of type 2 DM should start intrauterine and continue throughout life

Introduction • Gestational diabetes (GDM) is defined as any degree of impaired glucose tolerance of with onset or first recognition during pregnancy . • Many are denovo pregnancy induced • Some are type 2 ( 35-40%) • 10% have antibodies

Introduction • Difficult to distinguish pregestational Type 2 DM and denovo GDM • Fasting hyperglycemia • blood glucose greater than 180 mg/dL on OGT • acanthosis nicgrans • HbA1C > 5.3% • a systolic BP > 110 mm Hg • BMI > 30 kg/m2 • Fetal anomalies • Clues for Type 1 • Lean • DKA during pregnancy • Severe hyperglycemia with large doses of insulin

Fuel metabolism in pregnancy

Fuel metabolism in pregnancy • Goal is uninterrupted nutrient supply to fetus • The metabolic goals of pregnancy are • 1) in early pregnancy to develop anabolic stores to meet metabolic demands in late pregnancy • 2) in late pregnancy to provide fuels for fetal growth and energy needs.

Glucose metabolism in pregnancy • Early pregnancy • E2/PRL stimulates b cells –Insulin sensitivity same and peripheral glucose utilisation – 10% fall in BG levels • Late pregnancy • Fetoplacental unit extracts glucose and aminoacids, fat is used mainly for fuel metabolism • Insulin sensitivity decreases progressively upto 50-80% during the third trimester • variety of hormones secreted by the placenta, especially hPL and placental growth hormone variant, cortisol, PRL,E2 and Prog

Glucose metabolism in pregnancy FASTING accelerated starvation and esxaggerated ketosis (maternal hypoglycemia, hypoinsulinemia, hyperlipidemia, and hyperketonemia) FED hyperglycemia, hyperinsulinemia, hyperlipidemia, and reduced tissue sensitivity to insulin Fat Hyperinsulinemia Insulin resistance Glucose Aminoacids Fetus

24-hour insulin requirement before conception is approximately 0.8 units / kg. • In the first trimester, the insulin requirement rises to 0.7units / kg of the pregnant weight – more unstable glycemia with a tendency to low fasting plasma glucose and high postprandial excursions and the occurrence of nocturnal hypoglycemia • By the second trimester, the insulin requirement is 0.8 units per kilogram. From 24th month onwards steady increase in insulin requirement and glycemia stabilises • By third trimester the insulin requirement is 0.9 - 1.0 unit /kg pregnant weight per day • Last month – may be a decrease in insulin and hypoglycemias esp. nocturnal

EPIdemiology AND Risk factors

Magnitude of problem: Global • Prevalence of GDM varies worldwide and among different racial and ethnic groups within a country • America – white women (3.9%) and Asian (8.7%) • Europe – 0.6% to 3.6% • Australia – 3.6% to 4.7% (Indian women – 17.7%) • China – 2.3%; Japan – 2.9% • Variability is partly because of the different criteria and screening regimens

Magnitude of the problem - India • Chennai, hospital based, universal screening – 18.9% had FPG ≥ 126 and PPPG ≥ 140. • Trivandrum – 15% • Bangalore – 12% • Erode – 18.8% • Chennai, community based, universal screning, 17.8% in urban, 13.8% in semi urban and 9.9% in rural areas. • Chennai : 0.56% • Mysore Parthenon Study: 6% • Maharashtra, hospital based, selective screening – 7.7% had GDM; 13.9% had IGGT.

Risk factors • A family history of diabetes, especially in first degree relatives • Prepregnancy weight ≥110% of ideal body weight or body mass index over 30 kg/m2 or significant weight gain in early adulthood, between pregnancies, or in early pregnancy • Age greater than 25 years • Previous delivery of a baby greater than 4.1 kg • Personal history of abnormal glucose tolerance • Member of an ethnic group with higher than the background rate of type 2 diabetes (in most populations, the background rate is approximately 2 percent) • Previous unexplained perinatal loss or birth of a malformed child • Maternal birthweight greater than 4.1 kg or less than 6 pounds 2.7 kg • Glycosuria at the first prenatal visit • Polycystic ovary syndrome • Current use of glucocorticoids • Essential hypertension or pregnancy-related hypertension

Maternal and Fetal risks

Maternal complications • Worsening retinopathy – 10% new DR, 20% mild NPDR and 55% mod-severe NPDR progresses • Worsening proteinuria. GFR decline depends on preconception creatinine and proteinuria • Hypertension and Cardiovascular disease • Neuropathy – No worsening (gastroparesis, nausea, orthostatic dizziness can be worsened) • Infection

Maternofetal complications • Macrosomia: 63 percent • Cesarean delivery: 56 percent • Preterm delivery: 42 percent • Preeclampsia: 18 percent • Respiratory distress syndrome: 17 percent • Congenital malformations: 5 percent • Perinatal mortality: 3 percent • Spontaneous abortion, third trimester fetal deaths, Polyhydramnios, preterm birth, ?adverse neurodevelopmental outcome • Risk for type 2 DM

Neonatal complications • Morbidity associated with preterm birth • Macrosomia ± birth injury (shouldeer dystocia, brachial plexus injury) • Polycythemia and hyperviscosity • Hyperbilirubinemia • Cardiomyopathy • Hypoglycemia and other metabolic abnormalities (hypocalcemia, hypomagnesemia) • Respiratory problems • Congenital anomalies

Congenital anomalies • 2/3rd CVS or CNS,– 13-20 times common • Cardiac( including great vessel anomalies) : most common • Central nervous system (spina bifida/anencephaly) : 7.2% • Skeletal: cleft lip/palate, caudal regression syndrome • Genitourinary tract: ureteric duplication • Gastrointestinal : anorectal atresia

Skeletal and central nervous system • Caudal regression syndrome • Neural tube defects excluding anencephaly • Anencephaly with or without herniation of neural elements • Microcephaly • Cardiac • Transposition of the great vessels with or without ventricular • Ventricular septal defects • Coarctation of the aorta with or without ventricular septal defects or patent ductus arteriosus • Atrial septal defects • Cardiomegaly • Renal anomalies • Hydronephrosis • Renal agenesis • Ureteral duplication • Gastrointestinal • Duodenal atresia • Anorectal atresia • Small left colon syndrome

Caudal regression syndrome

SCREENING AND DIAGNOSIS

Whom to screen ? • No consensus • recommended screening ranges from selective screening of average- and high-risk individuals to universal diagnostic testing of the entire population dependent on the risk of diabetes in the population. Risk stratification based on certain variables Low risk : no screening Average risk: at 24-28 weeks High risk : as soon as possible

Low risk for GDM To satisfy all these criteria • Age <25 years • Not a member of an ethnic group with high prevalence of GDM (not Hispanic, Native American/Alaskan, Asian/Pacific Islander, African American) • Normal prepregnancy body weight (not 20% or more over desired body weight or BMI 27 kg/m2 or more) • No family history of diabetes in first-degree relatives. • No history of abnormal glucose tolerance • No history of poor obstetric outcome

High risk • Marked obesity • Prior GDM (30-50% risk for recurrence) • Glycosuria • Strong family history

When and how to screen? • 24-28 weeks • High risk • First prenatal visit • 50 g glucose loading test • High risk women – 3 hr GTT with 100 g glucose

50 g GTT • A 50-g oral glucose load is given without regard to the time elapsed since the last meal and plasma or serum glucose is measured one hour later • A value ≥130 mg/dL is considered abnormal ; we use ≥130 mg/dL as the threshold for our patients. • Capillary blood should not be used for screening unless the precision of the glucose meter is known, it has been correlated with simultaneously drawn venous plasma samples, and has met federal standards for laboratory testing.

100 g GTT • Oral glucose tolerance test ( OGTT) with 100 gm glucose • Overnight fast of at least 8 hours • At least 3 days of unrestricted diet and unlimited physical activity • > 2 values must be abnormal

75 g GTT ADA WHO

Whom and when to screen? Indian Scenario -The DIPSI Guidelines • 75 gm GCT with single PG at 2 hrs – • ≥ 140 mg/dL is GDM • ≥ 120 mg/dL is DGGT • Universal screening • First trimester, if negative at 24 – 28 weeks and then at 32 – 34 weeks

Management of gdm

MANAGEMENT ISSUES • Patient education • Medical Nutrition therapy • Pharmacological therapy • Glycemic monitoring: SMBG and targets • Fetal monitoring: ultrasound • Planning on delivery

Medical nutrition therapy • Goals • Achieve normoglycemia • Prevent ketosis • Provide adequate weight gain • Contribute to fetal well-being • Nutritional plan • Calorie allotment • Calorie distribution • CH2O intake

Calorie allotment • 30 kcal per kg current weight per day in pregnant women who are BMI 22 to 25. • 24 kcal per kg current weight per day in overweight pregnant women (BMI 26 to 29). • 12 to 15 kcal per kg current weight per day for morbidly obese pregnant women (BMI >30). • 40 kcal per kg current weight per day in pregnant women who are less than BMI 22.

Carb intake • Postprandial blood glucose concentrations can be blunted if the diet is carbohydrate restricted. Complex carbohydrates, such as those in starches and vegetables, are more nutrient dense and raise postprandial blood glucose concentrations less than simple sugars. • Carbohydrate intake is restricted to 33-40% of calories, with the remainder divided between protein (about 20%) and fat (about 40%). • With this calorie distribution, 75 to 80 percent of women with GDM will achieve normoglycemia.

Calorie distribution • Variable opinion • Most programs suggest three meals and three snacks; however, in overweight and obese women the snacks are often eliminated • Breakfast — The breakfast meal should be small (approximately 10%of total calories) to help maintain postprandial euglycemia. Carbohydrate intake at breakfast is also limited since insulin resistance is greatest in the morning. • Lunch — 30% of total calories • Dinner — 30% of total calories • Snacks — Leftover calories (approximately 30% of total calories) are distributed, as needed, as snacks.

Monitoring BG • Atleast 4 times • Fasting and 3 one hr postprandial • Pre vs postprandial monitoring • Better glycemic control (HbA1c value 6.5 versus 8.1 percent) • A lower incidence of large-for-gestational age infants (12 versus 42 percent) • A lower rate of cesarean delivery for cephalopelvic disproportion (12 versus 36 percent)

Monitoring BG • Home monitoring • Maintain log book • Use a memory meter • Calibrate the glucometer frequently • HbA1C • Ancillary test for feedback to the patient • Lower values when compared to nonpregnant state – lower BG and increase in red cell mass and slight decrease in life span – measured every 2-4 weeks • Target < 5.1%

Studies report no to moderate correlations between HbA1 and different components of the glucose profile when an HbA1 result of 4% to 5% includes a capillary blood glucose range of 50 to 160 mg/dL. • Levels of HbA1c are related to the rate of congenital anomalies and spontaneous early abortions in pre-existing diabetes, but the use of this measure, which retrospectively reflects glycemic profile in the last 10 weeks, for treatment evaluation in GDM is questionable. In addition, the association between glycosylated hemoglobin and pregnancy outcome in GDM or prediction of macrosomia is poor • Glycosylated protein and fructosamine widely variable and not yet established

Glycemic targets (ACOG) • ACOG • Fasting venous plasma ≤ 95 mg/dl • 1 hour postprandial ≤ 140 mg/dl • 2 hour postprandial ≤ 120 mg/dl • Pre-meal ≤ 100 mg/dl • A1C ≤ 6% • ADA • premeal 80-110 • 2 hr postmeal not more than 155 These are venous plasma targets, not glucometer targets

PHARMACOLOGICAL INTERVENTION • If the FPG at diagnosis is ≥ 120, can consider immediate therapy. • Otherwise, MNT for 2 weeks • If majority FPG (4/7) > 95 or PP > 120 then to start on insulin.

Insulin • ≈ 15% need insulin • Total dose varies. ≈ 0.7 to 2 units per kilogram (present pregnant weight) • FBG high – Night NPH ≈ 0.2 units/kg • PPBG high – bolus ≈ 1.5 units/10 gm CH2O for breakfast and ≈ 1 unit /10 gm CH2O for lunch and dinner • If both pre and postprandial BG high or if the woman's postprandial glucose levels can only be blunted if starvation ketosis occurs - four injection/day regimen. • Total 0.7 unit/kg up to week 18 • 0.8 unit/kg for weeks 18 to 26 • 0.9 unit/kg for weeks 26 to 36 • 1. unit/kg for weeks 36 to term. • In a morbidly obese woman, the initial doses of insulin may need to be increased to 1.5 to 2. units/kg to overcome the combined insulin resistance of pregnancy and obesity.

OHA in pregnancy • Systematic review by John Hopkins University • maternal glucose levels did not differ substantially between gravidae treated with insulin versus those treated with oral glucose-lowering agents • there was no consistent evidence of an increase in any adverse maternal or neonatal outcome with use of glyburide, acarbose, or metformin compared with use of insulin • Inconsistent data. ADA, ACOG, USFDA do not endorse.

OHA in pregnancy • Tolbutamide and chlorpropamide • Cross placenta. Fetal hperinsulinemia. Prolonged fetal hypoglycemia • Glibenclamide • Minimal transplacental transport • Observational studies – no excess anomalies or hypoglycemia • Only RCT – 404 women. Glib vs insulin. No difference

second-generation sulfonylureas especially glyburide, do not significantly cross the diabetic or nondiabetic placenta. Fetal concentrations reached no more than 1% to 2% of maternal concentrations. • tolbutamide diffused across the placenta most freely, followed by chlorpropamide, then glipizide, with glyburide crossing the least. • Metformin crosses placenta – not teratogenic in rat models

OHA in pregnancy • Metformin • Category B • No adverse outcome after first trimester • Second, third trimester safe and effective • Vs. insulin – no serious adverse effects • No studies vs. glibenclamide • Acarbose • Two prelim studies • Thiazolidinediones and GLP-1 • Not studied

• More by User

Gestational Diabetes Mellitus

Pat Sonnenstuhl,ARNP, CNM. 2. Introduction. Following appropriate screening guidelines, understanding causation and associated conditions, and effectively managing the client with GDM can improve both short term and long term health conditions associated with GDM. Pat Sonnenstuhl,ARNP, CNM. 3. Definitions.

340 views • 0 slides

Gestational Diabetes

Gestational Diabetes. Pennington Biomedical Research Center Division of Education. Gestational Diabetes. This diagnosis is given when a woman, who has never had diabetes before, gets diabetes or has high blood sugar, when she is pregnant.

942 views • 43 slides

Gestational Diabetes. Nutrition During Pregnancy. Gestational Diabetes. An important aspect of nutrition management of diabetes during pregnancy is prevention of excessive weight gain.

956 views • 20 slides

Gestational Diabetes. Adapted from: Turok DK, Ratcliff SD, Baxley EG. Management of Gestational Diabetes Mellitus. Am Fam Physician 2003; 68:1767-72. Gestational Diabetes. Defined as: Glucose intolerance that begins, or is first recognized, during pregnancy. Maternal Complications

785 views • 18 slides

Gestational Diabetes Mellitus. Dr. R V S N Sarma., M.D., M.Sc., (Canada) Consultant Physician &amp; Chest Specialist Visit us at: www.drsarma.in. Gestational Diabetes Mellitus. Is it physiological? Is it a disease? Should we screen for gdm ? Does it require treatment?

1.85k views • 45 slides

Gestational Diabetes. Testing Paradigms in a Rural Office November 7, 2014. Learning Objectives. Understand normal glucose levels in pregnancy. Define Gestational Diabetes Mellitus Understand testing for Gestational Diabetes Mellitus. What's normal?.

434 views • 10 slides

Gestational Diabetes Mellitus. Dr. Hema Divakar. Director, Divakar’s Hospital for Women, Bangalore. Secretary General, ICOG Former Vice president FOGSI Lots of publication on Diabetes in pregnancy. Gestational Diabetes Mellitus. Diagnosed first time in pregnancy May not last after.

889 views • 66 slides

Gestational Diabetes . Bashir Taha Salih MD Germany , F RCOG UK Consultant &amp; Chief Obstetric Medicine Corniche Hospital Abu Dhabi Kuwait April 27 th 2014. Contents. Introduction Physiology What’s new in GDM ? In Screening In Management Conclusion. Introduction.

4.7k views • 82 slides

Gestational Diabetes Mellitus: The Importance of Intervention

Presented by Erin Bostic. Gestational Diabetes Mellitus: The Importance of Intervention. Sessions with Registered Dietitians in order to discuss issues pertaining to gestational diabetes and what nutritional needs must be met in order for pregnancy to proceed in a positive manner.

327 views • 15 slides

GESTATIONAL DIABETES MELLITUS - CURRENT CONCEPTS

Dr.Vivek Sundaram.MD.DNB.MRCP(UK) Consultant – Internal Medicine,Diabetes &amp; Critical Care Sundaram Hospital,Trichy. GESTATIONAL DIABETES MELLITUS - CURRENT CONCEPTS. Watching TV for 2 hours/day increases Risk of diabetes by 20%....JAMA,June 2011. ARETAEUS(200 A.D.)

763 views • 48 slides

GESTATIONAL DIABETES MELLITUS

GESTATIONAL DIABETES MELLITUS. 2003 Clinical Practice Guidelines for the Prevention and Management of Diabetes in Canada. RISK FACTORS FOR GDM. Previous diagnosis of GDM Previous delivery of a macrosomic infant

286 views • 14 slides

Gestational diabetes mellitus. Piyawadee Wuttikonsammakit, M.D. GDM. Prevalence of diagnosed diabetes has increased : 14.5 (1991)  47.9 cases/1000 (2003) Increasing prevalence of type 2 diabetes in younger people

1.04k views • 63 slides

Gestational Diabetes. Just the Facts. Diabetes is the most common metabolic disorder of pregnancy 3-5% of all pregnancies Affects more than 150,000 pregnancies each year More than 7,000 are of women with Type 1 diabetes

1.68k views • 31 slides

Gestational Diabetes Mellitus. Helping Your Client Make Healthy Lifestyle Choices. Introduction.

1.5k views • 103 slides

EPIDEMIOLOGY IN GESTATIONAL DIABETES MELLITUS

EPIDEMIOLOGY IN GESTATIONAL DIABETES MELLITUS. Methodology. Dr. Nam-Han Cho Associate Professor of Preventive Medicine Director of Center for Clinical Epidemiology Ajou University School of Medicine Suwon, Korea. GESTATIONAL DIABETES MELLITUS.

507 views • 19 slides

Gestational Diabetes Mellitus. Amy Hansen Concordia College. Objectives. Be able to describe gestational diabetes Identify who is at risk for gestational diabetes Describe the diagnosis of gestational diabetes Identify management options for gestational diabetes. Definition.

762 views • 23 slides

Gestational Diabetes. Definition. Any degree of glucose intolerance with onset or 1 st recognition during pregnancy. Diabetes Care, 2003 Jan:26(1):s103 prevalence 1.4 – 14% UTD 11.2. Etiology. Early pregnancy

1.03k views • 23 slides

Gestational diabetes

Gestational diabetes. This is a type of diabetes that some women get during pregnancy. Between 2 and 10 percent of expectant mothers develop this condition, making it one of the most common health problems of pregnancy. How will I know if I have gestational diabetes? *Pregnancy Weight Tracker

423 views • 8 slides

Gestational Diabetes Mellitus case studies by Diabetesasia.org

Our aim is to alleviate human suffering related to diabetes and its complications among those least able to withstand the burden of the disease. From 2002 to March 2017, the World Diabetes Foundation provided USD 130 million in funding to 511 projects in 115 countries. For every dollar spent, the Foundation raises approximately 2 dollars in cash or as in-kind donations from other sources. The total value of the WDF project portfolio reached USD 377 million, excluding WDF’s own advocacy and strategic platforms.

248 views • 21 slides

Nursing, Maternity

75 views • 1 slides

ANAESTHETIC MANAGEMENT OF DIABETES MELLITUS AND GESTATIONAL DIABETES

ANAESTHETIC MANAGEMENT OF DIABETES MELLITUS AND GESTATIONAL DIABETES. Anaesthetic management of diabetes includes Preoperative evaluation Intraoperative management Postoperative management. Preoperative evaluation.

2.36k views • 90 slides

Gestational diabetes. metabolic disease result from underproduction of insulin which effect CHO , fat &amp;protein metabolism During pregnancy 1.preexisting 2.gestational. Homeostasis during pregnancy NP - FBS maintained 4-5 mmol/l

349 views • 15 slides

• Practice Test
• Fundamentals of Nursing
• Anatomy and Physiology
• Medical and Surgical Nursing
• Perioperative Nursing
• Psychiatric Mental Health Nursing
• Maternal & Child Nursing
• Community Health Nursing
• Pathophysiology
• Nursing Research
• Study Guide and Strategies
• Nursing Videos
• Work for Us!
• Privacy Policy

Gestational Diabetes Mellitus Case Study

Gestational diabetes mellitus (GDM), also known as type III diabetes mellitus, is one of the most common types of diabetes mellitus and considered the most common complication of pregnancy. This health problem is like pregnancy-induced hypertension (PIH) that develops during pregnancy and disappears after the delivery of the fetus, or as the maternal body returns to its pre-pregnant state. Gestational diabetes mellitus may or may not with co-existing maternal diabetes. It heightens the level of diabetes (if with previous diabetes) by a notch in response to the rise in fetal carbohydrate demand. 40% of pregnant mothers who develop GDM will eventually develop non-insulin-dependent diabetes mellitus (NIDDM or type II DM) within 5 years.

FACTS ABOUT INSULIN

Knowing the facts about insulin facilitates the understanding of gestational diabetes mellitus. Or any form of diabetes for that matter. This creates/develops ideas on how and why such health problems occur.

• The insulin is a normal body hormone that is produced by the beta cells of the Islets of Langerhans in the pancreas.
• The release of insulin is regulated by negative feedback in response to high glucose levels. The high glucose level may come from excessive glucagon action or high carbohydrate intake.
• The insulin secretion of the pancreas and its action on the liver makes it maintain a normal value of 80-120 mg/dL.
• Carbohydrates— utilization of glucose by the cells
• Proteins— conversion of amino acids to replace muscle tissues
• Fats— conversion of excess glucose to fatty acids and store them to adipose tissues
• Endothelial and nerve cells are the only cells/tissues that can use glucose even without insulin.
• Low insulin level causes the rise in plasma glucose concentration and glycosuria.
• Diabetes mellitus develops as the body secretes a low amount or as body cells reject its utilization.

ANATOMY AND PHYSIOLOGY

A normal body uses insulin as a channel for glucose to enter the cells for utilization. This process is also applicable to the fetus (during pregnancy) for growth and development. As the fetus grows, the maternal body executes an automatic response by doubling the level of glucose level through lowering insulin secretion and with the aid of some gestational hormones that antagonize the effects of insulin, a process known as a protective mechanism. Along with this, this mechanism causes the rise of placental lactogen, estrogen, and progesterone to cause the following effects: 1. antagonizes the effects of insulin, 2. prolong the elevation of stress hormones (cortisol, epinephrine, and glucagon), and 3. degradation of insulin by the placenta. The total effect of these mechanisms raises the maternal glucose level for fetal usage. Hyperglycemia normally occurs with a protective mechanism that predisposes a pregnant mother in the triggering of her pre-diabetic state or heightens an existing diabetes mellitus.

The effects of pregnancy on diabetes mellitus are summarized as:

• The first trimester— glucose level is relatively stable or may decrease
• The second trimester— there is a rapid increase in glucose level
• The third trimester— there is a rapid decrease in glucose level and return to its pre-pregnant state.

CAUSES AND INCIDENCE

The primary cause is almost the same as the other types of diabetes . The inability of the body to produce or synthesize a sufficient amount of insulin in response to glucose level (as in type I DM), or the body’s rejection of insulin (as in type II DM) shows a significant relationship on the development of any form of diabetes. The existence of either of these problems, plus, the interaction of the protective mechanisms in pregnancy doubles the occurrence of GDM.

The incidence of gestational diabetes mellitus is almost 3% in all pregnancies and 2% in all women with diabetes before pregnancy.

GDM causes a high incidence of fetal morbidity and unwanted complications such as polyhydramnios and macrosomia in fetus.

RISK FACTORS

For some clear and unclear pathological reasons, the following are considered the risk factors in the occurrence/development of GDM:

• Family history of DM
• Age of 45 or older (when got pregnant)
• Previous delivery of a baby weighing 9 lbs or more
• History of any autoimmune disease
• Belonging to/with ethnic background from African Americans, Latino, and Native Americans
• History of previous GDM
• With any level of hypertension
• With elevated high-density lipoprotein

SIGNS AND SYMPTOMS

The clinical manifestations of gestational diabetes mellitus coincide with the signs and symptoms of the other types of diabetes mellitus. These are popularly known as the “3 P’s” or polydipsia (excessive thirst), polyphagia (excessive hunger), and polyuria (frequent urination). Aside from these manifestations, there are also other signs and symptoms that are general manifestations and pregnancy-specific manifestations.

PATHOPHYSIOLOGY

COMPLICATIONS

The chronic effects or the uncontrolled glucose level during pregnancy would lead to the development of the following complications:

• Urinary tract infection (UTI)
• Infertility
• Preterm labor and delivery
• Pregnancy-induced hypertension (PIH)- pre-eclampsia and eclampsia
• Congenital anomalies
• Spontaneous abortion

Also, a woman who developed or experienced gestational diabetes mellitus is expected to have type II diabetes mellitus within 5 years for the rest of her life.

The prognosis or the chance of the mother and/or fetus for survival depends on the maternal ability to tolerate and adjust to high glucose levels, medical management, and obedience to the treatment regimen. This means that the more cooperative and responsive the mother to the treatment regimen is, the better chances of both maternal and fetal well being are.

The performance of the following diagnostic tests aims to determine the level of diabetes present in the pregnant mother and determine its extent of damage or impending effects. This serves as the basis for the plan of care for the mother and the fetus.

• Blood glucose monitoring— this can either be done through fasting blood sugar (FBS) or randomly. This reveals the glucose level and indicates the plan of care needed.
• Glucose tolerance test (GTT)— to evaluate the response of insulin to loading glucose.
• Glycated hemoglobin (Glycohemoglobin)— measures glycemic control by evaluating the attachment of glucose to freely permeable erythrocytes during their whole life cycle.
• C-peptide Assay (connecting peptide assay)— useful when the presence of insulin antibodies interferes with direct insulin assay.
• Fructosamine assay— is much more useful than glycosylated hemoglobin tests in cases of hemoglobin variants.
• Urine glucose and ketone monitoring— may be performed in cases where blood glucose monitoring is not available, but, is not as accurate as of the former.
• Amniocentesis
• Non-stress test

NURSING DIAGNOSES

• Altered nutrition, more or less than body requirements related to weight gain.
• High-risk pregnancy: high risk for infection, ketosis, fetal demise, cephalopelvic disproportion, polyhydramnios, congenital anomalies, preterm labor.
• Knowledge deficit related to disease and insulin use and interaction.

The overall goal of management for gestational diabetes mellitus is the control of the maternal glucose level and keep it on a normal or near-normal level to prevent the development of complications that might compromise both the mother and the fetus. The most significant of these managements is the use of insulin. This is the most potent, yet, requires accuracy and monitoring of its unwanted effect (hypoglycemia) that brings immediate danger to both the mother and the fetus. Proper timing, dosage, and knowledge on counteractions of its over-reaction are vital concepts to be incorporated in health education.

Along with this, health promotion and disease prevention activities like diet, exercise, and fetal monitoring are of great importance.

NURSING MANAGEMENTS

History taking on:

• First presentation of the manifestations of diabetes (3 P’s)
• First diagnosis of DM
• Family members with DM

Review of systems:

• Weight gain, increasing fatigue/weakness/tiredness
• Skin lesions, infections, hydration, signs of poor wound healing
• Changes in vision—floaters, halos, blurred vision, dry/burning eyes, cataract, glaucoma
• Gingivitis, periodontal disease
• Orthostatic hypotension, cold extremities, weak pedal pulses
• Diarrhea, constipation, early satiety, bloating, flatulence, hunger and thirst
• Frequent urination, nocturia, vaginal discharge
• Numbness and tingling of the extremities, decrease pain and temperature sensation

Intervention

1. Nutrition

• Assess the timing and content of meals
• Instruct on importance of a well-balanced diet
• Explain the importance of exercise
• Plan for a weight reduction course

2. Insulin use

• Encourage verbalization of feelings
• Demonstrate and explain insulin therapy
• Allow the client to do self-administration
• Review mastery of the whole process

3.   Injury from hypoglycemia

• Monitor maternal blood glucose level
• Instruct on insulin-activity-diet interaction
• Teach on the signs and symptoms of hypoglycemia
• Teach/present list of things/foods that need to be available at all times (in cases of hypoglycaemic attacks)
• Have an identification band indicating the health condition (DM) for fainting instances

4.  Activity tolerance

• Plan for regular exercise
• Increase carbohydrate intake before exercise
• Instruct to avoid exercise if blood glucose level exceeds 250 mg/dL and urine ketones are present
• Advise to use abdomen for insulin injection if arms and legs are used for exercise

5.  Skin integrity

• Avoid alcohol use, instead, lotion
• Teach on proper foot care
• Advice to stop smoking and alcohol use

6. Fetal well-being

• Continuous monitoring of fetal activities and fetal heart tone
• Monitor fetal activities during maternal activities
• Monitor early signs of labor
• Advice to report of any discharge coming from the vagina
• Monitor daily weight and advice to report on rapid weight gain

7. Educative

• Teach on lifestyle modifications
• Advice to see  psychologists with other family members for therapy on the possibilities of fetal abnormalities
• Advice to call emergency response team in cases of emergency
• Advise to religiously follow health instructions  
• Bodyweight is within the normal range for the age of gestation.
• Demonstrates proper technique in self-administration of insulin
• No episodes of hypoglycemia as claimed by the client
• No skin problems/lesions
• Verbalizes readiness on the possible fetal defects.
•   Stable fetal heart rate

RELATED ARTICLES MORE FROM AUTHOR

Anaphylactic shock case study -the impending doom, ectopic pregnancy case study, chronic suppurative otitis media case study, pregnacy induced hypertension (pih) case study, leave a reply cancel reply.

Save my name, email, and website in this browser for the next time I comment.

Obstetrics and Gynaecology

At a glance, fourth edition errol r. norwitz, john o. schorge.

• Multiple Choice
• Your feedback
• Become a reviewer
• More student books
• Student Apps
• Join an e-mail list

Find out more

Case Studies

Case 9: gestational diabetes.

A 28-year-old G 4 P 2 presents to your office for a routine prenatal visit at 24 weeks’ gestation. Her physical examination is unremarkable and fetal wellbeing is reassuring. You recommend testing for gestational diabetes mellitus (GDM).

1. What is GDM?

Show Answer

Correct answer: GDM refers to any form of glucose intolerance with the onset of pregnancy or first recognized during pregnancy, and complicates approximately 5% of all pregnancies. It likely includes some women who have undiagnosed pregestational diabetes.

2. Should everyone be screened for GDM? If so, at what gestational age should they be screened?

Correct answer: Patients with GDM are typically asymptomatic. There is a small cohort of pregnant women in whom routine screening for GDM is not cost-effective. These are women under age 25 who have normal body mass index (BMI 2 ), no first-degree relatives with diabetes, no risk factors (such as a history of GDM, insulin resistance/PCOS [polycystic ovarian syndrome], a prior macrosomic infant, a prior unexplained late fetal demise, and women with persistent glycosuria), and who are not members of ethnic or racial groups with a high prevalence of diabetes (such as Hispanic, Native American, Asian, or African–American). As such patients are rare, most experts and organizations recommend screening for GDM in all pregnant women. The ideal time to screen for GDM is 24–28 weeks of gestation. For women at high risk of developing GDM (listed above), early screening for GDM is recommended at the first prenatal visit. If the early screen is negative, it should be repeated at 24–28 weeks.

3. Her 1-hour GLT is 182 mg/dL. Does she have GDM?

Correct answer: The most common screening test for GDM is the glucose load test (GLT) – also known as the glucose challenge test (GCT) – which is a non-fasting 50-g oral glucose challenge followed by a venous plasma glucose measurement at 1 hour. Most authorities consider the GLT to be positive if the 1-hour glucose measurement is >140 mg/dL. Use of a lower cut-off (such as >130 mg/dL) will increase the detection rate of women with GDM, but will result in a substantial increase in the false-positive rate.

There is no GLT cut-off that should be regarded as diagnostic of GDM . A definitive diagnosis of GDM requires a 3-hour glucose tolerance test (GTT). In pregnancy, the GTT involves 3 days of carbohydrate loading followed by a 100-g oral glucose challenge after an overnight fast. Venous plasma glucose is measured fasting and at 1 hour, 2 hours, and 3 hours. Although there is agreement that two or more abnormal values are required to confirm the diagnosis, there is little consensus about the glucose values that define the upper range of normal in pregnancy (see below). Most institutions use the National Diabetes Data Group (NDDG) or Carpenter and Coustan cut-offs. Measurement of glycated hemoglobin (HbA1c) levels is not useful in making the diagnosis of GDM, although it may be useful in the diagnosis of pregestational diabetes.

Plasma glucose values (mg/dL) (mmol/L) *

Sacks et al.

Carpenter and Coustan

* Values in parentheses are mmol/L.

4. All four values of her 3-hour GTT are elevated and her fasting glucose level is 127 mg/dL. How would you manage her GDM? How long would you allow her to try dietary restriction before adding a hypoglycemic agent?

Correct answer: GDM poses little risk to the mother. Such women are not at risk of diabetic ketoacidosis (DKA), which is primarily a disease of absolute insulin deficiency. However, GDM has been associated with an increase in infant birth trauma and perinatal morbidity and mortality. The risk to the fetus/infant is directly related to its size. Fetal macrosomia is defined as an estimated fetal weight (not birthweight) of ≥4,500 g. It is a single cut-off that is unrelated to gestational age, the sex of the baby, or the presence or absence of diabetes, or to the actual birthweight.

The goal of antepartum treatment of GDM is to prevent fetal macrosomia and its resultant complications by maintaining maternal blood glucose at desirable levels throughout gestation, defined as a fasting glucose level 95 mg/dL, treatment can be started immediately because “you can’t diet more than fasting.”

Insulin (which has to be given several times a day by injection) remains the “gold standard” for the medical management of GDM. The use of oral hypoglycemic agents has traditionally been avoided in pregnancy because of concerns over fetal teratogenesis and prolonged neonatal hypoglycemia. However, recent studies suggest that second-generation hypoglycemic agents (glyburide, glipizide) do not cross the placenta, are safe in pregnancy, and can achieve adequate glycemic control in 85% of pregnancies complicated by GDM.

5. The estimated fetal weight at 38 weeks’ gestation is 4,600 g (10 lb 2 oz). She has had six prior uncomplicated vaginal deliveries. How would you counsel her about delivery?

Correct answer: As noted above, the complications of GDM are related primarily to fetal macrosomia, including an increased risk of cesarean section delivery, operative vaginal delivery, and birth injury to both the mother (vaginal, perineal, and rectal trauma) and fetus (including orthopedic and neurologic injury). Shoulder dystocia with resultant brachial plexus injury (Erb’s palsy) is a serious consequence of fetal macrosomia, and further increased in the setting of GDM because the macrosomia of diabetes is associated with increased diameters in the upper thorax of the fetus.

The use of elective cesarean section delivery to reduce the risk of maternal and fetal birth injury in the setting of fetal macrosomia remains controversial. According to current ACOG guidelines, an elective cesarean section delivery at or after 39 weeks’ gestation should be recommended for all non-diabetic women who have a fetus with an estimated fetal weight (EFW) ≥5,000 g (or ≥4,500 g in a diabetic individual) to minimize the risk of birth trauma. Furthermore, it is recommended that a discussion be held about the safest route of delivery with non-diabetic women who have a fetus with an EFW ≥4,500 g (or ≥4,000 g in a diabetic individual) and that this discussion be documented in the medical record.

6. After extensive counseling, the couple decline elective cesarean section delivery. She is now 38 weeks’ gestation. How should she be managed at this point in time?

Correct answer: If the patient declines elective cesarean section delivery, spontaneous labor should be awaited. Induction of labor for so-called “impending macrosomia” does not decrease the risk of cesarean section delivery or intrapartum complications, and is therefore not routinely recommended. If she is still undelivered at 41 weeks’ gestation, she should be counseled again about induction of labor and/or elective cesarean section.

During labor, maternal glucose levels should be maintained at 100–120 mg/dL to minimize the risk of intrapartum fetal hypoxic–ischemic injury. Continuous fetal monitoring is recommended throughout labor and the progress of labor should be carefully charted. Internal monitors such as an intrauterine pressure catheter (IUPC) and/or fetal scalp electrode can be used, if indicated. Neonatal blood glucose levels should be measured within 1 hour of birth and early feeding encouraged.

Delivery of the fetus and placenta effectively removes the source of the anti-insulin (counter-regulatory) hormones that cause GDM. As such, no further management is required in the immediate postpartum period. A 2-hour non-pregnant GTT should be performed at 6–8 weeks postpartum in all women with GDM to exclude pre-gestational diabetes.

See Chapter 45.

Print Answers | « Previous Case | Next Case »

Gestational diabetes

The two case studies presented here provide an overview of gestational diabetes (GDM). The scenarios cover the screening, identification and management of GDM, as well as the steps that should be taken to screen for, and ideally prevent, development of type 2 diabetes in the long term post-pregnancy. By actively engaging with the case studies, readers will feel more confident and empowered to manage GDM effectively in the future.

Useful resources

At a glance factsheet: Diabetes before, during and after pregnancy. Diabetes & Primary Care 23 : 73–4

Bellamy L, Casas JP, Hingorani AD, Williams D (2009) Type 2 diabetes mellitus after gestational diabetes: A systematic review and meta-analysis. Lancet 373 : 1773–9

Catalano PM (2014) Trying to understand gestational diabetes. Diabet Med 31 : 273–81

ElSayed NA, Aleppo G, Aroda VR et al; American Diabetes Association (2023a) 2. Classification and Diagnosis of Diabetes: Standards of Care in Diabetes–2023. Diabetes Care 46 (Suppl 1): S19–40

ElSayed NA, Aleppo G, Aroda VR et al; American Diabetes Association (2023b) 15. Management of Diabetes in Pregnancy: Standards of Care in Diabetes–2023. Diabetes Care 46 (Suppl 1): S254–66

Horvath K, Koch K, Jeitler K et al (2010) Effects of treatment in women with gestational diabetes mellitus: Systematic review and meta-analysis. BMJ 340 : c1395

Iftakhar R (2012) Benefit of metformin in reducing weight gain and insulin requirements in pregnancies complicated by gestational diabetes. Diabesity in Practice 3 : 108–13

Knowler WC, Barrett-Connor E, Fowler SE et al; Diabetes Prevention Program Research Group (2002) Reduction in the incidence of type 2 diabetes with lifestyle intervention or metformin. N Engl J Med 346 : 393–403

Lindström J, Louheranta A, Mannelin M et al; Finnish Diabetes Prevention Study Group (2003) The Finnish Diabetes Prevention Study (DPS): Lifestyle intervention and 3-year results on diet and physical activity. Diabetes Care 26 : 3230–6

McGovern A, Butler L, Munro M, de Lusignan S (2014) Gestational diabetes mellitus follow-up in primary care: A missed opportunity. Diabetes & Primary Care 16 : 60

Meltzer SJ (2010) Treatment of gestational diabetes. BMJ 340 : c1708

NICE (2017) Type 2 diabetes: prevention in people at high risk [PH38]. Available at: https://www.nice.org.uk/guidance/ph38

NICE (2020) Diabetes in pregnancy: management from preconception to the postnatal period [NG3]. Available at: https://www.nice.org.uk/guidance/ng3

NICE (2022) Type 2 diabetes in adults: management [NG28]. Available at: https://www.nice.org.uk/guidance/ng28

Noctor E, Dunne F (2017) A practical guide to pregnancy complicated by diabetes. Diabetes & Primary Care 19 : 35–4

Rowan JA, Hague WM, Gao W et al; MiG Trial Investigators (2008) Metformin versus insulin for the treatment of gestational diabetes. N Engl J Med 358 : 2003–15

Silverman BL, Rizzo TA, Cho NH, Metzger BE (1998) Long-term effects of the intrauterine environment. The Northwestern University Diabetes in Pregnancy Center. Diabetes Care 21 (Suppl 2): B142–9

Questions Summary

0 of 17 Questions completed

Information

You have already completed the questions before. Hence you can not start it again.

Questions is loading…

You must sign in or sign up to start the questions.

You must first complete the following:

Questions complete. Results are being recorded.

Time has elapsed

• Not categorized 0%

1 . Question

Section 1 – holly.

Holly is a 31-year-old lady who is now 26 weeks into her first pregnancy. She sees you with a 3-day history of dysuria and frequency of micturition. There is no history of abdominal pain or fever.

A urine dipstick reveals a positive test for nitrites and the presence of white cells. It also shows glycosuria ++.

What is your assessment of Holly’s situation?

This response will be awarded full points automatically, but it can be reviewed and adjusted after submission.

2 . Question

Holly appears to have a lower urinary tract infection (UTI). The glycosuria suggests she may have gestational diabetes (GDM), although it is possible she may have entered the pregnancy with undiagnosed type 2 diabetes.

What factors would you look for in Holly’s history that could suggest she is at high risk of gestational diabetes?

3 . Question

Risk factors for developing GDM include (NICE, 2020):

• BMI >30 kg/m 2 .
• Previous GDM.
• Previous macrosomic baby weighing 4.5 kg or more.
• Family history of diabetes (first-degree relative).
• Ethnic background with high prevalence of diabetes (South or East Asian, African–Caribbean, Middle Eastern).

  Further considerations regarding the likelihood of GDM include advanced maternal age (>35 years), a history of polycystic ovarian syndrome (a condition of increased insulin resistance) and previous unexplained fetal death.

Holly had a pre-pregnancy BMI of 29.4 kg/m 2 but no family history of type 2 diabetes.

What action would you take?

4 . Question

In addition to treating the UTI, Holly needs to be investigated for possible GDM.

Holly is prescribed a course of cephalexin (a safe and effective antibiotic in pregnancy) and encouraged to drink plenty of fluids. A mid-stream urine sample is sent off for laboratory analysis. A fingerprick glucose reading demonstrates a glucose level of 11.7 mmol/L. A blood sample is sent off for HbA 1c assessment (HbA 1c will not accurately reflect recent onset of diabetes in a pregnancy but could point toward the likelihood of pre-existing undiagnosed type 2 diabetes when entering the pregnancy).

NICE (2020) recommends formal testing for GDM if pregnant women have:

• Glycosuria of ++ or above on one occasion.
• Glycosuria of + or above on more than one occasion.

  In Holly’s case, local maternity services are contacted and an oral glucose tolerance test (OGTT) is arranged to ascertain the diagnosis of GDM. In the meantime, the importance of controlling blood glucose levels in pregnancy is explained to her and she is advised on eating a healthy diet and taking exercise to help achieve this.

Can you explain why gestational diabetes arises?

5 . Question

GDM is defined as diabetes diagnosed during the second and third trimester of pregnancy that was not clearly overt diabetes prior to gestation (ElSayed et al, 2023). As pregnancy progresses, insulin resistance rises and this is normally countered by increasing insulin production. However, women with GDM inherently have a greater degree of insulin resistance compared to those without GDM, and this coupled with reduced beta-cell capacity to produce the required insulin response leads to maternal hyperglycaemia (Catalano, 2014).

GDM is a more common cause of diabetes in pregnancy than pre-existing diabetes, accounting for nearly 90% of cases, and the prevalence is increasing in line with the demographic rise in body mass index (Noctor and Dunne, 2017).

Why is it important to identify gestational diabetes?

6 . Question

Maternal hyperglycaemia from poorly controlled GDM leads to fetal macrosomia. The consequence at delivery is an increased risk of obstructed delivery from shoulder dystocia, clavicular fracture and brachial plexus injury (Melzer, 2010).

Fetal hyperglycaemia is associated with a rise in congenital abnormalities. The incidence of neonatal respiratory distress, meconium aspiration and jaundice are all raised following GDM, and the carry-over of fetal hyperinsulinaemia post-delivery can lead to neonatal hypoglycaemia. All of the above are common reasons for admission to the neonatal intensive care unit (Noctor and Dunne, 2017).

For the mother with GDM, the incidence of pre-eclampsia, polyhydramnios, pre- and post-partum haemorrhage, and infection are all increased. Failure to progress with labour and delivery by caesarean section are more frequent with pregnancy complicated by GDM (Noctor and Dunne, 2017).

In the longer term, there is an association between offspring exposed to in utero GDM and the later occurrence of obesity and glucose intolerance (Silverman et al, 1998). Women who have had GDM are at increased risk of developing type 2 diabetes (Bellamy et al, 2009).

It is important, therefore, that primary and community care practitioners can appropriately advise women at high risk of GDM, understand the management of GDM and, as indicated later in this case study, assume responsibility for post-pregnancy follow-up of GDM (McGovern et al, 2014).

What treatments for diabetes are considered safe and effective in gestational diabetes?

7 . Question

Whilst the joint diabetes and antenatal clinic will assume responsibility for the majority of treatment decisions, primary healthcare workers need to be aware of GDM management. Effective treatment of GDM has been demonstrated to reduce fetal macrosomia, fetal and maternal birth trauma, and perinatal death (Horvath et al, 2010).

Lifestyle change constitutes the first-line treatment of GDM. NICE advises that a trial of diet and exercise should be offered to women with GDM without complications who have a fasting plasma glucose (FPG) level below 7 mmol/L at diagnosis (NICE, 2020). If dietary change and physical exercise prove ineffective in achieving blood glucose targets within 1–2 weeks, medical treatment should be commenced. In the absence of contraindications, this would usually be metformin.

For those women with an FPG of 7 mmol/L or above at diagnosis, and for women with an FPG of 6.0–6.9 mmol/L who have a complication such as fetal macrosomia or hydramnios, immediate medical treatment with insulin (with or without metformin), alongside lifestyle measures, is recommended (NICE, 2020).

Metformin, although not licensed for use in pregnancy, is considered safe and has gained ground as an option for treating GDM when lifestyle measures are insufficient. The risk of perinatal complications appears to be no higher than in insulin-treated patients (Rowan et al, 2008) and there is the advantage of less weight gain, less monitoring and reduced risk of hypoglycaemia in comparison to insulin (Iftakhar, 2012). Should gastrointestinal side effects prove troublesome with metformin, the modified-release preparation may be tried. However, if glycaemic control is inadequate then insulin should be promptly initiated.

Insulin therapy has traditionally been regarded as the first-line medical treatment in GDM and remains the preferred treatment of the American Diabetes Association (ElSayed et al, 2022b). Often a basal–bolus insulin regimen will be required, and insulin doses can be adjusted on a frequent basis, noting that requirements are likely to rise as pregnancy progresses, reflecting increasing insulin resistance. The rapid-acting insulin analogues (e.g. insulin aspart and insulin lispro) offer advantages in improved glycaemic control and reduced hypoglycaemia compared with human soluble insulins (NICE, 2020).

• Mark as read

8 . Question

Holly’s OGTT revealed an FPG of 6.7 mmol/L and a 2-hour plasma glucose of 9.4 mmol/L, confirming the diagnosis of GDM (thresholds for diagnosis: either FPG ≥5.6 mmol/L or 2-hour plasma glucose ≥7.8 mmol/L), and she was reviewed in the joint diabetes and antenatal clinic.

The need to carefully control blood glucose levels was explained to Holly and she was offered lifestyle advice, instructed on glucose monitoring, referred to a dietitian and subsequently commenced on metformin.

What frequency of glucose monitoring should be advised for Holly, who is using metformin for her gestational diabetes?

9 . Question

Holly, as a person using oral medication to control GDM, should be encouraged to take fasting and 1-hour post-meal readings to guide treatment. This monitoring pattern would also be appropriate for those on dietary control alone and if insulin is administered as a basal injection alone.

10 . Question

Section 10 – nadia.

Nadia is a 34-year-old lady of Indian ethnic origin who is now 24 weeks into her second pregnancy, her last pregnancy being 7 years ago. Nadia’s BMI is 32.4 kg/m 2 and her father has type 2 diabetes. GDM was not, however, diagnosed during her first pregnancy and her first baby was born at term weighing 3.8 kg.

How would you assess Nadia’s risk of acquiring gestational diabetes?

11 . Question

Nadia’s ethnic origin, obesity and family history of type 2 diabetes place her at high risk of GDM.

These risk factors were identified by the midwives at booking, and Nadia is scheduled for an OGTT at 28 weeks’ gestation.

There are conflicting recommendations over screening arrangements and diagnostic criteria for GDM. NICE (2020) recommends an OGTT between 24 and 28 weeks’ gestation for those at high risk of GDM (or as soon as possible after booking if previous GDM), with the following diagnostic criteria:

• Fasting plasma glucose of 5.6 mmol/L or more.
• 2-hour plasma glucose of 7.8 mmol/L or more.

  The American Diabetes Association now recommends screening for diabetes (with an HbA 1c or fasting plasma glucose test) in those women with risk factors who are planning a pregnancy, so that those found to have diabetes can optimise their glucose control ahead of pregnancy (ElSayed et al, 2022a).

12 . Question

A diagnosis of GDM is made from Nadia’s OGTT (FPG 8.1 mmol/L; 2-hour plasma glucose 12.7 mmol/L). Nadia is accordingly referred to the joint diabetes and antenatal clinic.

Nadia is quickly established on a basal–bolus insulin regimen of Lantus and NovoRapid in the diabetes/antenatal clinic, provided with a meter to self-monitor her capillary glucose and set targets for glycaemic control. NovoRapid is licensed for use in pregnancy and the SmPC of Lantus advises that Lantus may be considered during pregnancy if clinically needed.

What frequency of glucose monitoring might you expect Nadia to undertake?

13 . Question

Intensive glucose monitoring is advised during a pregnancy affected by diabetes, and you should be prepared to issue more glucose test strips. For Nadia, on a basal–bolus insulin regimen, NICE (2020) recommends capillary blood glucose monitoring prior to meals (including fasting), 1-hour post-meals and before bedtime.

NICE (2020) recommends setting the same capillary plasma glucose target levels for women with GDM as for those with pre-existing diabetes. Thus, ideal glucose targets would be the following:

• Fasting: 5.3 mmol/L.
• 1 hour after meals: 7.8 mmol/L; or 2 hours after meals: 6.4 mmol/L.

  In practice, targets will need to be individualised, recognising the need to avoid problematic hypoglycaemia. In the case of women using insulin, such as Nadia, capillary glucose levels should be kept above 4 mmol/L. Women at risk of hypoglycaemia should be advised to carry a fast-acting form of glucose at all times.

It should be mentioned that continuous subcutaneous insulin infusion (an insulin pump) is an alternative to a basal–bolus insulin regimen for pregnant women who do not achieve adequate glucose control without troublesome hypoglycaemia. Real-time or intermittently scanned (flash) glucose monitoring is an option where there is severe hypoglycaemia (especially if there is hypoglycaemia unawareness) or where unstable glucose readings are problematic (NICE, 2020).

What role does primary care have in managing women with gestational diabetes?

14 . Question

Whilst management of GDM will primarily occur in the diabetes/antenatal clinic, women with GDM may, in addition to the usual pregnancy-related health issues, need support from practice nurses and GPs in blood glucose monitoring and interpretation, and reassurance that maintaining good glycaemic control will improve outcomes for their babies and themselves. Advice regarding medication use and side-effects, and in particular the recognition and treatment of hypoglycaemia for those using insulin, may be necessary.

Nadia is frequently reviewed in the diabetes/antenatal clinic and achieves satisfactory glycaemic control with her insulin regimen. She delivers a healthy girl at 39 weeks’ gestation without significant problems. Nadia’s insulin is stopped after delivery and glucose levels are checked and seen to be running below 10 mmol/L. It is also important to check baby’s glucose levels, as there is a risk of neonatal hypoglycaemia.

How should Nadia’s glucose control be assessed in the post-partum period?

15 . Question

Whilst diabetes medications used for GDM are usually stopped at delivery in the expectation that glucose levels will fall to pre-pregnancy levels, there is the possibility that hyperglycaemia will persist (and hence the need for glucose checks immediately following delivery).

Nadia should have a formal test for hyperglycaemia within 3 months of delivery, and there needs to be clarity as to who assumes responsibility for this.

NICE (2020) advises that women with GDM (whose blood glucose levels return to normal after delivery) should be offered a fasting plasma glucose (FPG) test at 6–13 weeks postpartum to exclude diabetes (pragmatically, this could be at the 6-week postnatal review); otherwise, beyond 13 weeks postpartum, an HbA 1c test can be offered.

• If FPG is ≥7.0 mmol/L or HbA 1c is ≥48 mmol/mol, a confirmatory test for type 2 diabetes should be carried out and type 2 diabetes pathways (NICE, 2022) should then be followed.
• If FPG is 6.0–6.9 mmol/L or HbA 1c is 39–47 mmol/mol, there is a high risk of developing type 2 diabetes. Lifestyle advice and an offer to refer to the NHS Diabetes Prevention Programme should follow.
• Note these are different HbA 1c risk thresholds than for “prediabetes” in the NICE (2017) PH38 advice, because they refer to a different population.

Nadia has an FPG test at 6 weeks post-delivery, which reveals an FPG <6.0 mmol/L, suggesting that she does not have prediabetes or type 2 diabetes.

What about Nadia’s future risk of developing type 2 diabetes?

16 . Question

Nadia’s GDM is a marker for insulin resistance and places her at increased risk of developing prediabetes and type 2 diabetes in the future compared to women without GDM (relative risk 7.4; Bellamy et al, 2009). Nadia should be alerted to the likelihood of recurrence of GDM in future pregnancies and of the possibility of type 2 diabetes in the future.

Nadia sees you at the clinic following her normal FPG test and asks about her GDM and its future implications.

What advice would you offer Nadia for the future, and what arrangements would you set in place for future screening of diabetes?

17 . Question

It is helpful to think that GDM confers “prediabetic status”. There is good evidence that lifestyle adjustment can prevent or delay the onset of diabetes (Knowler et al, 2002; Lindström et al, 2003). Encourage Nadia to be careful with her diet, take regular exercise and aim for weight loss – similar principles as for those with type 2 diabetes – as detailed in NICE public health guidance on prevention of type 2 diabetes (NICE, 2017). She is offered referral to the Healthier You NHS Diabetes Prevention Programme.

Nadia should be placed on annual recall, checking HbA 1c , lipids, renal function, weight and blood pressure.

With her history of GDM, in any future pregnancy Nadia should be offered early self-monitoring of blood glucose or an OGTT as soon as possible after booking (NICE, 2020).

In reality, there is a disappointingly low rate of both short-term and longer-term review of GDM, with rates of both around 20% in one study (McGovern et al, 2014). Possible reasons for this poor follow-up include lack of awareness amongst women with GDM, poor communication between secondary and primary care, a lack of consensus over responsibility for post-natal tests and missed opportunities in primary care for the annual review.

Share this article + Add to reading list – Remove from reading list

• At-a-glance factsheets
• How to... series
• Diabetes Distilled
• Supplements

Cardiovascular disease and type 2 diabetes

Primary and secondary prevention of CVD in people with type 2 diabetes.

12 Jun 2024

Non-diabetic hyperglycaemia – Prediabetes

Diagnosing and managing non-diabetic hyperglycaemia

16 Apr 2024

Dyslipidaemia and type 2 diabetes. Part 2: Statin-induced myalgia, secondary prevention of cardiovascular disease and using non-statin agents

Statin intolerance pathways and non-statin drugs for both primary and secondary prevention.

12 Feb 2024

Dyslipidaemia and type 2 diabetes. Part 1: Primary prevention of cardiovascular disease and use of statins

Assessing cardiovascular risk and using statins for primary prevention.

16 Nov 2023

Obesity and type 2 diabetes

Assessing and managing obesity in the context of type 2 diabetes.

20 Oct 2023

Early-onset type 2 diabetes in adults

The clinical implications, diagnosis and management of early-onset type 2 diabetes.

Erectile dysfunction in type 2 diabetes

Geoffrey has type 2 diabetes and is seeking help for erectile dysfunction (ED). What examinations, investigations and treatments would you consider?

Heart failure and type 2 diabetes

Mark and Jane present with symptoms suggestive of heart failure. How would you establish the diagnosis and which therapies would be effective?

The elderly and type 2 diabetes

Three elderly people require very different levels of care for their type 2 diabetes. How should you treat each of them appropriately?

Problems with the diabetic foot

Glenda, Sam and Proma all have established type 2 diabetes. Each presents with different foot problems. How would you interpret their symptoms?

25 Oct 2022

Recognition and management of pancreatogenic (type 3c) diabetes

Sarah was diagnosed with type 2 diabetes two years ago. Recently her glycaemic control has deteriorated and she is unwell. What are the implications?

18 Aug 2022

Pre-pregnancy care in diabetes

Georgia wants advice before trying for pregnancy, while Emily is determined to go ahead. Both have type 2 diabetes. What advice would you provide?

30 May 2022

Managing type 2 diabetes during Ramadan

Aabid and Jameela both have type 2 diabetes. Should they fast during Ramadan and, if so, how can they do it safely?

10 Mar 2022

Managing hypertension in diabetes – tricky cases

Winston, Lily and Mark have elevated blood pressure but, given their different case histories, how should each be treated?

Managing hypertension in diabetes – the basics

Brian is 52 years old. He has type 2 diabetes, is obese and his blood pressure was recently recorded as 167/97 mmHg.

Fatty liver disease and type 2 diabetes

Cassie, a 49-year-old with type 2 diabetes, is overweight, has hypertension and her liver function test results are elevated.

11 Oct 2021

Hypoglycaemia and type 2 diabetes

Four mini-scenarios to help build your skills in managing hypoglycaemia in people with type 2 diabetes.

12 Aug 2021

Steroid-induced hyperglycaemia

3 mini-case studies to take you through what it is necessary to consider in identifying and managing steroid-induced hyperglycaemia.

14 Jul 2021

Making a diagnosis of type 2 diabetes

Colin, Rao and Rachael each have signs of elevated blood glucose, but how should correct diagnoses be made?

18 May 2021

Type 2 diabetes and diabetic nephropathy

Meet Louise, a 56-year-old schoolteacher with type 2 diabetes and now showing signs of possible diabetic nephropathy.

The thin person with T2D Meet Jim, a 47-year-old electrician diagnosed with type 2 diabetes four years ago, now presenting with elevated HbA1c.

17 May 2021

Sign up to all DiabetesontheNet journals

• CPD Learning
• Diabetes & Primary Care
• Journal of Diabetes Nursing
• Diabetes Care for Children & Young People
• The Diabetic Foot Journal
• Diabetes Digest

Useful information

• Terms and conditions
• Privacy policy
• Editorial policies and ethics

By clicking ‘Subscribe’, you are agreeing that DiabetesontheNet.com are able to email you periodic newsletters. You may unsubscribe from these at any time. Your info is safe with us and we will never sell or trade your details. For information please review our Privacy Policy .

Are you a healthcare professional?  This website is for healthcare professionals only. To continue, please confirm that you are a healthcare professional below.

We use cookies  responsibly to ensure that we give you the best experience on our website. If you continue without changing your browser settings, we’ll assume that you are happy to receive all cookies on this website.  Read about how we use cookies .

Username or Email Address

Remember Me

User Details: UserFields

• Receive all email newsletters and site updates
• Diabetes & Primary Care (DPC)
• Journal of Diabetes Nursing (JDN)
• Diabetes Care for Children & Young People (DCCYP)
• The Diabetic Foot Journal (DFJ)
• Diabetes Digest (DD)

Registration confirmation will be emailed to you.

An official website of the United States government

The .gov means it’s official. Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

The site is secure. The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

• Publications
• Account settings

Preview improvements coming to the PMC website in October 2024. Learn More or Try it out now .

• Advanced Search
• Journal List
• AME Case Rep
• PMC11292075

Progression of gestational diabetes mellitus to pregnancy-associated fulminant type 1 diabetes: a case report

1 Department of Endocrinology, Hainan Hospital Affiliated Hospital of Hainan Medical University/Hainan General Hospital, Haikou, China;

Kaining Chen

Huibiao quan.

2 Department of Obstetrics, Hainan Hospital Affiliated Hospital of Hainan Medical University/Hainan General Hospital, Haikou, China

Associated Data

The article’s supplementary files as

Pregnancy-associated fulminant type 1 diabetes (PF) occurs during pregnancy or within 2 weeks of delivery. Although it occurs infrequently, it is associated with high fetal mortality rate. Few studies have examined whether PF is associated with gestational diabetes mellitus (GDM).

Case Description

A 29-year-old woman diagnosed with GDM at 24 weeks of gestation developed a fever, sore throat, nausea and vomiting at 29 weeks of gestation. Ketoacidosis was considered based on her blood ketone and glucose levels and the results of a blood gas analysis. Since the patient’s islet function declined rapidly, fluid replacement, insulin therapy, and other treatments were administered. The patient was ultimately diagnosed with PF, and has required ongoing insulin therapy. She delivered a healthy baby girl by elective cesarean section at 37-week gestation. Her blood glucose has been satisfactorily controlled over the 12 months since her acute presentation.

Conclusions

PF is characterized by poor maternal and infant outcomes and a high stillbirth rate. Blood glucose should be regularly monitored in pregnant women with GDM. A sudden increase in blood glucose may indicate the possibility of PF, which needs to be managed in a timely manner to avoid adverse pregnancy outcomes.

Highlight box

Key findings.

• Gestational diabetes mellitus (GDM) and gestational pregnancy-associated fulminant type 1 diabetes (PF) have different pathogenesis, and only a few patients have GDM before PF.

What is known and what is new?

• Fulminant type 1 diabetes mellitus (FT1DM) that occurs during pregnancy or the perinatal period is known as PF.

• PF is always without history of abnormal glucose metabolism. Here, we present a patient who developed PF during treatment but were first diagnosed with GDM.

What is the implication, and what should change now?

• Body mass index was not a predictor of PF; patients with GDM need to monitor their blood sugar regularly during pregnancy, and a sudden rise in blood sugar may alert them to turn into PF, which requires high attention and timely medical treatment to avoid adverse pregnancy outcomes.

Introduction

Pregnancy-associated fulminant type 1 diabetes (PF) occurs during pregnancy or within 2 weeks of delivery, has a low incidence, and is characterized by a rapid decline in islet cell function and the onset of ketoacidosis ( 1 ). It is a highly dangerous condition associated with a high incidence of stillbirth. The cause of PF is not yet clear. Gestational diabetes mellitus (GDM) occurs during pregnancy and is harmful to both the mother and fetus ( 2 ). Unfortunately, few studies have examined the possible correlation between GDM and PF.

The current patient was diagnosed with GDM in her second trimester, but subsequently represented with PF. The fetus survived after active treatment. This report summarizes the clinical features of this patient along with review of the relevant literature with the aim to extend understanding about PF and to prevent its misdiagnosis and mistreatment. We present this article in accordance with the CARE reporting checklist (available at https://acr.amegroups.com/article/view/10.21037/acr-24-52/rc ).

Case presentation

All the procedures performed in this study were conducted in accordance with the ethical standards of Hainan General Hospital and the Declaration of Helsinki (as revised in 2013). Written informed consent was obtained from the patient for the publication of this case report and the accompanying images. A copy of the written consent is available for review by the editorial office of this journal.

Chief complaints

A 29-year-old female in her 29 th gestational week was admitted to hospital on January 23, 2021. Over the 3 days prior, she had experienced fever, fatigue, mild sore throat, and cough without any obvious trigger. She also reported one day of nausea and vomiting and stated that fetal movements appeared to have decreased over the preceding 12 hours ( Table 1 ).

BMI, body mass index.

Five weeks earlier, she had been diagnosed with GDM after an oral glucose tolerance test (OGTT), which revealed a 1-hour postprandial glucose of 10.6 mmol/L ( Table 2 ) [diagnostic criteria for GDM developed by the International Association of Diabetes and Pregnancy Study Group (IADPSG) in 2010: GDM is diagnosed by meeting or exceeding at least one of the following indicators: fasting plasma glucose (FPG) ≥5.1 mmol/L, glucose level at 1-hour postprandial glucose (1 h PG) ≥10.0 mmol/L and (or) at 2 hours postprandial glucose after OGTT (2 h PG) ≥8.5 mmol/L]. Subsequent to this, her blood glucose had been satisfactorily controlled with diet and exercise alone.

Data in parentheses are ranges of normal values. PF, pregnancy-associated fulminant type 1 diabetes; GDM, gestational diabetes mellitus; OGTT, oral glucose tolerance test; HbA1c, glycated hemoglobin.

The initial laboratory test results (normal range) showed capillary blood glucose: 19 mmol/L (FPG 3.9–6.1 mmol/L); urine ketone bodies: 4+ (negative); pH: 7.1 (7.35–7.45); base excess (BE): −22 (−3 to 3); and urine amylase: 735.5 U/L (4–32 U/dL). A diagnosis of diabetic ketoacidosis (DKA) was considered. She received fluid replacement and glucose-lowering treatment [0.9% sodium chloride infusion (500 mL) + 10% potassium chloride (15 mL) + one-off human insulin (6–8 IU)], intravenous (IV) drip in the obstetrics department and was then transferred to the Endocrinology ward for ongoing care.

History of illness

The patient had a previous history of α-thalassemia [Southeast Asian (SEA) deletion] and denied a family history of diabetes. She previously had regular menstrual cycles, and the first day of her last menstrual period was June 30, 2020. Her childbearing history was G 1 P 0 ( Table 1 ).

Physical examination

General observations demonstrated body temperature: 36.7 ℃; heart rate: 103 beats per minute; respiratory rate: 20 breathes per minute; and blood pressure: 122/72 mmHg. Maternal pre-pregnancy body mass index (BMI) was 22.3 kg/m 2 . She was alert and cooperative during the physical examination. She had normal vesicular breath sounds bilaterally with no added sounds on auscultation. Her heart rhythm was regular, with normal findings on examination of the praecordium. Longitudinal oval bulges were observed on abdominal inspection. Visible peristaltic waves were not present. There was no peripheral edema. Her upper and lower limb muscle strength and muscle tone were normal.

Gynecological examination showed uterine height: 25 cm; abdominal circumference: 85 cm; cephalic presentation; left occiput anterior position; head not engaged; palpable irregular uterine contractions; and fetal heart sounds: regular (136 beats/minute). A colposcopy showed that the cervix was not dilated.

Laboratory examinations

The ancillary test results (normal range) of the patient were as follows—white blood cell count: 14×10 9 /L (3.5–9.5 ×10 9 /L); neutrophils (percentage): 80.9% (40–75%); serum glucose: 22.5 mmol/L (≤7.8 mmol/L); D3-hydroxybutyric acid: 8.1 mmol/L (0.03–0.3 mmol/L); lactic acid: 0.97 mmol/L (0.6–2.2 mmol/L); pH: 7.1 (7.35–7.45); and BE: 22 (−3 to 3). The routine urine tests showed urine glucose: 4+ (negative); and urine ketone bodies: 4+ (negative). There were no obvious abnormalities on routine stool tests. The test results for influenza A and B antibodies were negative, as was a nucleic acid test for severe acute respiratory syndrome coronavirus.

The biochemical results (normal range) of the patient were as follows—blood sodium: 131 mmol/L (137–147 mmol/L); and normal liver/kidney function. The pancreatic enzyme results (normal range) of the patient were as follows—blood amylase: 346 U/L (35–135 U/L); pancreatic amylase: 331 U/L (30–220 U/L); lipase: 320 U/L (150–200 U/L); islet function: C-peptide (0') [CP (0')], 0.017 nmol/L (0.37–1.47 nmol/L); and C-peptide (120') [CP (120')], 0.09 nmol/L (0.37–1.47 nmol/L). The glycated hemoglobin (HbA1c%) was 6.1% (4–6%), and the islet cell antibodies, antibodies to glutamate decarboxylase, and insulin autoantibodies were negative ( Table 3 ).

PF, pregnancy-associated fulminant type 1 diabetes; GDM, gestational diabetes mellitus; WBC, white blood cell count; NE%, neutrophils (percentage); FCP, fasting C-peptide; PCP, 2-hour postprandial C-peptide; PG, plasma glucose; HbA1c, glycated hemoglobin; SCr, serum creatinine; CK, creatine kinase; CT, computed tomography.

Imaging examinations

Computed tomography (CT) of the upper abdomen revealed possible cholestasis of the gallbladder, but no obvious abnormalities were observed in the liver, pancreas, or spleen. Abdominal color ultrasound revealed thickened and unevenly distributed echoes in the liver parenchyma, but no sign of pancreatitis was observed. An electrocardiogram showed sinus tachycardia.

Final diagnoses

The patient’s diagnoses were as follows: (I) PF; (II) DKA; (III) GDM.

DKA treatment was started immediately after the identification of DKA, and included active fluid replacement [0.9% sodium chloride infusion (500 mL) + 10% potassium chloride (15 mL) + one-off human insulin (6–8 IU)], alternating with 5% glucose + 0.9% sodium chloride infusion (500 mL) + 10% potassium chloride (15 mL) + one-off human insulin (8–12 IU), IV insulin pump [human insulin (50 IU) + 0.9% sodium chloride (50 mL), infused at a rate of 2–5 mL/h], once every hour blood glucose monitoring, electrocardiogram monitoring, and fetal heart rate monitoring.

After DKA was corrected, a subcutaneous insulin pump was used (Medtronic, MMT-712EWS, Minneapolis, USA) with a total baseline dose of insulin aspart injection 26 IU/d (0:00–3:00 0.8 IU/h, 03:00–7:00 1.4 IU/h, 07:00–12:00 1.1 IU/h, 12:00–17:00 1.0 IU/h, 17:00–22:00 1.1 IU/d, 22:00–24:00 0.9 IU/h) and bolus dose before meals of 10–14 IU to maintain a stable blood glucose fluctuation range as follows: fasting: 4.5–5.7 mmol/L; 2-hour postprandial: 6–9 mmol/L.

In addition, a multidisciplinary team of experts from the nutrition, obstetrics, and psychology departments was established. Nutritious meals were provided after the correction of ketoacidosis, The nutritious meals were: 1,800 kcal of total calories, 250 g of carbohydrates, 80 g of proteins, 53 g of fats, and the proportion of breakfast, lunch and dinner is 1/5, 2/5, and 2/5, respectively. And the fetal condition was assessed by the obstetricians. The mother was diagnosed with mild depression by the psychology department, and psychological counseling was offered.

Outcome and follow-up

After active treatment, the patient’s mental status improved remarkably. Her nausea and vomiting resolved, and her appetite improved. Her blood glucose after DKA correction was well controlled (fasting: 4.5–5.7 mmol/L; 2-hour postprandial: 6–9 mmol/L). Fetal heart rate monitoring revealed no obvious abnormality.

Two months subsequent to her presentation with DKA (at 37 weeks of gestation), the mother delivered a healthy baby girl by elective cesarean section. Over the subsequent 12 months, she maintained stable glucose control using an insulin pump (fasting blood glucose 4.5–7 mmol/L; 2-hour postprandial glucose 6–11 mmol/L). Her most recent HbA1c was recorded to be 7.6%. She has not had recurrence of episodes of DKA.

Fulminant type 1 diabetes mellitus (FT1DM) is a new subtype of type 1 diabetes mellitus (T1DM) that was first proposed by Imagawa and colleagues in 2000 ( 3 ). FT1DM diagnosis was proposed by the Japan Diabetes Association in 2016 Standard ( 4 ). It is more common in Asian populations, and is especially common in Japan, South Korea, and China. FP is defined as FT1DM that occurs during pregnancy or within 2 weeks of delivery. FP is the most common type of FT1DM ( 5 ) and typically occurs in the third trimester. However, few studies have examined the possible correlation between GDM and PF.

The current report summarizes the clinical features of a woman diagnosed with PF. She had been diagnosed with GDM in the second trimester, and then experienced an acute onset of hyperglycemia and ketoacidosis in the third trimester. Her blood glucose was ≥16.0 mmol/L, but her HbA1c was not high (<8.7%). Her fasting and postprandial serum C-peptide levels were almost undetectable. There were no abnormal findings on the pancreatic ultrasound or CT (to determine the presence of pancreatitis, CT was performed with the patient’s informed consent). These findings represented the typical clinical and laboratory features for PF and she met the diagnostic criteria for PF.

Both the 2021 American Diabetes Association standards ( 6 ) and the 2019 World Health Organization guidelines ( 7 ) mention hyperglycemia during pregnancy. These descriptions include GDM, overt diabetes diagnosed in pregnancy, and pre-conceptional diabetes, but do not include PF. This suggests that the pathogenesis and clinical features of PF are completely different from any other type of hyperglycemia during pregnancy.

Both GDM and overt diabetes diagnosed in pregnancy occur due to the increased insulin resistance caused by insulin-antagonizing hormones secreted by adipocytes and placental tissues after pregnancy, the low-level inflammatory responses, and the reduced sensitivity to insulin of pregnant women ( 8 ). They can be regarded as compensatory and decompensated manifestations that help maintain the normal physiological glucose metabolism ( 8 ). After the delivery of the fetus and placenta, insulin resistance is alleviated and blood sugar improves or even returns to normal; thus, insulin can be used in much lower dosages or stopped. However, for person with PF, postpartum blood glucose is difficult to control due to the complete loss of islet function, and lifelong insulin use is consequently required.

The common etiologies of PF include viral infections, human leukocyte antigen ( HLA ) gene susceptibility and autoimmunity. Various viral infections have been described: these include coxsackievirus ( 9 ), herpes virus, and influenza virus. These viruses can directly and rapidly destroy β cells and also initiate autoimmunity by exposing the antigens. In one Chinese report, however, few patients were shown to have a viral trigger ( 10 ). Consistent with that observation, although the current case initially had a fever and symptoms of an upper respiratory tract infection, viral testing was negative.

The presence of specific HLA class II genes, notably HLA DR and DQ genes is closely related to the occurrence of PF ( 11 ). Next, with the patient’s informed consent, we intend to improve the testing of the woman’s related genes.

Autoimmunity also plays a key role in the pathogenesis of PF ( 12 ). While most individuals with PF have negative antibodies, a small proportion may have islet autoantibodies. Given the low rate of seropositivity, this is not regarded as a diagnostic criterion for PF. However, the autoantibodies in the current case were negative, which is consistent with most individuals with PF.

The pancreatic histopathology of patients with FT1DM is characterized by the rapid destruction of both α and β cells, which differs from classic T1DM, in which only β cells are destroyed at a relatively low rate of destruction. In addition, the elevated pancreatic enzymes in the current patient were consistent with the reported elevated exocrine pancreatic indicators in patients with PF ( 10 ). There were, however, no signs of pancreatitis on imaging. This combination of results might be explained by lymphocyte infiltration of the exocrine pancreas without pancreatic edema ( 6 ).

The clinical manifestations and metabolic disorders of patients with PF are more severe than those of patients with FT1DM who are not pregnant. Clinically, it is manifested as a rapid onset (typically within 1 week). PF also has the following clinical features: (I) influenza-like symptoms or gastrointestinal symptoms before onset; (II) a high blood glucose level and a nearly normal HbA1c level; (III) elevated exocrine enzymes of the pancreas; (IV) no signs of pancreatitis on imaging; and (V) an onset during pregnancy or within 2 weeks of delivery. In addition, unlike pre-GDM complicated by gestational DKA, PF has a much higher fetal mortality rate. In one report, stillbirth occurred in eight (89%) of nine cases of PF ( 13 ). In contrast, the fetal mortality rate of pre-pregnancy T1DM complicated by DKA is only about 9–36% ( 14 ).

Emaciation is a common characteristic of patients with classic T1DM and non-pregnancy-associated FT1DM. Conversely, the body weight of patients with PF is typically quite different from that of patients with non-pregnancy-associated FT1DM. Based on the body weight of several other patients with PF admitted to our department and the cases described by Peking Union Medical College Hospital, we noted that PF is more likely to occur in those who are overweight or obese (personal unpublished observation). In one of our previous studies ( 15 ), the preconception BMI of patients with PF did not differ from that of those with GDM. However, due to the small sample sizes, the reliability of these conclusions needs further verification.

According to the literature, most pregnant women deny a history of GDM before the occurrence of PF ( 11 ). In contrast, our patient had GDM during pregnancy. Thus, the question arises as to whether GDM is directly associated with the development of PF. It has been reported that patients with GDM are at risk of developing T1DM diabetes and a variety of autoimmune diseases ( 16 ). Islet autoimmunity may be involved in the development of PF, but the specific mechanism needs to be further studied.

In the current case, blood glucose fluctuations were revealed by close monitoring, which was important in identifying the cut-off time point at which GDM turned into PF. If blood glucose suddenly becomes difficult to control and deteriorates rapidly in a woman with GDM whose lifestyle interventions and insulin doses remain unchanged, the risk of PF should be considered. In the current case, the patient received regular blood glucose monitoring after the diagnosis of GDM. Before PF occurred, her blood glucose was basically well controlled. However, she later suffered from a sudden blood sugar increase and sought medical treatment promptly. Her fetus ultimately survived.

Early detection is especially important for PF. GDM turned into PF in the current case, which indicates that blood glucose should be monitored regularly in women with GDM until after delivery. According to Liu et al. ( 17 ), a PG/HbA1c ratio with a threshold of ≥3.3 can be used as a cut-off point in predicting PF from DKA in China. An elevated PG/HbA1c ratio at the time of diagnosis is predictive of more severe insulin secretion dysfunction and a poor prognosis. In our case, a sudden increase of blood glucose for unknown reasons and a PG/HbA1c ratio of ≥3.3 are highly suggestive of the possibility of PF, and further tests for blood glucose, HbA1c, D3-hydroxybutyric acid, C peptide, and islet antibodies should be performed.

Treatment for DKA should be commenced as early as possible, even before the diagnosis of PF is confirmed. DKA therapies include aggressive fluid replacement, the early insulin administration (via an insulin pump), the maintenance of the water-electrolyte balance, infection control, and fetal heart rate monitoring. In addition, due to the high basal cardiopulmonary stress in pregnant women, special attention should be paid to rehydration rate. After the DKA is corrected, an insulin pump or an intensive insulin regimen may be applied to maintain target blood glucose levels. Hosokawa et al. ( 18 ) recently reported that induced pluripotent stem cells may be a new therapeutic strategy for PF.

In summary, PF is characterized by poor maternal and infant outcomes and a high stillbirth rate. However, early recognition and treatment of FT1DM is crucial in preventing unfavourable pregnancy outcomes ( 19 ). The current patient had been diagnosed with GDM in the second trimester 5 weeks prior to presenting with influenza-like symptoms. She then experienced an acute onset of hyperglycemia, with ketoacidosis and reduced pancreatic islet cell function, but her HbA1c was not elevated. Together, these findings represent the typical clinical and laboratory features of PF. Moreover, patients with GDM are at risk of developing T1DM diabetes and a variety of autoimmune diseases. Islet autoimmunity may be involved in the development of PF, but the specific mechanism needs to be elucidated.

Supplementary

Acknowledgments.

We thank Dr. Andrew S. Day (University of Otago Christchurch, New Zealand) and Dr. Maria Ruth B. Pineda-Cortel (Research Center for the Natural and Applied Sciences, University of Santo Tomas, Philippines) for their critical comments and valuable advice on this study.

Funding: This study was granted by the Hainan Provincial Natural Science Foundation-Youth Cultivation Fund ( No. 822QN454 to Q.J.), National Natural Science Fund Cultivating 530 Project of Hainan General Hospital - Youth Cultivation Fund Project ( No. 2021QNXM09 to Q.J.), Hainan Health Science and Education Project ( No. 21A200219 to Q.J.) and project supported by Hainan Province Clinical Medical Center (to Q.J.).

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. All the procedures performed in this study were conducted in accordance with the ethical standards of Hainan General Hospital and the Declaration of Helsinki (as revised in 2013). Written informed consent was obtained from the patient for the publication of this case report and the accompanying images. A copy of the written consent is available for review by the editorial office of this journal.

Reporting Checklist: The authors have completed the CARE reporting checklist. Available at https://acr.amegroups.com/article/view/10.21037/acr-24-52/rc

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://acr.amegroups.com/article/view/10.21037/acr-24-52/coif ). Q.J. reports that this study was granted by the Hainan Provincial Natural Science Foundation-Youth Cultivation Fund (No. 822QN454 to Q.J.), National Natural Science Fund Cultivating 530 Project of Hainan General Hospital - Youth Cultivation Fund Project (No. 2021QNXM09 to Q.J.), Hainan Health Science and Education Project (No. 21A200219 to Q.J.) and project supported by Hainan Province Clinical Medical Center (to Q.J.). The other authors have no conflicts of interest to declare.

• AME Case Rep. 2024; 8: 83.

Peer Review File

Available at https://acr.amegroups.com/article/view/10.21037/acr-24-52/prf

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

• View all journals
• Explore content
• About the journal
• Publish with us
• Sign up for alerts
• Open access
• Published: 05 August 2024

Functional genetic variants and susceptibility and prediction of gestational diabetes mellitus

• Gongchen Huang 1   na1 ,
• Yan Sun 1   na1 ,
• Ruiqi Li 1 ,
• Qiulian Liang 1 &
• Xiangyuan Yu 1  

Scientific Reports volume  14 , Article number:  18123 ( 2024 ) Cite this article

182 Accesses

2 Altmetric

Metrics details

• Computational biology and bioinformatics
• Endocrinology
• Risk factors

The aetiological mechanism of gestational diabetes mellitus (GDM) has still not been fully understood. The aim of this study was to explore the associations between functional genetic variants screened from a genome-wide association study (GWAS) and GDM risk among 554 GDM patients and 641 healthy controls in China. Functional analysis of single nucleotide polymorphisms (SNPs) positively associated with GDM was further performed. Univariate regression and multivariate logistic regression analyses were used to screen clinical risk factors, and a predictive nomogram model was established. After adjusting for age and prepregnancy BMI, rs9283638 was significantly associated with GDM susceptibility ( P  < 0.05). Moreover, an obvious interaction between rs9283638 and clinical variables was detected ( P interaction  < 0.05). Functional analysis confirmed that rs9283638 can regulate not only target gene transcription factor binding, but it also regulates the mRNA levels of SAMD7 ( P  < 0.05). The nomogram model constructed with the factors of age, FPG, 1hPG, 2hPG, HbA1c, TG and rs9283638 revealed an area under the ROC curve of 0.920 (95% CI 0.902–0.939). Decision curve analysis (DCA) suggested that the model had greater net clinical benefit. Conclusively, genetic variants can alter women's susceptibility to GDM by affecting the transcription of target genes. The predictive nomogram model constructed based on genetic and clinical variables can effectively distinguish individuals with different GDM risk factors.

Similar content being viewed by others

Fine-tuning of Genome-Wide Polygenic Risk Scores and Prediction of Gestational Diabetes in South Asian Women

Genetic polymorphisms associated with adverse pregnancy outcomes in nulliparas

Distinct and shared genetic architectures of gestational diabetes mellitus and type 2 diabetes

Introduction.

Gestational diabetes mellitus (GDM) is one of the most common complications of pregnancy and is defined as the onset or the first discovery of glucose intolerance during pregnancy 1 . Worldwide, it affects approximately 2–20% of all pregnant women, but, in China, approximately 14.8% of pregnant women are affected 2 . Studies have confirmed that GDM can ultimately lead to adverse outcomes and long-term adverse effects on mothers and their offspring, such as foetal macrosomia, preeclampsia (PE), preterm birth, spontaneous abortion, respiratory distress syndrome, small for gestational age (SGA), large for gestational age (LGA), polycythemia, future obesity and type 2 diabetes mellitus (T2DM) 3 , 4 , 5 . GDM poses a serious threat to the health and quality of life of patients and their offspring 6 , 7 .

Similar to the pathogenesis of T2DM, GDM can be caused by insulin resistance and insufficient insulin secretion compensation 8 , 9 . Currently, the known causes of GDM include older age at pregnancy, prepregnancy overweight or obesity, excessive weight gain during pregnancy, family history of T2DM, and past history of GDM 8 , 10 . Epidemiological evidence shows that a family history of diabetes is an independent risk factor for GDM, and the closer individuals are to diabetes patients, the greater the risk of GDM is during pregnancy 11 , 12 . In addition, the incidence rate of GDM in Asian women during pregnancy is approximately 3–7 times greater than that in Caucasians 13 , 14 . This indicates that genetic factors are also involved in the pathogenesis of GDM. Therefore, identifying individual genetic risk factors for GDM is highly important for disease prevention and control.

Single nucleotide polymorphisms (SNPs) are the main variant form of the human genome and determine the core information of genetic susceptibility to disease. It has been widely applied in disease risk prediction and patient prognosis assessment 15 . SNPs located in different functional regions of genes may affect promoter and enhancer activity, alternative splicing, messenger RNA (mRNA) conformation and posttranscription level, protein function and structure and even cause changes in the biological traits of an individual 16 , 17 , 18 . Genome-wide association studies (GWASs) are considered an effective approach for detecting SNPs associated with complex disease phenotypes or traits across the entire genome, providing more genetic clues for the pathogenesis of human diseases. At present, a certain number of GDM susceptibility SNPs have been successfully identified 14 , 19 , 20 , 21 .

Disease prediction models can predict individuals’ probability of developing disease or experiencing certain conditions in the future 22 . Previous studies have extensively constructed GDM nomogram prediction models based on conventional clinical parameters (age, BMI, blood pressure, FPG, HbA1c, glucose and lipid levels, etc.) for early disease detection, prevention and treatment 23 , 24 , 25 . During the construction process of the nomogram model, the factors included in the model were scored based on the size of the logistic regression coefficients and then presented in the form of scaled line segments. The probability of corresponding outcome events occurring was determined by calculating the total score. This type of model can effectively predict the risk of individual GDM occurrence and help doctors make decisions through the use of visualized clinical predictions that provide personalized and highly accurate risk estimates 26 . However, there is a lack of risk factors characterized by genetic susceptibility as a predictive indicator. It is of great clinical significance to establish a practical risk prediction model for complex human diseases, including GDM prevention and control, by combining genetic variants and environmental risk factors.

Here, a large sample size case‒control study was conducted to validate the effects of SNPs screened by GWAS on the incidence of GDM. Subsequently, a nomogram model with GDM-positively associated SNPs and clinical indicators was constructed for early GDM prediction.

Study population

All subjects who met the following inclusion criteria were enrolled in the Affiliated Hospital of Guilin Medical University from September 2014 to April 2016: singleton pregnancy, no family relationship and no metabolic disease, such as type 1/2 diabetes mellitus. A routine 75-g oral glucose tolerance test (OGTT) was performed between 24 and 28 weeks of gestation. According to the standards of the International Association of Diabetes and Pregnancy Research Groups (IADPSG), women can be diagnosed with GDM if their fasting plasma glucose (FPG) is ≥ 5.1 mmol/L, 1-h plasma glucose (1hPG) is ≥ 10.0 mm/L or 2-h plasma glucose (2hPG) is ≥ 8.5 mmol/L.

At the initial discovery stage, 96 GDM patients and age and pre-BMI matched 96 healthy pregnant women from the same period were recruited to conduct a genome-wide association study (GWAS) for screening GDM associated SNPs (GDM-SNPs) by using infinium Asian Screening Array (ASA, illumina) BeadChip. During the validation phase, singleton pregnant women of the same conditions were recruited, and candidate SNPs were genotyped in 554 GDM patients and 641 healthy pregnancies. In addition, biological samples from the other 42 normal pregnant women, including peripheral whole blood and placental tissues, were collected to detect the biological functions of the positively associated variants.

The Ethics Committee of Guilin Medical University approved this research (Number: GLMC20131205), and the study was conducted in accordance with the Declaration of Helsinki. All included subjects signed informed consent forms prior to study procedures. The details of this study design are depicted in the flowchart in Fig.  1 .

The flowchart of the study design. TFBS indicated transcription factor-binding sites, e QTL indicated expression quantitative trait locus.

Infinium Asian screening array (ASA)

All DNA samples were extracted using DNA-extraction kits (Tiangen Biotech). Genotyping module of Genomestudio v2.1 (illumina) was used to call the genotype, and to obtain high-quality data for GWAS. We pruned the data set of discovery stage with the following criteria: (1) SNP call rate > 95%, and a threshold for Hardy–Weinberg equilibrium (HWE) of 0.0001, minimum allele frequencies (MAF) < 1% and sex chromosome SNP sites; (2) Sample call rates > 95%; In addition, to exclude closely related individuals, we calculated genome-wide identity by descent (IBD) for each pair of samples and removed samples with PI-HAT > 0.25. We took group analysis quality control from 1000Geomics Northern and Western European Ancestry (CEU), Japanese in Tokyo (JPT) and Han Chinese in Bejing (CHB) database to Confirm whether the sample grouping meets expectations and detect outlier samples.

Clinical and biochemical characteristics

Clinical and biological characteristics, including age, prepregnancy weight (kg), height (m), systolic blood pressure (SBP), diastolic blood pressure (DBP), fasting plasma glucose (FPG), 1-h plasma glucose (1hPG), 2-h plasma glucose (2hPG), triglyceride (TG), total cholesterol (TC), haemoglobin A1c (HbA1c), low-density lipoprotein cholesterol (LDL-c) and high-density lipoprotein cholesterol (HDL-c), etc., were obtained from a unified questionnaire and patient medical records.

Candidate SNP selection and genotyping

Preliminary selection of candidate SNPs was based on the strength of the association effect on GDM ( P  < 1.0 × 10 −3 ) according to the Infinium Asian Screening Array (ASA) BeadChip. The SNP function prediction (FuncPred) tool ( https://manticore.niehs.nih.gov/snpinfo/snpfunc.html ) was subsequently used for screening potential functional variants in the Chinese Han population in Beijing (CHB) with minimum allele frequencies (MAF) greater than 0.05.

The candidate variants were genotyped via the Sequenom MassARRAY platform. The multiplex PCR master mix was composed of 1.0 μl of template DNA (20 ~ 100 ng/μl), 1.850 μl of ddH 2 O, 0.625 μl of 1.25 × PCR buffer (15 mmol/L MgCl 2 ), 0.325 μl of 25 mmol/L MgCl 2 , 0.1 μl of 25 mmol/L dNTPs, 1 μl of 0.5 μmol/L primer mix, and 0.1 μl of 5 U/μl HotStar Taq polymerase. The reaction was conducted at 94 °C for 15 min, followed by 45 cycles at 94 °C for 20 s, 56 °C for 30 s and 72 °C for 1 min, with a final incubation at 72 °C for 3 min. The primers used are listed in Supplemental Table S1 .

Functional analysis of positively associated SNPs

For positively associated SNPs located in TFBSs, the Alibaba 2.1 tool ( http://gene-regulation.com/pub/programs/alibaba2/index.html ) was used to explore potential biological functions. In addition, to determine whether the SNP was an expression quantitative trait locus (eQTL), we also carried out validated experiments in our study.

According to the Aidlab DNA Extraction Kit (Aidlab Biotechnology Co., Ltd., China), genomic DNA was extracted from peripheral blood of 42 healthy pregnant women, and then the optical density values of each sample at 260 nm and 280 nm were measured using a NanoDrop spectrophotometer (Thermo Scientific, Waltham, MA, USA) to determine the DNA concentration and purity. Next, the genotypes of the candidate SNPs were determined using Kompetitive Allele Specific Polymerase Chain Reaction (KASP) 27 in a StepOnePlus™ real-time PCR system (Thermo Fisher Scientific, Life Technologies Holding Pte Ltd., China). The 10-µl reaction system contained 5 µl of Flu Arms 2 × PCR mix, 0.5 µl of three specific primers (F1: 0.1 µl, F2: 0.1 µl, and R: 0.3 µl), 0.5 µl (25–150 ng) of DNA and 4 µl of ddH 2 O. The cycling conditions were as follows: hot-start Tap activation at 95 °C for 3 min, followed by 10 touchdown cycles at 95 °C for 15 s and at 61–55 °C for 60 s (61 °C decreasing to 0.6 °C per cycle to achieve a final annealing and elongation temperature of 55 °C), followed by 30 amplification cycles at 95 °C for 15 s, 55 °C for 60 s and postread at 30 °C for 60 s. The primer sequences are shown in Supplemental Table S1 .

Total RNA was extracted from the placental tissues of 42 normal pregnant women using TRIzol reagent (Invitrogen, Carlsbad, CA, USA) according to the manufacturer’s instructions. The concentration and purity of the extracted RNA were tested using a Thermo Scientific Nanodrop-2000c microspectrophotometer. Total RNA (2 µg) was reverse transcribed into cDNA according to the instructions for the reverse transcription kit (HaiGene, Harbin, China). Finally, quantitative real time polymerase chain reaction (QRT-PCR) was performed using the GLPBIO SYBR Green qPCR Mix (2 ×) kit on the StepOne Plus TM real-time PCR system. The 10 µl RT‒qPCR system contained 1 µl of cDNA template, 5 µl of 2 × SYBR Green PCR Mastermix, 2 µl of forwards and reverse primer concentrations and 3.4 µl of DEPC ddH2O. The PCR mixtures were denatured at 95 °C for 10 min, followed by 40 cycles of 95 °C for 15 s and 65 °C for 60 s. The 2^(− ΔΔCt) method was used to quantify gene expression, with GAPDH serving as an internal control 28 . The primer sequences are shown in Supplemental Table S1 .

Data processing

In this study, the data were processed with IBM SPSS Statistics 28 for Windows (IBM Corp., Armonk, NY, USA) and R 4.3.1 software. Clinical and biochemical variables are shown as the mean ± SD or percentage and were analysed using independent sample t tests or chi square (χ 2 ) tests. Logistic regression analysis was adopted to evaluate the association between variants and GDM risk with the odds ratio (OR) and its corresponding 95% confidence interval (CI). One-way ANOVA was used to compare expression levels among the different genotypic samples. Additionally, univariate logistic regression and multivariate regression analysis by forwards stepwise selection with the Akaike information criterion (AIC) were employed to determine the clinical risk factors for GDM.

A predictive nomogram model composed of clinical risk factors and positive SNPs was eventually constructed using the R package “rms”. The area under the receiver operating characteristic curve (AUC) was used to evaluate the model’s performance. The calibration curve by internal validation with a bootstrap method with 1000 resamples was generated to assess the level of consistency between the predicted and observed values. The clinical utility and net benefit were estimated by decision curve analysis (DCA). Finally, a web-based interactive dynamic nomogram was established via the R package “DynNom”. A two-sided test was adopted, and P values < 0.05 were considered to indicate statistical significance.

Patient characteristics

The selected characteristics of the patients are shown in Table 1 . There were no significant differences in TC, HDL-c or LDL-c between the two groups ( P  > 0.05). However, the mean age, pre-BMI, SBP, DBP, FPG, 1hPG, 2hPG, HbA1c and TG levels in GDM patients were much greater than those in controls ( P  < 0.05).

Candidate SNPs Screening

According to the GWAS, a large amount of GDM associated SNPs were screened (Fig.  2 ). Based on the established variant screening strategy, 5 SNPs were ultimately selected, of which 4 SNPs (rs17099985, rs9283638, rs6798181, rs796749) were predicted to be located at transcription factor-binding sites (TFBS), and one SNP (rs1742473) was predicted to be located at a splicing site (SS) (Supplemental Table S2 ).

Manhattan plot demonstrating the -log 10 P value for the SNPs in the gestational diabetes mellitus genome-wide association study at the discovery stage. The red line represents the genome-wide significance threshold ( P  = 5 × 10 –4 ).

SAMD7 rs9283638 C > T and GDM risk

The frequency distribution of the three genotypes of the 5 variants followed the Hardy Weinberg equilibrium (HWE) law ( P HWE  > 0.05) in the control group. Significant differences in the genotype distribution of rs9283638 were observed between GDM patients and controls (χ 2  = 9.06, P  = 0.011) (Table 2 ).

Unconditional logistic regression analysis revealed that rs9283638 was significantly associated with GDM risk. Compared with the CC genotype, the TT genotype increased GDM risk by 54% (TT vs. CC: crude OR = 1.54, 95% CI 1.05–2.26, P  = 0.029). However, after adjusting for age and BMI, the positive associations previously described no longer existed. However, we did find a significant correlation with GDM risk in the recessive model (TT vs. CC/CT: adjusted OR = 1.57, 95% CI 1.06–2.32, P  = 0.025) as shown in Table 2 .

According to the stratified analysis, compared with individuals with the CT/TT genotype, individuals with the rs9283638 TT genotype had a greater risk of GDM in the age > 30.09 years (adjusted OR = 2.80, 95% CI 1.45–5.41, P  = 0.002), DBP ≤ 69.53 mmHg (adjusted OR = 1.75, 95% CI 1.06–2.91, P  = 0.035) and TG subgroup ≤ 2.54 mmol/L (adjusted OR = 2.20, 95% CI 1.29–3.75, P  = 0.004) subgroups. A significant interaction effect of rs9283638 with age ( P interaction  = 0.017) was observed under the recessive model (Table 3 ).

However, there was no significant association between GDM risk and other variants (rs17099985, rs1742473, rs6798181 and rs796749) in the present study ( P  > 0.05) (Table 2 ).

According to bioinformatic analysis, the rs9283638 polymorphism located at a TFBS can change the types of transcription factors binding to the promoter region under different alleles, which may affect gene transcription (Fig.  3 a and b). Furthermore, expression quantitative trait locus (eQTL) analysis of placental tissues revealed that rs9283638 C > T could significantly regulate the mRNA levels of SAMD7 ( P  = 0.017). As shown in Fig.  4 a and b.

The prediction for the transcription factor binding site (TFBS) using AliBaba 2.1. ( a ) The transcription factors of rs9283638 C allele in 97–106 bp. ( b ) The transcription factors of rs9283638 T allele in 101–110 bp.

Schematic diagram of the genotyping of rs9283638 and the expression quantitative trait locus (eQTL) analysis of SAMD7 . ( a ) rs9283638 genotyping plot by Kompetitive Allele Specific Polymerase Chain Reaction (KASP-PCR). ( b ) Analysis of SAMD7 differential expression level under different genotypes. * P  < 0.05.

Variable screening and nomogram establishment

Through the univariate and multivariate logistic regression analysis, 6 clinical factors were considered risk factors for GDM: age, FPG, 1hPG, 2hPG, HbA1c and TG. Considered the rs9283638 was associated with an increased GDM risk, the predictive nomogram model was eventually constructed with the positive SNP (rs9283638 recessive model) and significant clinical factors (Supplemental Table S3 ). The patients were randomly assigned to the training and validation cohorts at a 7:3 ratio; thus, there were 805 patients in the training set and 344 patients in the validation set. The GDM risk can be predicted based on the sum of assigned points for each risk factor’s level. Higher total scores indicate that GDM events are more likely to occur (Fig.  5 a). In addition, to facilitate the use of nomograms for clinicians, we constructed a dynamic nomogram online to visualize the predictive results for GDM. The probability of GDM occurrence can be easily determined by inputting personal values of risk indicators into the web-based application (Fig.  5 b–d).

The static and dynamic nomogram for predicting individual GDM risk. ( a ) A static nomogram for GDM risk prediction. Each risk indicators corresponding to level can be given different scores, and the total scores obtained by adding these scores from all variables can use to predict the GDM risk. ( b ) The risk variables input panel of the online dynamic nomogram ( https://qiulianl.shinyapps.io/GDM Predict/). ( c ) Person GDM predictive results’ graph visualization. ( d ) Showing individual GDM predictive probability and its corresponding 95% confidence intervals.

Validation of the nomogram

The predictive nomogram had an area under the curve (AUC) of 0.920 (95% CI 0.902–0.939, P < 0.001) in the training cohort and 0.834 (95% CI 0.778–0.890, P < 0.001) in the validation cohort, indicating the good discriminating ability of the model (Fig.  6 a and b). The nomogram calibration plot was roughly close to the ideal line, revealing good agreement between the predicted and observed values (Fig.  6 c and d). As shown in the DCA analysis, the model curves for most of the risk threshold probabilities were above the two lines (“treat all” or “treat none”), suggesting that the nomogram model had greater net clinical benefit (Fig.  6 e and f).

Validation of the nomogram. ( a ) Receiver operating characteristic (ROC) curves in training set with an area under the curve (AUC) of 0.920, cutoff value of 0.428, specificity of 80.6%, sensitivity of 89.9%. ( b ) ROC curve in validation set with a AUC of 0.834. ( c ) Calibration plot in training set conducted by a bootstrap method with 1000 resamples. ( d ) Calibration plot in validation set conducted by a bootstrap method with 1000 resamples. ( e ) A decision curve analysis (DCA) in training set. ( f ) DCA curve in validation set.

GDM is considered to pose a serious threat to the short-term and long-term health of mothers and their offspring 29 . Identifying high-risk populations for GDM is particularly useful for early intervention and prevention of disease progression 30 , 31 . Although significant progress has been made in identifying the mechanism of GDM susceptibility, they have not been fully understood. It is now recognized that GDM is a multifactorial disease and exhibits a clear genetic tendency. That is, genetic variants may alter individuals’ genetic susceptibility to GDM, even under the same environmental conditions 32 , 33 . Here, while clarifying the association between genomic SNPs and GDM, we further attempted to construct a nomogram predictive model to predict the risk of GDM in pregnant women. It is believed to be of great social significance for the prevention and control of GDM.

In the present study, we observed a significant association between rs9283638 and the risk of GDM in the population of Guilin, China. This finding is consistent with the findings of numerous previous studies 8 , 10 , 13 , 14 , 19 , 20 , 21 . Meaning, there are obvious genetic characteristics involved in the pathogenesis of GDM, and a series of associated genes and SNPs are involved in disease occurrence at the genetic level. Furthermore, these findings suggest that the studied SNPs exert different effects on different levels of some clinical indicators, and significant interactions have been observed between rs9283638 and age. Similarly, Kwak SH et al. reported that the CDKAL1 SNP rs7754840 was significantly associated with insulin expression, inhibition of insulin secretion in pancreatic β-cells and birth weight of a baby 20 , while Polina V et al. suggested that genetic variants of MTNR1B (rs10830963 and rs1387153) can reduce early insulin secretion through parallel signalling pathways in pancreatic β-cells, thereby regulating glucose metabolism 34 . These findings indicated that genetic variants may modify the genetic background of an individual or, combine with environmental features or clinical traits, may affect individuals’ susceptibility to complex human diseases. Personal differences associated with GDM may be affected by SNPs or SNP-environmental factor interactions.

It is speculated that the construction of a predictive model can serve as an important bridge between clinical epidemiology or molecular epidemiology and clinical practice, and it could become an effective means of identifying high-risk populations, guiding clinical diagnosis and treatment, promoting the prevention and control of complex diseases, and improving patient clinical prognosis 35 , 36 . The nomogram prediction model integrates multiple disease-related indicators and draws scaled line segments on the same plane in a certain proportion to express the relationships between selected variables. The model quantifies the occurrence rate and high-risk factors for GDM risk, intuitively representing the probability of patients developing GDM, and provides personalized risk assessment for subjects 26 , 37 , 38 .

Given the independent hazard effect of environmental and genetic factors on the pathogenesis of GDM, this study incorporated validated SNPs significantly associated with GDM and clinical indicators (age, FPG, 1hPG, 2hPG, HbA1c and TG) to construct a GDM risk prediction nomogram model. This model demonstrated a good ability to distinguish individual GDM risks, with an area under the ROC curve of 0.920. The genetic-clinical model can help clarify the probability of women developing GDM during pregnancy, thereby identifying high-risk individuals and leading to personalized prevention. It is extremely important to accurately prevent GDM in individuals during early pregnancy.

The potential gene expression regulatory region variants not only serve as genetic markers but also may affect individual physiological and pathological manifestations by regulating the expression of genes or interacting with environmental exposure factors, making them suitable for revealing the susceptibility mechanisms of complex traits and diseases. For example, the functional variant rs10830963 was associated with GDM risk by regulating the expression levels of the MTNR1B gene, fasting blood glucose, fasting insulin, and homeostasis model assessment for insulin resistance 39 . In the present study, we found that rs9283638 is significantly associated with the risk of GDM and has significant interactions with age. Furthermore, we found that the above association findings seem to be biologically plausible. Functional analysis suggested that rs9283638 C > T can affect transcription factor binding to specific binding motifs and alter the transcription of the SAMD7 gene. In addition, mRNA level detection in placental tissues revealed that rs9283638 can be an eQTL that regulates the expression levels of SAMD7 mRNA. This finding provides new insight into the biological genetic mechanism of susceptibility to GDM.

However, this study has several limitations. First, as a hospital-based case‒control study, there will inevitably be bias in subject selection and data collection. Second, potential confounding factors of GDM, such as smoking status, poor obstetrics, malnutrition, and socioeconomic factors, were not assessed. These factors are likely to interfere with the true effects of the association between the studied variants and GDM risk. Third, the very low frequency of genotypes tested in the studied variants may still limit the statistical performance, especially in subgroup analysis. Finally, limited in-depth biological functional analysis of significantly associated variants was conducted in this study.

In the present study, we confirmed that rs9283638 is significantly related to the risk of GDM. The potential mechanism may involve independent genetic risk effects and genetic-environmental interactions affecting female individuals′ susceptibility to GDM. Based on key genetic SNPs and clinical parameters, a predictive nomogram model with good potential for the early identification and prevention of GDM has been successfully established.

Data availability

The datasets generated and/or analysed during the current study are available in the dryad repository, doi: https://doi.org/ https://doi.org/10.5061/dryad.fj6q5743m .

Goedegebure, E. A. R. et al. Pregnancy outcomes in women with gestational diabetes mellitus diagnosed according to the WHO-2013 and WHO-1999 diagnostic criteria: A multicentre retrospective cohort study. BMC Pregnancy Childbirth 18 , 152 (2018).

Article   PubMed   PubMed Central   Google Scholar  

Gao, C., Sun, X., Lu, L., Liu, F. & Yuan, J. Prevalence of gestational diabetes mellitus in mainland China: A systematic review and meta-analysis. J. Diabetes Investig. 10 , 154–162 (2019).

Article   CAS   PubMed   Google Scholar  

Coustan, D. R. Pregnancy outcomes in women with and without gestational diabetes mellitus according to the international association of the diabetes and pregnancy study groups criteria. Obstet. Gynecol. 121 , 377 (2013).

Article   PubMed   Google Scholar  

Farrar, D. et al. Hyperglycaemia and risk of adverse perinatal outcomes: Systematic review and meta-analysis. BMJ 354 , i4694 (2016).

Li, M. et al. Genetic factors and risk of type 2 diabetes among women with a history of gestational diabetes: Findings from two independent populations. BMJ Open Diabetes Res. Care 8 , e000850 (2020).

Xiang, A. H. Diabetes in pregnancy for mothers and offspring: reflection on 30 years of clinical and translational research: The 2022 Norbert Freinkel award lecture. Diabetes Care 46 , 482–489 (2023).

Zeng, J. et al. Association of maternal obesity and gestational diabetes mellitus with overweight/obesity and fatty liver risk in offspring. World J. Gastroenterol. 28 , 1681–1691 (2022).

Article   CAS   PubMed   PubMed Central   Google Scholar  

Plows, J. F., Stanley, J. L., Baker, P. N., Reynolds, C. M. & Vickers, M. H. The pathophysiology of gestational diabetes mellitus. Int. J. Mol. Sci. 19 , 3342 (2018).

You, H., Hu, J., Liu, Y., Luo, B. & Lei, A. Risk of type 2 diabetes mellitus after gestational diabetes mellitus: A systematic review & meta-analysis. Indian J. Med. Res. 154 , 62–77 (2021).

Chen, P. et al. Risk factors and management of gestational diabetes. Cell Biochem. Biophys. 71 , 689–694 (2015).

Zhou, Y., Xie, N., Zhang, L. & Chen, D. Impact of family history of diabetes on blood glucose, lipid levels and perinatal outcomes in pregnant women with gestational diabetes mellitus. Zhejiang Da Xue Xue Bao Yi Xue Ban 50 , 329–334 (2021).

PubMed   PubMed Central   Google Scholar  

Monod, C. et al. Prevalence of gestational diabetes mellitus in women with a family history of type 2 diabetes in first- and second-degree relatives. Acta Diabetol. 60 , 345–351 (2023).

Benny, P. et al. Genetic risk factors associated with gestational diabetes in a multi-ethnic population. PLoS One 16 , e0261137 (2021).

Wei, W. et al. Gestational diabetes mellitus: The genetic susceptibility behind the disease. Horm. Metab. Res. 53 , 489–498 (2021).

Acosta-España, J. D. & Voigt, K. Mini review: Risk assessment, clinical manifestation, prediction, and prognosis of mucormycosis: Implications for pathogen- and human-derived biomarkers. Front. Microbiol. 13 , 895989 (2022).

Li, G. Expression quantitative trait loci analysis in multiple tissues. Methods Mol. Biol. 2082 , 231–237 (2020).

McRae, A. F. et al. Identification of 55,000 replicated DNA methylation QTL. Sci. Rep. 8 , 17605 (2018).

Article   ADS   PubMed   PubMed Central   Google Scholar  

Prasad, R. B., Kristensen, K., Katsarou, A. & Shaat, N. Association of single nucleotide polymorphisms with insulin secretion, insulin sensitivity, and diabetes in women with a history of gestational diabetes mellitus. BMC Med. Genom. 14 , 274 (2021).

Article   CAS   Google Scholar  

Dalfrà, M. G., Burlina, S., Del Vescovo, G. G. & Lapolla, A. Genetics and epigenetics: New insight on gestational diabetes mellitus. Front. Endocrinol. (Lausanne) 11 , 602477 (2020).

Kwak, S. H. et al. A genome-wide association study of gestational diabetes mellitus in Korean women. Diabetes 61 , 531–541 (2012).

Wu, N. N. et al. A genome-wide association study of gestational diabetes mellitus in Chinese women. J. Matern. Fetal Neonatal Med. 34 , 1557–1564 (2021).

Article   ADS   CAS   PubMed   Google Scholar  

Sammani, A., Baas, A. F., Asselbergs, F. W. & Te Riele, A. Diagnosis and risk prediction of dilated cardiomyopathy in the era of big data and genomics. J. Clin. Med. 10 , 921 (2021).

Tong, J. N. et al. Fasting plasma glucose in the first trimester is related to gestational diabetes mellitus and adverse pregnancy outcomes. Endocrine 75 , 70–81 (2022).

Zhang, D. et al. A clinical model and nomogram for early prediction of gestational diabetes based on common maternal demographics and routine clinical parameters. J. Obstet. Gynaecol. Res. 48 , 2738–2747 (2022).

Zhang, X. et al. Risk prediction model of gestational diabetes mellitus based on nomogram in a Chinese population cohort study. Sci. Rep. 10 , 21223 (2020).

Article   ADS   CAS   PubMed   PubMed Central   Google Scholar  

Li, S., Li, H., Li, C., He, X. & Wang, Y. Development and validation of a nomogram for predicting the risk of pregnancy-induced hypertension: A retrospective cohort study. J. Womens Health (Larchmt) 30 , 1182–1191 (2021).

He, C., Holme, J. & Anthony, J. SNP genotyping: The KASP assay. Methods Mol. Biol. 1145 , 75–86 (2014).

Livak, K. J. & Schmittgen, T. D. Analysis of relative gene expression data using real-time quantitative PCR and the 2(-Delta Delta C(T)) Method. Methods 25 , 402–408 (2001).

Moon, J. H. & Jang, H. C. Gestational diabetes mellitus: Diagnostic approaches and maternal-offspring complications. Diabetes Metab. J. 46 , 3–14 (2022).

Clarke, E., Cade, T. J. & Brennecke, S. Early pregnancy screening for women at high-risk of GDM results in reduced neonatal morbidity and similar maternal outcomes to routine screening. J. Pregnancy 2020 , 9083264 (2020).

Zhang, C., Rawal, S. & Chong, Y. S. Risk factors for gestational diabetes: Is prevention possible?. Diabetologia 59 , 1385–1390 (2016).

Wu, Q. et al. An early prediction model for gestational diabetes mellitus based on genetic variants and clinical characteristics in China. Diabetol. Metab. Syndr. 14 , 15 (2022).

Xie, K. et al. Genetic predisposition to gestational glucose metabolism and gestational diabetes mellitus risk in a Chinese population. J. Diabetes 11 , 869–877 (2019).

Popova, P. V. et al. Association of common genetic risk variants with gestational diabetes mellitus and their role in GDM prediction. Front. Endocrinol. (Lausanne) 12 , 628582 (2021).

Niu, Z. R., Bai, L. W. & Lu, Q. Establishment of gestational diabetes risk prediction model and clinical verification. J. Endocrinol. Investig. 47 , 1281–1287 (2023).

Article   Google Scholar  

Lin, Q. & Fang, Z. J. Establishment and evaluation of a risk prediction model for gestational diabetes mellitus. World J. Diabetes 14 , 1541–1550 (2023).

Li, W. et al. Predictive nomogram of RAGE Genetic polymorphisms and metabolic risk factors for myocardial infarction risk in a Han Chinese population. Angiology 68 , 877–883 (2017).

Tang, G. et al. Evaluation and analysis of incidence and risk factors of lower extremity venous thrombosis after urologic surgeries: A prospective two-center cohort study using LASSO-logistic regression. Int. J. Surg. 89 , 105948 (2021).

Konig, M. & Shuldiner, A. R. The genetic interface between gestational diabetes and type 2 diabetes. J. Matern. Fetal Neonatal Med. 25 , 36–40 (2012).

Download references

This study was supported by: Guangxi Science and Technology Base and Talent Special Project (AD24010027); self-funded research project of The Health Committee of Guangxi (Z-C20241580); the Guangxi Natural Science Foundation of China (2020GXNSFAA238025); Guangxi Young and middle-aged teachers' basic ability improvement project (2020KY12028); Maternal and Child Health Research Project of Guangxi Bagui Scholars (Jun Zhang).

Author information

These authors contributed equally: Gongchen Huang and Yan Sun.

Authors and Affiliations

The Guangxi Key Laboratory of Environmental Exposomics and Entire Lifecycle Health, The School of Public Health, Guilin Medical University, Guilin, 541000, China

Gongchen Huang, Yan Sun, Ruiqi Li, Qiulian Liang & Xiangyuan Yu

Department of Obstetrics and Gynecology, The Second Affiliated Hospital of Guilin Medical University, Guilin, 541000, China

You can also search for this author in PubMed   Google Scholar

Contributions

Conceptualization: X.Y.Y., Q.L.L.; Data curation: L.M.; Formal analysis: Q.L.L., Y.S.; Investigation:Y.S., R.Q.L.; Methodology: X.Y.Y., Q.L.L.; Software: G.C.H., Q.L.L.; Visualization: G.C.H.; Writing-original draft: G.C.H., Y.S., Q.L.L.; Writing-review & editing: X.Y.Y., R.Q.L. All authors reviewed the article and approved the submitted version.

Corresponding authors

Correspondence to Qiulian Liang or Xiangyuan Yu .

Ethics declarations

Competing interests.

The authors declare no competing interests.

Additional information

Publisher's note.

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Supplementary tables., rights and permissions.

Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/ .

Reprints and permissions

About this article

Cite this article.

Huang, G., Sun, Y., Li, R. et al. Functional genetic variants and susceptibility and prediction of gestational diabetes mellitus. Sci Rep 14 , 18123 (2024). https://doi.org/10.1038/s41598-024-69079-y

Download citation

Received : 30 April 2024

Accepted : 31 July 2024

Published : 05 August 2024

DOI : https://doi.org/10.1038/s41598-024-69079-y

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

• Gestational diabetes mellitus
• Genetic susceptibility
• Nomogram model

By submitting a comment you agree to abide by our Terms and Community Guidelines . If you find something abusive or that does not comply with our terms or guidelines please flag it as inappropriate.

Quick links

• Explore articles by subject
• Guide to authors
• Editorial policies

Sign up for the Nature Briefing: Translational Research newsletter — top stories in biotechnology, drug discovery and pharma.

Effect of dietary myo-inositol supplementation on the insulin resistance and the prevention of gestational diabetes mellitus: an open-label, randomized controlled trial

• Maternal-Fetal Medicine
• Published: 14 August 2024

Cite this article

• George Asimakopoulos   ORCID: orcid.org/0000-0001-6587-8226 1 ,
• Vasilios Pergialiotis 1 ,
• Panagiotis Antsaklis 1 ,
• Mariana Theodora 1 ,
• Dimitrios Loutradis 1 &
• George Daskalakis 1  

Myo-inositol (MI) is an insulin-sensitizing dietary supplement, enhancing the transfer of glucose into the cell. Gestational diabetes mellitus (GDM) is characterized by abnormal glucose tolerance, which is associated with elevated insulin resistance. The present study aimed to assess the effect of MI supplementation during pregnancy on the incidence of GDM.

We performed a single-center, open-label, randomized controlled trial. A cohort of 200 pregnant women at 11–13 +6 weeks of gestation were randomly assigned in two groups: MI group (n = 100) and control group (n = 100). The MI group received MI and folic acid (4000 mg MI and 400 mcg folic acid daily), while the control group received folic acid alone (400 mcg folic acid daily) until 26–28 weeks of gestation, when the 75 g Oral Glucose Tolerance Test (OGTT) was performed for the diagnosis of GDM. Clinical and metabolic outcomes were assessed.

The incidence of GDM was significantly higher in the MI group (14.9%) compared to the control group (28.5%) (P = 0.024). Women treated with MI had significantly lower OGTT glucose values, than those not treated with MI (P < 0.001). The insulin resistance as assessed by HOMA-IR was significantly lower in the MI group versus control (P = 0.045). Furthermore, MI group had significantly higher insulin sensitivity as measured by the Matsuda Index, compared to the control group (P = 0.037).

MI supplementation seems to be an effective option to improve the glycemic control of pregnant women and prevent the onset of GDM.

Trial registration

ISRCTN registry: ISRCTN16142533. Registered 09 March 2017.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Subscribe and save.

• Get 10 units per month
• Download Article/Chapter or eBook
• 1 Unit = 1 Article or 1 Chapter
• Cancel anytime

Price includes VAT (Russian Federation)

Instant access to the full article PDF.

Rent this article via DeepDyve

Institutional subscriptions

Data availability

Data will be available upon reasonable request.

(2018) ACOG Practice Bulletin No. 190: gestational diabetes mellitus. Obstet Gynecol 131:e49–64. https://doi.org/10.1097/AOG.0000000000002501

Buchanan TA, Xiang AH (2005) Gestational diabetes mellitus. J Clin Investig 115:485–491. https://doi.org/10.1172/JCI24531

Article   CAS   PubMed   PubMed Central   Google Scholar  

Preda A, Stefan AG, Vladu IM, Fortofoiu M-C, Clenciu D, Fortofoiu M et al (2022) Analysis of risk factors for the development of gestational diabetes mellitus in a group of romanian patients. J Diabetes Res 2022:2367213. https://doi.org/10.1155/2022/2367213

Article   PubMed   PubMed Central   Google Scholar  

HAPO Study Cooperative Research Group, Metzger BE, Lowe LP, Dyer AR, Trimble ER, Chaovarindr U et al (2008) Hyperglycemia and adverse pregnancy outcomes. N Engl J Med 358:1991–2002. https://doi.org/10.1056/NEJMoa0707943

Article   Google Scholar  

Schwartz N, Green MS, Yefet E, Nachum Z (2016) Modifiable risk factors for gestational diabetes recurrence. Endocrine 54:714–722. https://doi.org/10.1007/s12020-016-1087-2

Article   CAS   PubMed   Google Scholar  

Zhu Y, Zhang C (2016) Prevalence of gestational diabetes and risk of progression to type 2 diabetes: a global perspective. Curr Diab Rep 16:7. https://doi.org/10.1007/s11892-015-0699-x

Egeland GM, Skjaerven R, Irgens LM (2000) Birth characteristics of women who develop gestational diabetes: population based study. BMJ 321:546–547. https://doi.org/10.1136/bmj.321.7260.546

Szostak-Węgierek D, Szamotulska K (2011) Fetal development and risk of cardiovascular diseases and diabetes type 2 in adult life. Med Wieku Rozwoj 15:203–215

PubMed   Google Scholar  

Corrado F, D’Anna R, Laganà AS, Di Benedetto A (2014) Abnormal glucose tolerance later in life in women affected by glucose intolerance during pregnancy. J Obstet Gynaecol 34:123–126. https://doi.org/10.3109/01443615.2013.841658

Lowe WL, Scholtens DM, Lowe LP, Kuang A, Nodzenski M, Talbot O et al (2018) Association of gestational diabetes with maternal disorders of glucose metabolism and childhood adiposity. JAMA 320:1005–1016. https://doi.org/10.1001/jama.2018.11628

Formoso G, Baldassarre MPA, Ginestra F, Carlucci MA, Bucci I, Consoli A (2019) Inositol and antioxidant supplementation: safety and efficacy in pregnancy. Diabetes Metab Res Rev 35:e3154. https://doi.org/10.1002/dmrr.3154

Genazzani AD, Lanzoni C, Ricchieri F, Jasonni VM (2008) Myo-inositol administration positively affects hyperinsulinemia and hormonal parameters in overweight patients with polycystic ovary syndrome. Gynecol Endocrinol 24:139–144. https://doi.org/10.1080/09513590801893232

Pintaudi B, Di Vieste G, Bonomo M (2016) The effectiveness of myo-inositol and D-chiro inositol treatment in type 2 diabetes. Int J Endocrinol 2016:9132052. https://doi.org/10.1155/2016/9132052

Asimakopoulos G, Pergialiotis V, Anastasiou E, Antsaklis P, Theodora M, Vogiatzi E et al (2020) Effect of dietary myo-inositol supplementation on the insulin resistance and the prevention of gestational diabetes mellitus: study protocol for a randomized controlled trial. Trials 21:633. https://doi.org/10.1186/s13063-020-04561-2

American Diabetes Association (2021) 2. Classification and diagnosis of diabetes: standards of medical care in diabetes-2021. Diabetes Care 44:S15-33. https://doi.org/10.2337/dc21-S002

Matthews DR, Hosker JP, Rudenski AS, Naylor BA, Treacher DF, Turner RC (1985) Homeostasis model assessment: insulin resistance and beta-cell function from fasting plasma glucose and insulin concentrations in man. Diabetologia 28:412–419. https://doi.org/10.1007/BF00280883

Lorenzo C, Haffner SM, Stančáková A, Kuusisto J, Laakso M (2015) Fasting and OGTT-derived measures of insulin resistance as compared with the euglycemic-hyperinsulinemic clamp in nondiabetic Finnish offspring of type 2 diabetic individuals. J Clin Endocrinol Metab 100:544–550. https://doi.org/10.1210/jc.2014-2299

D’Anna R, Di Benedetto A, Scilipoti A, Santamaria A, Interdonato ML, Petrella E et al (2015) Myo-inositol supplementation for prevention of gestational diabetes in obese pregnant women: a randomized controlled trial. Obstet Gynecol 126:310–315. https://doi.org/10.1097/AOG.0000000000000958

Vasileiou V, Kyratzoglou E, Paschou SA, Kyprianou M, Anastasiou E (2018) The impact of environmental temperature on the diagnosis of gestational diabetes mellitus. Eur J Endocrinol 178:209–214. https://doi.org/10.1530/EJE-17-0730

Matarrelli B, Vitacolonna E, D’Angelo M, Pavone G, Mattei PA, Liberati M et al (2013) Effect of dietary myo-inositol supplementation in pregnancy on the incidence of maternal gestational diabetes mellitus and fetal outcomes: a randomized controlled trial. J Matern Fetal Neonatal Med 26:967–972. https://doi.org/10.3109/14767058.2013.766691

Celentano C, Matarrelli B, Pavone G, Vitacolonna E, Mattei PA, Berghella V et al (2020) The influence of different inositol stereoisomers supplementation in pregnancy on maternal gestational diabetes mellitus and fetal outcomes in high-risk patients: a randomized controlled trial. J Matern Fetal Neonatal Med 33:743–751. https://doi.org/10.1080/14767058.2018.1500545

Vitale SG, Fiore M, La Rosa VL, Rapisarda AMC, Mazza G, Paratore M et al (2022) Liposomal ferric pyrophosphate and ascorbic acid supplementation in pregnant women with iron deficiency anaemia: haematochemical, obstetric, neonatal and psychological outcomes in a prospective observational study. Int J Food Sci Nutr 73:221–229. https://doi.org/10.1080/09637486.2021.1950129

Merialdi M, Carroli G, Villar J, Abalos E, Gülmezoglu AM, Kulier R et al (2003) Nutritional interventions during pregnancy for the prevention or treatment of impaired fetal growth: an overview of randomized controlled trials. J Nutr 133:1626S-1631S. https://doi.org/10.1093/jn/133.5.1626S

Perry A, Stephanou A, Rayman MP (2022) Dietary factors that affect the risk of pre-eclampsia. BMJ Nutr Prev Health 5:118–133. https://doi.org/10.1136/bmjnph-2021-000399

Adams JB, Kirby JK, Sorensen JC, Pollard EL, Audhya T (2022) Evidence based recommendations for an optimal prenatal supplement for women in the US: vitamins and related nutrients. Matern Health Neonatol Perinatol 8:4. https://doi.org/10.1186/s40748-022-00139-9

Baillargeon J-P, Iuorno MJ, Apridonidze T, Nestler JE (2010) Uncoupling between insulin and release of a D-chiro-inositol-containing inositolphosphoglycan mediator of insulin action in obese women with polycystic ovary syndrome. Metab Syndr Relat Disord 8:127–136. https://doi.org/10.1089/met.2009.0052

Nestler JE, Jakubowicz DJ, Reamer P, Gunn RD, Allan G (1999) Ovulatory and metabolic effects of D-chiro-inositol in the polycystic ovary syndrome. N Engl J Med 340:1314–1320. https://doi.org/10.1056/NEJM199904293401703

Gerli S, Mignosa M, Di Renzo GC (2003) Effects of inositol on ovarian function and metabolic factors in women with PCOS: a randomized double blind placebo-controlled trial. Eur Rev Med Pharmacol Sci 7:151–159

CAS   PubMed   Google Scholar  

Unfer V, Carlomagno G, Dante G, Facchinetti F (2012) Effects of myo-inositol in women with PCOS: a systematic review of randomized controlled trials. Gynecol Endocrinol 28:509–515. https://doi.org/10.3109/09513590.2011.650660

Santamaria A, Giordano D, Corrado F, Pintaudi B, Interdonato ML, Vieste GD et al (2012) One-year effects of myo-inositol supplementation in postmenopausal women with metabolic syndrome. Climacteric 15:490–495. https://doi.org/10.3109/13697137.2011.631063

Giordano D, Corrado F, Santamaria A, Quattrone S, Pintaudi B, Di Benedetto A et al (2011) Effects of myo-inositol supplementation in postmenopausal women with metabolic syndrome: a perspective, randomized, placebo-controlled study. Menopause 18:102–104. https://doi.org/10.1097/gme.0b013e3181e8e1b1

Article   PubMed   Google Scholar  

D’Anna R, Di Benedetto V, Rizzo P, Raffone E, Interdonato ML, Corrado F et al (2012) Myo-inositol may prevent gestational diabetes in PCOS women. Gynecol Endocrinol 28:440–442. https://doi.org/10.3109/09513590.2011.633665

D’Anna R, Scilipoti A, Giordano D, Caruso C, Cannata ML, Interdonato ML et al (2013) myo-Inositol supplementation and onset of gestational diabetes mellitus in pregnant women with a family history of type 2 diabetes: a prospective, randomized, placebo-controlled study. Diabetes Care 36:854–857. https://doi.org/10.2337/dc12-1371

Facchinetti F, Pignatti L, Interdonato ML, Neri I, Bellei G, D’Anna R (2013) 60: Myoinositol supplementation in pregnancies at risk for gestational diabetes Interim analysis of a randomized controlled trial (RCT). Am J Obstet Gynecol 208:S36. https://doi.org/10.1016/j.ajog.2012.10.234

Santamaria A, Di Benedetto A, Petrella E, Pintaudi B, Corrado F, D’Anna R et al (2016) Myo-inositol may prevent gestational diabetes onset in overweight women: a randomized, controlled trial. J Matern Fetal Neonatal Med 29:3234–3237. https://doi.org/10.3109/14767058.2015.1121478

Vitale SG, Corrado F, Caruso S, Di Benedetto A, Giunta L, Cianci A et al (2021) Myo-inositol supplementation to prevent gestational diabetes in overweight non-obese women: bioelectrical impedance analysis, metabolic aspects, obstetric and neonatal outcomes—a randomized and open-label, placebo-controlled clinical trial. Int J Food Sci Nutr 72:670–679. https://doi.org/10.1080/09637486.2020.1852191

Amaefule CE, Drymoussi Z, Gonzalez Carreras FJ, Pardo Llorente MDC, Lanz D, Dodds J et al (2022) Myo-inositol nutritional supplement for prevention of gestational diabetes (EMmY): a randomised, placebo-controlled, double-blind pilot trial with nested qualitative study. BMJ Open 12:e050110. https://doi.org/10.1136/bmjopen-2021-050110

Mashayekh-Amiri S, Mohammad-Alizadeh-Charandabi S, Abdolalipour S, Mirghafourvand M (2022) Myo-inositol supplementation for prevention of gestational diabetes mellitus in overweight and obese pregnant women: a systematic review and meta-analysis. Diabetol Metab Syndr 14:93. https://doi.org/10.1186/s13098-022-00862-5

Li C, Shi H (2024) Inositol supplementation for the prevention and treatment of gestational diabetes mellitus: a meta-analysis of randomized controlled trials. Arch Gynecol Obstet 309:1959–1969. https://doi.org/10.1007/s00404-023-07100-x

Paschou SA, Shalit A, Gerontiti E, Athanasiadou KI, Kalampokas T, Psaltopoulou T et al (2024) Efficacy and safety of metformin during pregnancy: an update. Endocrine 83:259–269. https://doi.org/10.1007/s12020-023-03550-0

Wu R, Zhang Q, Li Z (2024) A meta-analysis of metformin and insulin on maternal outcome and neonatal outcome in patients with gestational diabetes mellitus. J Matern Fetal Neonatal Med 37:2295809. https://doi.org/10.1080/14767058.2023.2295809

Wu R, Li Z (2024) Cost-effectiveness analysis of metformin versus insulin in the treatment of gestational diabetes mellitus. Arch Gynecol Obstet. https://doi.org/10.1007/s00404-024-07483-5

Chatzakis C, Cavoretto P, Sotiriadis A (2021) Gestational diabetes mellitus pharmacological prevention and treatment. Curr Pharm Des 27:3833–3840. https://doi.org/10.2174/1381612827666210125155428

Wu R, Luan J, Hu J, Li Z (2024) Effect of probiotics on pregnancy outcomes in gestational diabetes: systematic review and meta-analysis. Arch Gynecol Obstet. https://doi.org/10.1007/s00404-023-07346-5

Esteghamati A, Aryan Z, Esteghamati A, Nakhjavani M (2015) Vitamin D deficiency is associated with insulin resistance in nondiabetics and reduced insulin production in type 2 diabetics. Horm Metab Res 47:273–279. https://doi.org/10.1055/s-0034-1389903

Baynes HW, Mideksa S, Ambachew S (2018) The role of polyunsaturated fatty acids (n-3 PUFAs) on the pancreatic β-cells and insulin action. Adipocyte 7:81–87. https://doi.org/10.1080/21623945.2018.1443662

Griffith RJ, Alsweiler J, Moore AE, Brown S, Middleton P, Shepherd E et al (2020) Interventions to prevent women from developing gestational diabetes mellitus: an overview of cochrane reviews. Cochrane Database Syst Rev 6:CD012394. https://doi.org/10.1002/14651858.CD012394.pub3

Matsuda M, DeFronzo RA (1999) Insulin sensitivity indices obtained from oral glucose tolerance testing: comparison with the euglycemic insulin clamp. Diabetes Care 22:1462–1470. https://doi.org/10.2337/diacare.22.9.1462

DeFronzo RA, Tobin JD, Andres R (1979) Glucose clamp technique: a method for quantifying insulin secretion and resistance. Am J Physiol Endocrinol Metab 237:E214. https://doi.org/10.1152/ajpendo.1979.237.3.E214

Article   CAS   Google Scholar  

Kirwan JP, Huston-Presley L, Kalhan SC, Catalano PM (2001) Clinically useful estimates of insulin sensitivity during pregnancy: validation studies in women with normal glucose tolerance and gestational diabetes mellitus. Diabetes Care 24:1602–1607. https://doi.org/10.2337/diacare.24.9.1602

DeFronzo RA, Matsuda M (2010) Reduced time points to calculate the composite index. Diabetes Care 33:e93. https://doi.org/10.2337/dc10-0646

Farren M, Daly N, McKeating A, Kinsley B, Turner MJ, Daly S (2017) The prevention of gestational diabetes mellitus with antenatal oral inositol supplementation: a randomized controlled trial. Diabetes Care 40:759–763. https://doi.org/10.2337/dc16-2449

Wang H, Li N, Chivese T, Werfalli M, Sun H, Yuen L et al (2022) IDF diabetes atlas: estimation of global and regional gestational diabetes mellitus prevalence for 2021 by International Association of Diabetes in Pregnancy Study Group’s criteria. Diabetes Res Clin Pract 183:109050. https://doi.org/10.1016/j.diabres.2021.109050

Lao TT, Ho L-F, Chan BCP, Leung W-C (2006) Maternal age and prevalence of gestational diabetes mellitus. Diabetes Care 29:948–949. https://doi.org/10.2337/diacare.29.04.06.dc05-2568

Facchinetti F, Appetecchia M, Aragona C, Bevilacqua A, Bezerra Espinola MS, Bizzarri M et al (2020) Experts’ opinion on inositols in treating polycystic ovary syndrome and non-insulin dependent diabetes mellitus: a further help for human reproduction and beyond. Expert Opin Drug Metab Toxicol 16:255–274. https://doi.org/10.1080/17425255.2020.1737675

Wei J, Yan J, Yang H (2022) Inositol nutritional supplementation for the prevention of gestational diabetes mellitus: a systematic review and meta-analysis of randomized controlled trials. Nutrients 14:2831. https://doi.org/10.3390/nu14142831

Costabile L, Unfer V (2017) Treatment of gestational diabetes mellitus with myo-inositol: analyzing the cutting edge starting from a peculiar case. Eur Rev Med Pharmacol Sci 21:73–76

Oostdam N, Bosmans J, Wouters MGAJ, Eekhoff EMW, van Mechelen W, van Poppel MNM (2012) Cost-effectiveness of an exercise program during pregnancy to prevent gestational diabetes: results of an economic evaluation alongside a randomised controlled trial. BMC Pregnancy Childb 12:64. https://doi.org/10.1186/1471-2393-12-64

Download references

Acknowledgements

We would like to thank the staff of Maternal-Fetal Medicine Department and the staff of Diabetes Centre of First Department of Endocrinology in Alexandra Hospital in Athens, Greece.

The study was funded by the investigators. External funding was not received.

Author information

Authors and affiliations.

First Department of Obstetrics and Gynecology, Alexandra Hospital, National and Kapodistrian University of Athens, Athens, Greece

George Asimakopoulos, Vasilios Pergialiotis, Panagiotis Antsaklis, Mariana Theodora, Dimitrios Loutradis & George Daskalakis

You can also search for this author in PubMed   Google Scholar

Contributions

G Asimakopoulos: Protocol development, Data Collection, Manuscript writing. V Pergialiotis: Protocol development, Data analysis, Manuscript editing. P Antsaklis: Data Collection. M Theodora: Protocol development, Data Collection, Manuscript editing. D Loutradis: Protocol development, Manuscript editing. G Daskalakis: Protocol development, Manuscript editing.

Corresponding author

Correspondence to George Asimakopoulos .

Ethics declarations

Conflict of interest.

The authors declare that they have no competing interests.

Ethical approval

The trial was performed with respect for the individual participants according to the Declarations of Helsinki. Approval was granted by the Ethics Committee of the Alexandra University Hospital (Scientific Board of Alexandra Hospital, 28/06/2017, ref: 520/22–06-2017).

Consent to participate

Informed consent was obtained from all individual participants included in the study.

Consent to publish

Not applicable.

Additional information

Publisher's note.

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Asimakopoulos, G., Pergialiotis, V., Antsaklis, P. et al. Effect of dietary myo-inositol supplementation on the insulin resistance and the prevention of gestational diabetes mellitus: an open-label, randomized controlled trial. Arch Gynecol Obstet (2024). https://doi.org/10.1007/s00404-024-07618-8

Download citation

Received : 21 April 2024

Accepted : 25 June 2024

Published : 14 August 2024

DOI : https://doi.org/10.1007/s00404-024-07618-8

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

• Glucose intolerance
• Matsuda index
• Find a journal
• Publish with us
• Track your research