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. 2026 May 22;26:787. doi: 10.1186/s12884-026-09192-0

A prospective cohort study comparing IADPSG and DIPSI criteria for diagnosing gestational diabetes and evaluating impact on maternal and neonatal health outcomes (DECIDE study protocol)

Yashdeep Gupta 1, Nomita Chandhiok 2, Reema Mukerjee 3, Shrinivas NGadappa 4, Ashish V Gokhle 5, M Geetha 6, Ramesh Sonowal 7, Anjoo Agarwal 8, Jyotsna Suri 9, Sarita Agrawal 10, Kalaivani Mani 11, Neerja Bhatla 12, Nikhil Tandon 1,✉; DECIDE
PMCID: PMC13378154  PMID: 42168896

Abstract

Background

Accurate diagnosis of gestational diabetes mellitus (GDM) is important for improving the short and long-term outcomes of mothers and babies. There are different criteria to diagnose GDM. ​ Around the world, many use the International Association of Diabetes and Pregnancy Study Groups (IADPSG) criteria. ​ However, in India, a different method called the Diabetes in Pregnancy Study Group of India (DIPSI) criteria is more commonly used. ​ However, there is limited evidence comparing how well these two criteria work in improving pregnancy outcomes for Indian women. ​ This study aims to fill that gap by looking at the pregnancy outcomes of women who are diagnosed with GDM using the IADPSG method but are considered normal by the DIPSI method. ​

Methodology

The DECIDE (Diagnostic Evaluation and Comparison of IADPSG and DIPSI criteria for expectant mothers) study is a prospective, multicenter observational cohort study being conducted across seven sites in India, enrolling pregnant women 18 years or older and between 24 to 28 weeks of pregnancy. Two glucose tests are conducted as part of this study. ​ The first test follows the DIPSI method, which does not require fasting beforehand. ​ The second test follows the IADPSG method, which requires fasting overnight and measures blood glucose levels three times, before drinking a glucose solution, one hour after, and two hours after. ​ The results of the IADPSG test are kept blinded from the treating physician and the participant, unless the woman is found to have very high blood glucose levels (overt diabetes). ​Postdelivery, pregnancy outcomes of both the mothers and their newborns are collected using medical records and lab reports. ​

Discussion

This study aims to address the ongoing debate about the effectiveness of two diagnostic criteria for gestational diabetes: DIPSI and IADPSG. ​The goal is to determine whether the higher costs and complexity of adopting the IADPSG criteria are justified by better maternal and neonatal outcomes.​ The findings are expected to provide valuable insights that could help shape national guidelines on appropriate diagnostic criteria for GDM that can help in improving the health of mothers and newborns in India.

Keywords: Gestational diabetes; IADPSG, DIPSI, India, Outcomes, Comparison

Introduction

Gestational diabetes mellitus (GDM) is characterized by elevated blood glucose levels first identified during pregnancy, which are not high enough to be classified as overt diabetes in a nonpregnant population [1, 2]. ​ According to the 11th Edition of the International Diabetes Federation (IDF) Diabetes Atlas, hyperglycemia affects 19.7% of pregnancies, with 80% of these cases attributed to GDM. ​ The prevalence of hyperglycemia during pregnancy is even higher in Southeast Asia, with age-standardized estimates reaching 31.7% [3]. ​ Accurate diagnosis of GDM is essential for improving both short-term outcomes, such as perinatal health, and long-term outcomes, including a reduced risk of diabetes, hypertension, obesity, dyslipidemia and cardiovascular diseases in both mothers and their children [4–6].

The criteria for diagnosing GDM have changed significantly over time. ​ Initially, the O’Sullivan and Mahan criteria were used, which were later improved by Carpenter and Coustan. ​ These criteria were based on identifying blood glucose levels that were 2 standard deviations above the average (95th percentile) to identify women at risk of developing diabetes after pregnancy [7–9]. ​ However, from the perspective of obstetrics, the focus shifted to addressing the risks of adverse pregnancy outcomes caused by GDM, rather than just the mother's future risk of diabetes. ​ While the harmful effects of overt diabetes during pregnancy are well-known, the impact of less severe forms of glucose intolerance was unclear until the Hyperglycemia and Adverse Pregnancy Outcome (HAPO) study provided clarity on this issue [10].

The HAPO study, which included a diverse cohort of 25,000 pregnant women from different countries, clearly established a link between maternal glucose levels and certain adverse pregnancy outcomes [10]. ​ The results of this study were instrumental in creating the International Association of Diabetes and Pregnancy Study groups (IADPSG) criteria, which were later approved by the World Health Organization (WHO) in 2013 [11]. ​ However, it is important to note that no South Asian country participated in the HAPO study.

In 1999, the WHO recommended the use of a 75-g oral glucose tolerance test (OGTT) conducted in a fasting state, with diagnostic thresholds set at fasting glucose levels of ≥ 126 mg/dl and 2-h post-load glucose levels of ≥ 140 mg/dl [12]. ​ The Diabetes in Pregnancy Study Group of India (DIPSI) later adapted this approach, allowing the test to be performed in either a fasting or nonfasting state and relying solely on the 2-h post-load glucose value of ≥ 140 mg/dl for diagnosing GDM [13]. However, in 2013, the WHO endorsed the IADPSG criteria, citing insufficient evidence to support earlier recommendations [11]. ​ While most global guidelines have since adopted the IADPSG criteria for diagnosing GDM [14–18], the Ministry of Health and Family Welfare, Government of India, continues to use the DIPSI criteria [19]. ​ As a result, both the DIPSI and IADPSG criteria are currently in use across India [20].

There is currently no robust study that definitively establishes whether the commonly used DIPSI or IADPSG criteria are more effective in identifying women with GDM and improving perinatal or long-term outcomes in Indian women. ​ The absence of a clear consensus has led to inconsistent approach for diagnosing gestational GDM in India [20]. ​ To tackle this issue, the study focuses on assessing the effectiveness of two commonly used diagnostic criteria for GDM in the country, DIPSI and IADPSG. ​ It aims to compare the perinatal outcomes of women who are considered normoglycemic under the DIPSI criteria but are diagnosed with GDM using the IADPSG criteria, as well as those who are deemed normoglycemic by both criteria.

Methodology

Study design and settings: The DECIDE (Diagnostic Evaluation and Comparison of IADPSG and DIPSI criteria for expectant mothers) study is a prospective, multicenter observational cohort designed to evaluate maternal and fetal outcomes in women diagnosed with GDM or normoglycemia using the IADPSG criteria, among those classified as normoglycemic by the DIPSI criteria. ​ It is being conducted at tertiary care public hospitals equipped with teams of obstetricians, neonatologists, and endocrinologists/diabetologists who possess the necessary research expertise. ​All sites cater predominantly to the low- and middle-income populations of India.

The study spans seven sites across India, ensuring diverse representations of participants from both rural and urban areas. ​ The selection of hospitals was based on their ability to meet the study's requirements, including participant recruitment, conducting oral glucose tolerance tests (OGTTs), and assessing maternal, fetal, and neonatal outcomes. ​ To address ethical concerns, only sites that use DIPSI criteria for diagnosing and managing GDM were included to avoid any ethical concern of not treating women diagnosed with GDM via the IADPSG criteria. The selected sites represent various regions of India—North, Central, West, South, and Northeast India—providing a comprehensive representation of the nation's population.

Objective

The objective of this study is to assess perinatal outcomes in women diagnosed with GDM via the IADPSG criteria and compare these outcomes with those observed in women who are normoglycemic according to the IADPSG criteria among individuals classified as normoglycemic according to the DIPSI criteria. ​

Participant identification and recruitment

Pregnant women attending antenatal care at specific hospital sites are screened based on established inclusion and exclusion criteria. ​ Dedicated study staff explain the details of the study to potential participants, addressing any questions or concerns they may have. ​ Women who show interest and agree to participate by providing informed consent are then enrolled in the study.

Inclusion and exclusion criteria

The inclusion criteria for the study included pregnant women aged 18 years or older with a singleton pregnancy, who are between 24 and 28 weeks of gestation and undergo OGTTs on the basis of both the DIPSI and IADPSG guidelines. ​ The exclusion criteria are women diagnosed with GDM before 24 weeks, those planning to deliver at a different hospital, or those with uncertain gestational age due to the absence of an early ultrasound. ​ Additionally, women with overt or preexisting diabetes, secondary diabetes, or infections such as HIV or hepatitis B or C are excluded from the study. Reasons for exclusion are being collected as part of the screening form [designated as case record form (CRF) A in the study]. Women who are included in this study have to undergo both OGTTs for final eligibility in the study.

Study process

Eligible participants undergo two OGTTs between 24–28 weeks of gestation. ​ The first OGTT is conducted in a nonfasting state and interpreted via DIPSI guidelines [13], with management provided accordingly. ​ DIPSI tests can also be conducted in the fasting state if the woman is fasting. However, no prior instructions are given for fasting/nonfasting for the first OGTT. The second OGTT is performed in a fasting state within 2–3 days of the first test (with the provision to be completed no later than 28 weeks of gestation, in case of delay) and is interpreted via the IADPSG criteria [1]. For the fasting OGTT, the participants fasted overnight, avoiding food from 10:00 PM until the test the next morning. ​ Upon arrival, a baseline blood sample is collected to measure fasting plasma glucose levels. ​ Participants then consume 75 g of anhydrous glucose powder dissolved in approximately 300 ml of water. ​ Blood samples are collected at 1 h and 2 h after glucose consumption. ​ The results of the 2nd OGTT are blinded throughout the study from the treating doctors and participants unless overt diabetes is diagnosed. ​ Blood samples are collected for glucose estimation, and maternal and neonatal outcomes are assessed postdelivery at 4 to 12 weeks. ​

​The results are interpreted on the basis of the following criteria: the IADPSG criteria diagnose GDM with a fasting glucose level ≥ 92 mg/dl, a 1-h glucose level ≥ 180 mg/dl, or a 2-h glucose level ≥ 153 mg/dl, whereas the DIPSI criteria use a 2-h glucose value ≥ 140 mg/dl. ​ If overt diabetes is detected (fasting glucose ≥ 126 mg/dl or 2-h glucose ≥ 200 mg/dl) [21], the results are unblinded, appropriate treatment is initiated, and individuals are excluded from the study.

Data collection at 24–28 weeks

CRF-B (designated form at this stage) captures baseline data for pregnant women enrolled in the study, including demographic details (date of birth, age, occupation, education, and family history of diabetes), obstetric history (last menstrual period, prenatal weight, first antenatal weight, previous pregnancies, and interpregnancy interval), risk factors for GDM (history of GDM, treatment details, hypertension, and modes of conception), anthropometry measurements (height, weight, blood pressure, and comorbid ailments), results of any OGTTs performed before 24 weeks of gestation, and detailed results of OGTTs conducted between 24 to 28 weeks as per the DIPSI and IADPSG protocols. ​ The form also records the procedural details (time of glucose sampling and details of the last meal, whether major/minor, and its duration) for each OGTT (Fig. 1).

Fig. 1.

Fig. 1

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Study flow

Abbreviations: ANC: Antenatal clinic; POG: period of gestation; GTT: glucosetolerance test; GDM: Gestational diabetes mellitus; OGTT: oral glucose tolerance test; IADPSG: International association of diabetes andpregnancy study groups; DIPSI: Diabetes in pregnancy study group of India International Association of Diabetes and 76 Pregnancy StudyGroups

Measurements

Blood samples for glucose estimation are collected in fluoride tubes by trained laboratory technicians using standard venepuncture techniques in a safe and hygienic manner. ​ The samples are transported to the laboratory within two hours in an ice box to maintain their integrity and prevent exposure to extreme temperatures or delays. ​ In the lab, plasma glucose levels are analyzed using standardized methods like glucose oxidase or hexokinase techniques. ​The results are then interpreted based on the diagnostic criteria of either IADPSG or DIPSI to identify GDM. ​ To ensure the reliability of the measurements, all participating hospital laboratories are part of an external quality assurance program, and have internal quality standards.

Blood pressure is measured using a calibrated sphygmomanometer (Omron HEM 7156) with the participant seated comfortably and her arm supported at heart level. ​ Both systolic and diastolic readings are recorded at baseline. ​ Weight is measured using a digital scale, with the participant standing upright, barefoot, and wearing light clothing (Omron HN 300 T). ​ Height is measured using a stadiometer (Prestige), ensuring the participant stands straight with her heel, back, and head aligned against the device. ​ Body mass index (BMI) is calculated using the formula: weight (kg) divided by height squared (m2).

Primary outcome

The primary outcome of the study is a composite measure that includes seven significant adverse perinatal outcomes. ​ These are.

  1. Large for Gestational Age (LGA)

  2. Hypertensive disorders of pregnancy (excluding chronic hypertension). ​

  3. Clinically significant neonatal hypoglycemia

  4. Hyperbilirubinemia

  5. Respiratory distress syndrome (RDS)

  6. Preterm birth

  7. Perinatal Mortality

Detailed definitions for each of these outcomes are provided in Table 1 [22].

Table 1.

Maternal and Neonatal Outcomes and Definitions

Category Outcome Definition Measurement Method
Primary Outcomes Large for Gestational Age ​ Birthweight above the 90th percentile for gestational age ​ Intergrowth 21 standards
Hypertensive disorders of pregnancy De novo hypertension appearing after gestational week 20, Systolic BP ≥ 140 mmHg and/or diastolic BP ≥ 90 mmHg with/without additional maternal organ dysfunctions ​ Blood pressure monitoring and lab tests ​
Clinically Significant Neonatal Hypoglycemia ​ Plasma glucose value below 2.2 mmol/L ​ Blood glucose test ​
Hyperbilirubinemia Need for phototherapy or exchange transfusion ​ Medical records
Respiratory Distress Syndrome ​ Respiratory difficulties requiring positive pressure ventilation > 24 h or surfactant use ​ Clinical observation
Preterm Birth Babies born before 37 weeks gestational age ​ Gestational age assessment ​
Perinatal Mortality Infant deaths within 28 days or fetal deaths ≥ 20 weeks’ gestation ​ Medical records
Hypertension Parameters Gestational Hypertension De novo hypertension appearing after gestational week 20, A systolic blood pressure ≥ 140 mmHg and/or a diastolic BP ≥ 90 mmHg ​ Blood pressure monitoring
Pre-eclampsia Systolic BP ≥ 160 mmHg and/or diastolic BP ≥ 110 mmHg Coexistence of one or more of the following new onset conditions:1. Proteinuria (spot urine protein/creatinine ratio ≥ 30 mg/mmol (0.3 mg/mg) or ≥ 300 mg/day or at least 1 g/L (‘2+’) on dipstick testing)2. Other maternal organ dysfunction:• Renal insufficiency (creatinine ≥ 1.02 mg/dL)• Liver involvement (elevated transaminases: at least twice upper limit of normal + right upper quadrant or epigastric abdominal pain)• Neurological complications (examples include eclampsia, altered mental status, blindness, stoke, or more commonly hyperreflexia when accompanied by clonus, severe headaches when accompanied by hyperreflexia, persistent visual scotomata)• Hematological complications (thrombocytopenia: platelet count below 150,000/dL, DIC, hemolysis)3. Uteroplacental dysfunction: Fetal growth restriction ​ Blood pressure and lab tests ​
Delivery Parameters Operative Vaginal Delivery ​ Application of vacuum or forceps to the fetal head ​ Medical records
Caesarean Section Extraction of the fetus through an abdominal incision ​ Medical records
Abortion and Fetal Death ​ Miscarriage Loss of pregnancy before 20 weeks ​ Medical records
Stillbirth Delivery of a fetus showing no signs of life at ≥ 20 weeks’ gestation or ≥ 350 g weight ​ Medical records
Late Fetal Death ​ Fetal death at ≥ 28 weeks’ gestation ​ Medical records
Early Neonatal Death ​ Neonatal death within < 7 days ​ Medical records
Late Neonatal Death ​ Neonatal death within 7–28 days ​ Medical records
Live Neonatal Parameters ​ Birth Injury/Trauma Includes spinal cord injury, peripheral nerve injury, fractures, or cranial hemorrhage ​ Clinical observation and imaging
Respiratory Distress of Neonate ​ Respiratory difficulties requiring positive pressure ventilation > 24 h or surfactant use ​ Clinical observation
Neonatal Hypoglycemia Plasma glucose value below 2.2 mmol/L ​ Blood glucose test ​
Higher Level of Neonatal Care ​ Admission to neonatal intensive care unit or special care nursery > 24 h ​ Medical records
Hyperbilirubinemia Need for phototherapy or exchange transfusion ​ Medical records
Apgar Scores Measure of newborn health at 1 and 5 min (0–10 points) ​ Clinical observation
Large for Gestational Age ​ Birthweight above the 90th percentile for gestational age ​ Intergrowth 21 standards
Small for Gestational Age ​ Birthweight below the 10th percentile for gestational age ​ Intergrowth 21 standards
Macrosomia Birthweight ≥ 4000 g ​ Birthweight measurement
Birthweight In grams (4 digits) ​ Birthweight measurement
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Secondary outcomes

Each individual outcome listed under the primary composite outcome will be analyzed separately as a secondary outcome. ​ Additionally, this study will assess a broad spectrum of maternal, fetal, and neonatal outcomes associated with GDM to provide a comprehensive understanding of its health impacts. ​ Hypertension-related outcomes include gestational hypertension and preeclampsia. ​ Delivery outcomes encompass operative vaginal deliveries, including vacuum- and forceps-assisted procedures, as well as cesarean sections, and the timing of birth to determine preterm deliveries. ​ Neonatal outcomes focus on birth injuries, Apgar scores, and growth parameters such as large or small for gestational age, macrosomia, and birth weight. Detailed definitions for these outcomes are provided in Table 1 [22].

Procedure for outcome data collection

The study involves collecting detailed information such as the date of delivery, the gestational age at the time of delivery, the baby's birth weight, the method of delivery, and any complications or outcomes affecting the mother or baby. ​ If a participant delivers outside the study hospital, the researchers make efforts to obtain relevant data from hospital records, birth notes, or by directly contacting the patient. ​ However, since the care provided outside the study sites may differ, these external cases are not factored into the final sample size calculation. However, efforts will be made to collect data from these participants to achieve a comprehensive understanding of outcomes across all eligible participants. ​

A telephone follow-up is conducted at 4 weeks post-partum to capture any additional delivery and fetal outcome data that may not have been recorded at the time of delivery. ​ If participants cannot be reached at 4 weeks, follow-up attempts are made via telephone, email, or postal mail up to 24 weeks post-partum. ​ Participants are classified as lost to follow-up only if no contact is established within this 24-week period. ​

Outcome data are systematically recorded in the CRF-C (case record form for capturing study outcomes), which includes sections for hypertensive or amniotic fluid disorders, treatment for GDM, delivery outcomes, and fetal outcomes. ​ Supporting documents, such as hospital records and laboratory reports, are collected to validate the recorded data. ​ All outcome data are cross-verified by site staff and investigators before being entered into the e-CRF. ​

Sample size calculation

The sample size calculation for this study is based on the assumption that 88% of women will be normoglycemic according to both the DIPSI and IADPSG criteria, 2% will have GDM identified by both criteria, 8% will have GDM diagnosed solely by the IADPSG criteria, and 2% will have GDM diagnosed solely by the DIPSI criteria (Fig. 2) [23]. ​ This study aimed to detect an absolute risk difference of 5% for adverse outcomes in women diagnosed with GDM via the IADPSG criteria alone compared with normoglycemic women, with a statistical power of 90% and a significance level of 5%. ​

Fig. 2.

Fig. 2

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Assumptions based for sample size calculation

It is estimated that 30% of normoglycemic women (by both criteria) will experience the primary outcome, whereas 35% of women diagnosed with GDM using the IADPSG criteria (but classified as normoglycemic by the DIPSI criteria) will experience adverse outcomes. ​ To achieve the required statistical power, outcome data for 12,900 women are needed. ​ When a 20% loss to follow-up is accounted for, both OGTTs need to be conducted for 16,125 women. ​

Statistical analysis

The study's statistical analysis will examine the association between GDM, as diagnosed using the IADPSG criteria, and adverse outcomes during pregnancy and childbirth. ​ Women who are considered normoglycemic according to both the DIPSI and IADPSG criteria will be used as the comparison group. ​Absolute risk difference will be evaluated for the primary and secondary outcomes. To analyze the data, we will use logistic regression models to assess both raw and adjusted relationships. ​ The adjustments will take into account important factors such as the mother's age, body mass index (BMI), and number of previous pregnancies, which were identified as significant variables in the HAPO study.

Data entry, storage and verification

The process of data entry, storage, and verification in the study is carried out to ensure both accuracy and confidentiality. ​ Information collected from various sources, such as case record forms (CRFs), medical records, and study questionnaires, is entered into a secure electronic database. ​ This database is protected with a password, and only authorized personnel have access to it. ​ Important documents, including signed CRFs and informed consent forms, will be stored securely for at least five years after the study concludes. ​

To ensure the data remains accurate, the central team conducts thorough validation checks to identify and resolve any errors, discrepancies, or inconsistencies. ​ Queries are generated for resolution, and once corrections are made, the revised data are re-entered into the database. ​ Validation process is repeated until all issues are resolved. ​ Regular backups are performed to prevent data loss, and periodic "freezes" are implemented to create permanent copies for analysis. ​ These steps are taken to maintain the reliability, security, and integrity of the study's data. ​ The data is managed using RedCap software, which is hosted on a secure server at AIIMS, Delhi.

Study timelines

The study is planned to take around four years to complete. ​ The first three months were dedicated to recruiting staff and obtaining ethical approvals. ​ Participant recruitment is progressing smoothly and consistently, with a target of enrolling 66 participants per month at each of the seven study sites. ​ Data collection and cleaning are being carried out simultaneously during the recruitment phase and will continue until the final follow-up visit. ​ The last phase of the study will focus on finalizing data cleaning, conducting statistical analyses, and preparing the final report, which is expected to take three months (Table 2). ​ The study is scheduled to finish by the end of 2026, and the main findings are expected to be published in 2027.

Table 2.

Gantt Chart Representation for the Study

Task 0–3 Months 4–39 Months 40–45 Months 45–48 Months
Recruitment of Staff ​ ✔
Ethical Clearance ✔
Recruitment of Participants ​ ✔
Conducting OGTTs ✔
Data Collection (Maternal/Neonatal Outcomes) ​ ✔ ✔
Data Cleaning and Analysis ​ ✔
Preparation of Final Report ✔
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Ethics

The study adheres to strict ethical guidelines to ensure the protection of participants' rights, safety, and well-being. ​ Before starting the study, institutional ethics committees (IECs) at all participating institutions thoroughly reviewed and approved the study protocol. ​ Participants are required to provide informed consent in their preferred language, ensuring they fully understand the study's purpose, procedures, potential risks, and benefits. ​ Participation in the study is completely voluntary, and individuals can withdraw at any time without it affecting their medical care. ​ To maintain confidentiality, all data is securely stored, and coded identifiers are used to protect participants' privacy. The study team has received proper training in research ethics, and all processes comply with good clinical practice (GCP) standards.

Discussion

GDM is a significant public health issue, especially in South Asia, where the rates of high blood glucose during pregnancy are among the highest in the world [3]. ​ In India, there is ongoing debate about the effectiveness of two diagnostic criteria for GDM: DIPSI and IADPSG [24–27]. ​ The DECIDE study seeks to address this issue by comparing the outcomes for mothers and babies diagnosed using these two methods. ​ The goal is to provide evidence that can help shape better policies for diagnosing and managing GDM in India. ​

The DIPSI criteria are widely used in India because they are simple and cost-effective. ​ They involve a nonfasting OGTT that measures blood glucose levels two hours after consuming glucose [13]. ​ This makes it suitable for settings with limited resources. ​ However, DIPSI has some drawbacks, such as not accounting for fasting blood glucose levels, which can lead to missed cases of isolated fasting hyperglycemia, a common form of GDM in India. ​ Additionally, the DIPSI criteria have not been thoroughly validated against pregnancy outcomes, raising questions about their ability to identify women at risk for complications [26, 27].

The IADPSG criteria, which are endorsed by the WHO, involve conducting a fasting oral OGTT and measuring fasting, 1-h, and 2-h glucose levels [1]. ​ These criteria are considered more sensitive and have been validated against pregnancy outcomes [10], allowing for early interventions to improve maternal and neonatal health. ​ However, the IADPSG method is resource-intensive, requiring fasting tests and multiple blood samples, which may not be practical in low-resource settings [13, 15]. ​ Additionally, it may overestimate the prevalence of GDM in South Asian populations and does not fully account for ethnic differences, suggesting the need for region-specific glucose thresholds [26, 27]. ​

On the other hand, the DIPSI criteria, widely used in India, have been found to have lower sensitivity in diagnosing GDM compared to the IADPSG criteria [23, 28]. ​ Research indicates that women diagnosed with GDM under the IADPSG criteria but missed by the DIPSI criteria tend to have more severe hyperglycemia [29], worse pregnancy outcomes, and a higher risk of postpartum diabetes compared to women classified as normoglycemic [25, 30]. ​ The DECIDE study, conducted across India with a large sample size, aims to determine whether these women face higher risks of adverse pregnancy outcomes. ​ If the study confirms increased risks, it would support the adoption of the IADPSG criteria despite their higher costs and complexity. ​ However, if the outcomes are similar, the DIPSI criteria could be validated as a more practical and cost-effective option for diagnosing GDM in India.

The study is designed as a prospective multicenter observational cohort and is being conducted across seven different sites in India. ​ This approach will ensure that data is collected from a variety of regions, making the findings more applicable to the broader population. ​ Participants are recruited from centers that use the DIPSI criteria, while the IADPSG testing is conducted in a blinded manner to address ethical concerns and allow for a direct comparison between the two diagnostic methods. ​ The study focuses on a primary composite outcome, which includes seven significant adverse events linked to maternal hyperglycemia, such as large-for-gestational-age infants and preeclampsia. ​ Additionally, secondary outcomes like delivery details and neonatal complications are being analyzed to provide a thorough understanding of how gestational diabetes impacts maternal and fetal health. ​ The study will also examine glucose thresholds related to adverse outcomes, aiming to identify diagnostic cutoffs that may be more appropriate for South Asian populations.

The study's sample size calculation, based on previous research, ensures that there is enough statistical power to identify differences in outcomes between the groups being studied. ​ By involving seven sites and enrolling over 16,000 participants, the study aims to represent a wide range of populations and healthcare settings across India. ​ The results of this research could have significant implications for public health policies in the country, as millions of pregnancies require testing for gestational diabetes each year. ​ The choice of diagnostic criteria plays a crucial role in shaping healthcare systems, allocating resources, and improving maternal and fetal health outcomes. ​ Additionally, this study will set the stage for future research, such as randomized controlled trials and long-term follow-up studies, to better understand the overall impact of GDM on the health of mothers and their children in India.

In conclusion, this study is an important effort to address the ongoing debate about the best criteria for diagnosing GDM in India. ​ By offering evidence-based findings on how different diagnostic methods impact pregnancy outcomes, the study aims to contribute valuable information that can help shape national healthcare guidelines on screening of GDM.

Acknowledgements

We acknowledge the following research staff who are contributing to the execution of the DECIDE study. Shubham Shirsath, Udayasree Manchollu, Devika Ashok Mudhragadda, Rajvee Parikh, Trupti Solanki, Aayushi Dulera, Mansi Derasari, Mamta Padhiyar, Arularasan M, Arshadh S, Srijona Hazarika, Ratul Gogoi, Tikendra Gogoi, Shruti Tiwari, Vivek K Gupta, Aniket Yadav, Shailendra Gupta, Deepanshi Saini, Naziya Shireen, Varsha, Deepak Bist, Sahil Bishwal, Ankit K Shukla, Diksha Mahilang, Akanksha Verma, Vasinee Sinha, Neha Mohabanshi, Amitosh Dandsena, Pranjal Kumar DECIDE study collaborative authors list: Sonali Deshpande1, Rupali Gaikwad1, Purvi K Patel2, Sonali Agarwal2, A Suganya3, T Uma3, T S Meena3, K Kalaivani3, G Kuppulakshmi3, C Sumathi3, Pulak Kalita4, Aukifa K S Islam4, Ajit Kr Pegu4, Rashmi Rajkakati4, Amita Pandey5, Vandana Solanki5, Shalini Tripathi5, Mohd Kaleem Ahmad5, Sumitra Bachani6, Krishna Biswas6, Anita Rani6, Pradeep Debata6, Nilaj Kumar Bagde7, Amritava Ghosh7, Rachita Nanda7, Atiya Raza7, Maitreyi Dhir8, Akanksha8, Prachi Tewari8, Mugdha Ratnaparkhi1, Jayesh Parmar2, Arvind Bharani R S3, Rashi Sonowal4, Kritika Jain5, Seema Kush6, Mr N Sai Pawan7 1.Department of Obstetrics & Gynaecology, Government Medical College, Aurangabad, Maharashtra, India 2.Department of Obstetrics & Gynaecology, Medical College and SSG Hospital, Vadodara, India 3.Department of Obstetrics & Gynaecology, Institute of Obstetrics and Gynaecology and Government Hospital for Women and Children, Chennai, India 4.Department of Obstetrics & Gynaecology, Assam Medical College and Hospital, Dibrugarh, India 5.Department of Obstetrics & Gynaecology, King George's Medical University, Lucknow, India 6.Department of Obstetrics & Gynaecology, VMMC and Safdarjung Hospital, New Delhi, India 7. Department of Obstetrics & Gynaecology, All India Institute of Medical Sciences, Raipur, India 8.Department of Endocrinology & Metabolism, All India Institute of Medical Sciences, New Delhi, India

Authors’ contributions

YG wrote the first draft. All authors of the writing group critically reviewed and edited the manuscript.

Funding

The study is funded by Indian Council of Medical Research, India. The funder has no role in conceptualization, design, data collection, analysis, decision to publish or preparation of the manuscript.

Data availability

No data has been generated for this manuscript.

Declarations

Ethics approval consent to participate

No participant data is reported here. The current publication is the protocol of the DECIDE study.

Ethical approval was obtained from ethics committee of All India Institute of Medical Sciences, New Delhi, and all of the seven participating sites before enrolment of the participants.

Consent for publication

No participant data is reported here. The current publication is the protocol of the DECIDE study.

Competing interests

The authors declare no competing interests.

Footnotes

Publisher’s Note

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

Contributor Information

Nikhil Tandon, Email: nikhil_tandon@hotmail.com.

DECIDE:

Sonali Deshpande, Rupali Gaikwad, Rupali Gaikwad, Purvi K Patel, Sonali Agarwal, A Suganya, T Uma, T S Meena, K Kalaivani, G Kuppulakshmi, C Sumathi, Pulak Kalita, Aukifa K S Islam, Ajit Kr Pegu, Rashmi Rajkakati, Amita Pandey, Vandana Solanki, Shalini Tripathi, Vandana Solanki, Mohd Kaleem Ahmad, Sumitra Bachani, Krishna Biswas, Anita Rani, Pradeep Debata, Nilaj Kumar Bagde, Amritava Ghosh, Rachita Nanda, Atiya Raza, Maitreyi Dhir, Akanksha Verma, Prachi Tewari, Mugdha Ratnaparkhi, Jayesh Parmar, Arvind Bharani, Rashi Sonowal, Kritika Jain, Seema Kush, and Mr N Sai Pawan

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