Background: Gestational Diabetes Mellitus (GDM) is a common metabolic disorder during pregnancy with significant maternal and fetal complications. The Oral Glucose Tolerance Test (OGTT) is the gold standard for diagnosis but has limitations such as fasting requirements and patient discomfort. HbA1c, a measure of long-term glycemic control, has been proposed as an early screening tool. We evaluated the effectiveness of first-trimester HbA1c in screening for GDM and its correlation with pregnancy outcomes. Methods: A prospective cohort study was conducted on pregnant women attending antenatal clinics at 8–12 weeks of gestation. Participants underwent OGTT and HbA1c testing. GDM was diagnosed using DIPSI criteria. Statistical analysis included ROC curve evaluation to determine optimal HbA1c cutoff values. Results: An HbA1c threshold of 5.3% demonstrated high negative predictive value (96.2%) and specificity (71.43%). However, no significant differences were found in maternal age, BMI, prenatal complications, perinatal outcomes, or delivery methods between those with HbA1c <5.3% and ≥5.3%. Conclusion: While HbA1c alone is not sufficient to replace OGTT, it can aid in early risk stratification and reduce the need for extensive OGTT screening. Population-specific cutoff values should be established for accurate diagnosis. Further large-scale studies are necessary to determine its role in predicting adverse pregnancy outcomes.
Gestational Diabetes Mellitus (GDM), which is defined as hyperglycemia diagnosed during pregnancy, is the most prevalent form of diabetes during pregnancy, varying between 1% and 28% depending on population demographics, screening techniques, and diagnostic criteria [1,2,3]. In India, GDM rates range from 10-14.3%, significantly higher than in Western countries, and are projected to reach 20% due to factors such as urbanisation, increasing maternal age, obesity, unhealthy dietary patterns, and genetic predisposition [4,5].
GDM is characterized as carbohydrate intolerance first identified during pregnancy, irrespective of postpartum glycemic status.(6,7,8) It is associated with adverse maternal outcomes, including abortion, polyhydramnios, pre-eclampsia, preterm labor, prolonged labor, and infections. Fetal complications include macrosomia, stillbirth, respiratory distress, shoulder dystocia, neonatal hypoglycemia, and an elevated risk of obesity and type 2 diabetes later in life [9,10].
The Oral Glucose Tolerance Test (OGTT) remains the gold standard for GDM diagnosis, but its limitations include the need for fasting, multiple blood draws, poor reproducibility, and patient discomfort. Alternative diagnostic strategies that eliminate fasting and reduce procedural complexity may enhance GDM screening. Emerging evidence suggests that fetal overgrowth linked to GDM begins early in pregnancy, underscoring the need for earlier detection [11,12,13].
Glycated hemoglobin (HbA1c) serves as a marker of long-term glycemic control, reflecting blood glucose levels over the preceding 3–4 months [14]. The World Health Organization (WHO) and the American Diabetes Association (ADA) endorse HbA1c for diabetes diagnosis in the general population, yet no official recommendations exist for its use in pregnancy [15]. The International Association of Diabetes and Pregnancy Study Groups (IADPSG) suggests screening for overt diabetes using fasting plasma glucose, HbA1c, or random glucose at the first prenatal visit. An HbA1c ≥6.5% is diagnostic of diabetes; however, pregnancy-induced physiological changes may necessitate a lower threshold for GDM diagnosis [16].
HbA1c testing offers advantages such as convenience, reliability, and reduced variability compared to fasting glucose or OGTT. It is unaffected by short-term dietary intake, stress, or physical activity, making it a robust screening tool, particularly during the COVID-19 era. However, limitations include higher cost, interference from hemoglobinopathies, and inaccuracies in conditions affecting red blood cell turnover, such as anemia and chronic malaria [17].
Recent studies have explored HbA1c as a screening tool for GDM, but findings remain inconclusive [18]. Given the potential for early intervention, further research is warranted to establish optimal HbA1c thresholds specific to pregnancy. This study aims to address this gap by evaluating HbA1c as an early screening tool for GDM and also evaluate the pregnancy outcomes in GDM cases.
We conducted a prospective cohort study in the Department of Obstetrics and Gynaecology of a tertiary care centre located in hilly areas of North India, from January 1 to December 31, 2020. The study included all pregnant women attending the antenatal OPD at 8–12 weeks of gestation who consented to participate, regardless of gestational diabetes mellitus (GDM) status. Exclusion criteria included pre-existing diabetes, HbA1c ≥6.5%, OGTT ≥200 mg/dl, multiple pregnancy, severe anemia, chronic illnesses, recent major blood loss, and lack of consent.
We collected data through detailed history, clinical examination, and routine investigations, including OGTT and HbA1c testing via High-Performance Liquid Chromatography (HPLC), were conducted. GDM was diagnosed using DIPSI criteria, where a 75g OGTT was administered, and plasma glucose was measured after two hours.
First Trimester (8–12 weeks)
OGTT <140 mg/dl: Repeat test at 24–28 weeks
OGTT 140–199 mg/dl: Diagnosed as GDM, managed, and no further OGTT was done
OGTT ≥200 mg/dl: Excluded from the study
Follow-Ups at 24–28 Weeks and 32–34 Weeks
OGTT <140 mg/dl: Considered non-GDM
OGTT 140–199 mg/dl: Diagnosed as GDM, managed accordingly
OGTT ≥200 mg/dl: Excluded from the study
GDM patients were managed with medical nutrition therapy (MNT) and physical exercise, with metformin or insulin added if necessary. Maternal and fetal monitoring continued throughout pregnancy, with special attention to complications like polyhydramnios and preeclampsia. Delivery details, neonatal outcomes (APGAR score, birth weight, NICU admission, congenital anomalies, and mortality), and maternal complications were recorded.
Data analysis was conducted using Epi-Info version 7.2, applying the Shapiro-Wilk test for normality, Mann-Whitney test for quantitative variables, and Chi-square test for categorical variables (p<0.05 considered significant). Sensitivity, specificity, predictive values, and the AUC of ROC curves for different HbA1c thresholds were calculated.
The comparison between GDM (n=20) and Non-GDM (n=35) groups showed no statistically significant differences in mean age (26.05±4.5 vs. 26.80±4.3 years, p=0.54), mean BMI (22.57±2.6 vs. 22.8±1.9, p=0.70), or mean HbA1c levels (5.7±0.28 vs. 5.1±0.4, p=0.60) (Table 1).
Table 1: Baseline Characteristics of the Study Participants
Variable | GDM (n=20) | Non-GDM (n=35) | p-value |
Mean age (yrs) | 26.05±4.5 | 26.80±4.3 | 0.54 |
Mean BMI | 22.57±2.6 | 22.8±1.9 | 0.70 |
Mean HbA1C | 5.7±0.28 | 5.1±0.4 | 0.6 |
The Receiver Operating Characteristic (ROC) curve was constructed using OGTT as the reference to evaluate the sensitivity and specificity of first-trimester HbA1c in detecting gestational diabetes mellitus (GDM). The area under the curve (AUC) was 0.859 (95% CI: 0.795–0.958; p<0.0001). A first-trimester HbA1c cutoff value of >5.3 had the highest Youden index (0.664), with a sensitivity of 95% and specificity of 71% for diagnosing GDM (Table 2).
Table 2: ROC Curve Analysis
ROC curve | |
Sample size | 55 |
Positive group | 20 (36.36%) |
Negative group | 35 (63.64%) |
Area under the ROC curve (AUC) | 0.859 |
Standard Error | 0.051 |
95% Confidence interval | 0.759 to 0.958 |
z statistic | 7.081 |
Significance level P (Area=0.5) | <0.0001 |
Youden index | 0.664 |
Associated criterion | >5.3 |
Sensitivity | 95.00 |
Specificity | 71.43 |
Further stratification of data was done based on first trimester HbA1c cut off value obtained among two groups of HbA1c ˂5.3 (group 1) and ≥5.3 (group 2).
We compared outcomes between participants with first-trimester HbA1c <5.3 (n=21) and HbA1c ≥5.3 (n=34), and found no significant differences in mean age (26.5±4.3 vs. 26.6±4.5 years, p=0.94) or mean BMI (22.6±1.9 vs. 22.8±2.3, p=0.73). Prenatal complications, including pre-eclampsia, were similar (14% vs. 18%, p=0.7). Perinatal outcomes, such as abortion (1 vs. 2, p=0.3) and antepartum intrauterine demise (0 vs. 1, p=0.446), did not significantly differ. Total live births (20 vs. 31, p=0.556), preterm (5 vs. 7, p=0.805) and full-term deliveries (15 vs. 24, p=0.911) were comparable. There were no significant differences in spontaneous labor (14 vs. 23, p=0.14), induced labor (5 vs. 8, p=0.9), normal vaginal delivery (17 vs. 25, p=0.5), instrumental delivery (0 vs. 3, p=0.2), or emergency LSCS (2 vs. 3, p=0.9). Macrosomia (0 vs. 3, p=0.2) and NICU admissions (4 vs. 6, p=0.9) were also not significantly different between groups (Table 3).
Table 3: Outcome Comparison of Groups based on the HbA1C Categorisation
Variable | HbA1c < 5.3 (n=21) | HbA1c ³ 5.3 (n=34) | p-value |
Mean age (yrs) | 26.5±4.3 | 26.6±4.5 | 0.94 |
Mean BMI | 22.6±1.9 | 22.8±2.3 | 0.73 |
Prenatal Complications | |||
Pre-eclampsia | 3(14%) | 6(18%) | 0.7 |
Perinatal Outcomes | |||
Abortion | 1 | 2 | 0.3 |
Intrapartum IUD | 0 | 0 | na |
Antepartum IUD | 0 | 1 | 0.446 |
Total live births | 20 | 31 | 0.556 |
Preterm delivery | 5 | 7 | 0.805 |
Full term delivery | 15 | 24 | 0.911 |
Spontaneous labor | 14 | 23 | 0.14 |
Induced labor | 5 | 8 | 0.9 |
Normal vaginal delivery | 17 | 25 | 0.5 |
Instrumental delivery | 0 | 3 | 0.2 |
Emergency LSCS | 2 | 3 | 0.9 |
Macrosomia | 0 | 3 | 0.2 |
NICU admissions | 4 | 6 | 0.9 |
Our present study attempted to evaluate HbA1c as an early screening tool for GDM and assess the pregnancy outcomes in cases based on the value of HbA1c. We found a cut-off value of 5.3% for HbA1c in the first trimester as an effective predictor of GDM in pregnancy.
We found the baseline BMI and age of the participants to be similar and found no significant difference in the overall outcome of pregnancy in the cases who had HbA1c higher or lower than 5.3%.
The prevalence observed in our study (36.4%) was higher compared to findings by Punnose et al. [19] (24.5%), Lai et al. [20] (30.7%), and Khan et al. [21] (17.85%). This difference may be attributed to lifestyle changes during the COVID-19 lockdown, including unhealthy dietary habits, reduced physical activity, and increased psychological stress. Additionally, the variation in prevalence rates could be due to differences in diagnostic criteria, as other studies applied higher cutoff values whereas our study used a lower cutoff of 140 mg/dL.
The mean age of participants in our study was similar to the findings of Punnose et al. [19], who also reported comparable age groups and BMI for GDM and non-GDM cases. In line with our results, Siricharoenthai et al. [22] also found no statistically significant age difference between the two groups. However, studies by Sun et al. [23] reported significantly higher ages in the GDM group. With evolving lifestyle patterns, even younger individuals are increasingly at risk of developing gestational diabetes mellitus, making age differences between groups less pronounced.
Various studies have reported different HbA1c cut-off values for diagnosing gestational diabetes mellitus (GDM), aiming to balance sensitivity and specificity. However, most research suggests that a higher HbA1c level provides greater specificity in detecting GDM. In our study, a lower threshold was identified as optimal. Rajput et al. [24] observed a higher cut-off with strong specificity but lower sensitivity. Similarly, Sun et al. [23] found a comparable threshold with a high positive likelihood ratio. Siricharoenthai et al. [22] reported a slightly lower cut-off, ensuring no false positives. Bhavadharini et al. [25] suggested a different threshold that balanced sensitivity and specificity, while Roca et al. [26] identified a relatively lower cut-off based on the ROC curve. The variation in findings across studies is likely due to differences in diagnostic criteria used for the oral glucose tolerance test (OGTT).
Our study compared pregnancy outcomes in participants with higher and lower first-trimester HbA1c levels and found no significant differences in maternal characteristics such as age and BMI. Prenatal complications, including pre-eclampsia, were similar between groups, as were perinatal outcomes like abortion and intrauterine demise. Delivery patterns, including preterm and full-term births, spontaneous and induced labor, and the mode of delivery, did not show notable variations. Additionally, neonatal outcomes, such as macrosomia and NICU admissions, were comparable across both groups. These findings align with studies by Siricharoenthai et al [22] and Bhavadharini et al [25], who also reported that first-trimester HbA1c had limited predictive value for adverse pregnancy outcomes. However, research by Rajput et al. [24] and Sun et al. [23] suggests that elevated HbA1c levels in early pregnancy may be associated with increased risks, indicating that factors such as ethnicity, diagnostic criteria, and population characteristics may contribute to variations in findings. This highlights the need for further research to determine the clinical utility of first-trimester HbA1c in predicting pregnancy complications.
We had a small sample size in our study however the history taking was very detailed but still caution must be taken before generalising the findings.
We can conclude that Glycated hemoglobin is a convenient, single, non-fasting test with minimal variability, making it a potential tool for gestational diabetes mellitus (GDM) screening. However, the glucose tolerance test remains the gold standard due to its higher diagnostic accuracy. Studies worldwide suggest that HbA1c cannot replace OGTT but may complement it, reducing the need for extensive testing in many pregnant women. Population-specific HbA1c values are essential for accurate diagnosis. Our study found that an HbA1c cutoff of 5.3% had high negative predictive value and specificity, supporting its role in early risk stratification. Further research is needed for definitive conclusions.
Acknowledgments
I sincerely thank my guide, Professor Dr. Meenakshi Kandoria, for her invaluable guidance and support. I am also grateful to my co-guide, Dr. Geetika Gupta Syal, for her encouragement and insightful suggestions. My heartfelt appreciation goes to Professor and Head of Department, Dr. Bishan Dhiman for his constant inspiration. Lastly, I extend my gratitude to all the patients who participated in this study.
Source of Funding
None
Conflicts of Interest
None
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