Abstract
Objective: There are two types of criteria for diagnosing gestational diabetes mellitus (GDM). The first is based on measurement of three values on the glucose tolerance test (GTT) and making a diagnosis when any value is abnormal (individual time-point criterion). The second is based on creating a weighted average of the three values and using the average to split glycemic status into normal gestational glycemia (NGG), impaired gestational glycemia (IGG), gestational diabetes (GDM), or high-risk gestational diabetes (hGDM) (unified criterion). There is no information currently regarding how these two criteria relate to each other in the diagnosis of GDM. This study aimed to make this comparison.
Design: Cross-sectional study.
Setting: Publicly available data on a cohort of women in pregnancy.
Participants: Pregnant women from the cohort.
Methods: The cross-classification of diagnosis by two criteria was evaluated. The individual time-point criterion had a binary outcome (GDM yes/no), while the unified criterion had the four aforementioned outcomes.
Results: Within the low risk (non-GDM) category by the individual time-point criterion, 1 in 85 women would have been deemed at high risk by the unified criterion. More importantly, within the high risk (GDM) category by the individual time-point criterion, 1 in 2 women would have been deemed at low risk by the unified criterion.
Conclusion: The standard criterion is not equivalent to the unified criterion in terms of risk estimation. This is important as the unified criterion correlates with area under the GTT curve known to be associated with glucose excursion and is predictive of the net effect of insulin resistance and beta-cell function.
Gestational diabetes mellitus (GDM) refers to a condition in which a pregnant woman experiences glucose intolerance that occurs for the first-time or is first recognized during pregnancy.1 Complications include macrosomia, labor dystocia, and pre-eclampsia. In addition, the management of pregnancies with GDM incurs additional costs.2 According to the International Diabetes Federation (IDF), GDM affects around 1 in 6 live births globally.3 However, recently introduced criteria for diagnosing GDM, such as the International Association of the Diabetes and Pregnancy Study Groups (IADPSG) based on the Hyperglycemia and Adverse Pregnancy Outcome (HAPO) study,4 have resulted in an increase in the incidence of GDM.5
There are many criteria used today to diagnose GDM,4,6-8 and they fall into two categories: standard and unified. The main criteria at present are the standard criteria where GTT thresholds are set at each time-point, and the diagnosis is based on the number of abnormal values. The diagnostic criteria proposed by the IADPSG in 2010 is the current most utilized standard criterion for the diagnosis of GDM globally. This criterion depends on a 75g glucose tolerance test (GTT) initiated in the fasted state between 24-28 weeks of gestation and diagnoses GDM as any positive result above the threshold for any of the three time-points.4 Despite its endorsement by the World Health Organization (WHO), the quality of evidence to support its use is considered low.9 Hence, its accuracy and concurrent use in practice have been questioned for several reasons. Among the shortcomings of the criterion is its failure to consolidate the values of the GTT at each timepoint, which would provide a more holistic picture of a woman’s glucose tolerance in pregnancy. The resulting consequence is a probable overdiagnosis of GDM with the IADPSG/WHO (2013) criterion which, for example, classifies many women at low risk of developing pregnancy complications into the GDM category, hence contributing to the wasting of healthcare resources.10 Specifically, using the WHO 2013 threshold of fasting venous plasma glucose (FVPG) ≥5.1 mmol/L, a study conducted in Denmark demonstrated approximately 40.1% of a cohort was labeled as having GDM, yet most did not experience increased rates of complications such as excessive fetal growth, pregnancy-related hypertension, or higher rates of cesarean deliveries.10 Their findings indicate uniform global thresholds may inappropriately label many low-risk women as GDM, highlighting the need for unified diagnostic criterion based on local epidemiological data.10 Additionally, there has been much disagreement between similarly based criteria regarding both the optimum cut-offs by time-point and the glucose load being used.
Given the above problems, The National Priorities Research Program (NPRP) in Qatar funded a program of research aimed at finding a solution to this issue. The end result was the development of a prototype unified criterion for GDM. It was envisaged this would assist healthcare practitioners in identification and management of GDM in pregnancy through unified evaluation of GTT results using a 75g glucose load.11 The new criterion (called the NPRP criterion) was based on a weighted average of three glucose readings from the GTT, and this single average was then binned into four separate categories based on its magnitude: normal gestational glycemia (NGG), impaired gestational glycemia (IGG), gestational diabetes (GDM), and high-risk gestational diabetes (hGDM). These four categories indicate women who are at a progressively higher risk of both adverse events in pregnancy and the future development of type 2 diabetes (T2DM).11 Despite the availability of such a unified criterion, there has not been an independent evaluation over whether this criterion is equivalent to the standard criteria in the classification of GDM and related dysglycemia. In an effort to shed more light on this issue, this study aimed to cross-classify diagnosis by both criteria as well as identify the exact contribution of different GTT timepoints to the diagnosis of GDM by the IADPSG criterion. This study did not evaluate outcomes of women or their offspring in terms of the utility of these criteria. Rather, we focused on the biochemical differences in classification of GDM by these two criteria, and we demonstrated how each classification system selects different women as abnormal or normal based on their glycemic status. The impact of different classifications in terms of adverse maternal and neonatal outcomes have been published previously11 and are not considered further here.
Methods
Aims, Study Design and Data Source
A cross-sectional study was conducted using the data reported by d’Emden et al.12 as a supplement to their paper, which is publicly available. This dataset contains only biochemical GTT data on women in pregnancy between 24 to 32 weeks of gestation. The aim of this study was to compare selection of women at high-risk (GDM) by two different criteria. The first is the conventional time-point based criteria and the other is a time-point independent criteria, both derive from the standard GTT with timepoints at 0 (fasting), 1 hour, and 2 hours. No data on pregnancy, maternal, or neonatal outcomes was needed, because the aim of this study was to determine the equivalence of these two strategies in the diagnosis of GDM.
Selection of participants included all women in the early third trimester of pregnancy between January 1 to June 30, 2015 and without preexisting diabetes referred for GTT testing to three laboratories in Queensland, Australia: Queensland Medical Laboratory (QML), Sullivan Nicolaides Pathology (SNP), and Pathology Queensland (PathQ). Participants had the biochemical evaluation at a single point in time after referral from their medical examinations, which were conducted in designated healthcare facilities or secondary locations established in urban, suburban, and remote regions throughout the entire state. PathQ calculated the proportion of pregnant women who underwent testing by comparing the dataset to the number of neonatal screening tests for hypothyroidism administered to all newborns. A slight overestimation was observed due to the presence of multiple neonates in some pregnancies.
All GTTs were carried out in accordance with a standardized protocol across three laboratories. The tests were performed after an overnight fast, with no requirement for individuals to consume a high carbohydrate diet in the 72 hours preceding the test. Patients were tested between 7 and 9 am and instructed to consume 75 g of glucose within 10 minutes. Following glucose ingestion, patients remained at the collection center for 2 hours and were asked to rest quietly. The time point prior to glucose ingestion (TP1) was considered as the fasting plasma glucose (FPG), while the time points 1-hour after glucose ingestion (TP2) and 2-hours after glucose ingestion (TP3) were considered as Post-Load Plasma Glucose levels (1hPLG & 2hPLG, respectively). Blood samples were processed according to laboratory protocols and stored at 4°C to minimize glycolysis. Information regarding the duration of gestation was provided by either the referring physician or the patient for SNP and PathQ; however, it was not corroborated through any alternative means.12
NPRP & IADPSG Criteria
The IADPSG criteria defines GDM as any one of the three time-points above a defined threshold as follows: TP1 value ≥5.1 mmol/L or TP2 value ≥10 mmol/L or TP3 value ≥8.5 mmol/L. In other words, if any one of the cut-offs is met, the woman is diagnosed with GDM regardless of whether the other time points are normal.
For the NPRP criterion, each time-point’s plasma glucose level (TP1, TP2, and TP3) is multiplied by its weight, and the three products are summed to give the unified Doi’s Weighted Average Glucose (dwAG) value for each woman. The dwAG is classified into four categories. A dwAG of 6.8 or less, >6.8 to 7.5, >7.5 to 8.6, and above 8.6 indicate NGG, IGG, GDM, and hGDM, respectively.11
Statistical Methods
Descriptive analyses that described the percentage of contribution of each GTT timepoint to the diagnosis of GDM (by IADPSG) or to the diagnosis of IGG, GDM, or hGDM (by NPRP) was presented as pie charts. Similarly, the proportion of patients diagnosed with GDM (by IADPSG) within the subgroups of the NPRP criteria was depicted using pie charts. P values and 95% confidence intervals (CI) were not reported, as they did not contribute to the interpretation of the analysis reported. All descriptive analyses were conducted using Stata 17 SE (StataCorp, College Station, TX, USA).
Results
Of the 26,242 eligible women that underwent a GTT, 22,296 women (84.96%) did not have GDM, and the remaining 3,946 (15.04%) were determined to have GDM, as per the individual time-point based IADPSG criteria (Figure 1). Single time-point abnormalities notably contributed to the diagnosis of GDM in the majority of instances (70.8%) where an isolated TP1 value above the threshold contributed the most, whereas isolated TP2 and TP3 values above the threshold contributed almost equally to GDM diagnosis. The minority of GDM cases were determined by combined time-point values above the threshold. The combination of all three GTT time-points above their thresholds only accounted for 9.0% of the diagnosed cases (Figure 1).
Proportion of GTT timepoints within the two categories of the IADPSG criteria.
Abbreviations: GDM, gestational diabetes mellitus; TP1, timepoint 1; TP2, timepoint 2; TP3, timepoint 3; None, normal at all timepoints.
With respect to the NPRP criterion, the contribution of different time point values to women within different glucose excursion categories was examined. Within the NGG category, the majority had values below the threshold across all three time points (any time-point above the threshold were only N=915/20649; 4.4%). Almost all of the discordant values were isolated TP1 elevations (4.1%, Figure 2, top left panel). Thus, 1 in 25 women at low risk by the unified criterion would be deemed at high risk by the individual time-point criterion. Given the size of this category, this implies a large number (see below).
Proportion of abnormal GTT time points within the four categories of the NPRP criteria. NGG# includes TP3 (0.2%), TP2 (0.1%), TP1+2 (0%) & TP1+3 (0%). IGG# includes TP1+2 (1.3%) & TP1+3 (0.4%). hGDM# includes TP1+3 (1.5%), TP3 (1.5%) & TP1 (0.4%).
Abbreviations: NGG, normal gestational glycemia; IGG, impaired gestational glycemia; GDM, gestational diabetes mellitus; hGDM, high risk gestational diabetes mellitus TP1, FPG; TP2, 1hPLG; TP3, 2hPLG.
About 26.7% of women in the IGG category also had elevated single time-point values. The majority of abnormalities were TP1 elevations, but with almost similar contribution this time from TP2 and TP3 elevations but very few combined time-point elevations. Therefore, 1 in 4, women at low risk by this category of the unified criterion would be deemed high risk if the individual time-point criterion were to be used. Also, the majority of women in this category (71.7%) demonstrated no abnormality at all time-points (Figure 2, top right panel), and therefore, examination of individual time-points does not allow discrimination of NGG and IGG.
Within the NPRP GDM category, the major abnormalities seen were an isolated increase in TP3 followed by TP2 (post-load values at 2h and 1h, respectively), and then followed by no abnormality (Figure 2, bottom left panel). These results imply that 1 in 7 women at high risk by this category of the unified criterion will be deemed low risk when the individual time-point criterion is used for diagnosis.
Finally, the majority (88%) in the NPRP hGDM category were defined by either all three time-points abnormal or a combination of TP2 and TP3 only, with the remaining having other combinations of abnormalities on the time-points (Figure 2, bottom right panel). This category was, therefore, concordant with the diagnosis made when the individual time-points are used for diagnosis.
The over- or under-estimation of risk with the individual time-points when assessed using the four NPRP risk categories is depicted in Figure 3. We observed a total of 2,086 discordant results, and 915 participants with NGG had risk overstated as GDM. There were 910 participants with IGG who also had risk overstated as GDM, and 261 participants with GDM had risk understated as non-GDM by the individual time-point criterion. The individual time-point criterion only demonstrated complete concordance with unified criterion within the hGDM category (Figure 3). Thus, 1 in 2 women (if NGG and IGG discordances are combined) at high risk by the individual time-point criterion are actually low risk by the unified criterion. Similarly, 1 in 85 women at low risk by the individual time-point criterion are actually high risk by the unified criterion (Figure 3).
Distribution of the NPRP criteria classifications according to diagnosis by IADPSG (left pie: IADPSG normal; right pie: IADPSG GDM).
Abbreviations: NGG, normal gestational glycemia; IGG, impaired gestational glycemia; GDM, gestational diabetes mellitus; hGDM, high risk gestational diabetes mellitus.
Discussion
Clearly, the results of this study demonstrate that the two systems for GDM diagnosis are not equivalent, since both strategies select different women as abnormal or normal. Furthermore, the results clarify which timepoints contribute to diagnosis of GDM by either criterion and the extent of diagnosis by the standard criterion based on individual time-points to the unified criterion based on the whole GTT. We report that out of the 22,296 women whom the individual time-point criterion established as having low risk status, 1 in 85 were high risk by the unified criterion. More importantly, among the 3,946 women deemed high risk by the individual time-point criterion, one in two women were low risk by the unified criterion. Therefore, had the unified criterion represented a standard of diagnosis, this would imply a very gross over-diagnosis of GDM by the individual time-point criterion (IADPSG). The latter findings are supported by the results of other studies that suggest the use of single time-point thresholds contribute to over-diagnosis of GDM.10,13,14
The NPRP criteria utilizes the dwAG as a key metric for evaluating glucose homeostasis. The dwAG was investigated in a recent study comparing it to the area under the oral glucose tolerance test (A-GTT).15 The GTT is the existing procedure for determining glucose excursion. The study found a strong positive correlation between dwAG and A-GTT, indicating that dwAG could be an alternative method of assessing glucose tolerance. Additionally, the dwAG was markedly elevated in insulin resistance and impaired beta-cell function, both of which are indicators of imbalance in glucose homeostasis. Specifically, when categorized into the NPRP glucose excursion groups, the dwAG effectively distinguished different levels of insulin sensitivity, as evidenced by its stratification across tertiles of homeostatic model assessment for insulin sensitivity (HOMA-S). This validates the dwAG as a tool that can not only describe glucose tolerance in pregnancy, but also in non-pregnant adults.15
Two recent randomized-controlled trials have directly compared two individual time-point diagnosis methods for GDM, where one method used the IADPSG one-step screening process while the other involved a two-step process using the Carpenter-Coustan GTT criteria, which are more stringent.16,17 GDM was diagnosed in more women (14.5%–16.5%) assigned to the IADPSG approach than in the more stringent approach (4.5%–8.5%), even though the two approaches used individual time-point criteria. That the other primary outcomes showed no significant differences between the two groups16 suggests again that the GDM contribution to outcomes occurred essentially in women who were in the highest category of glycemic risk (akin to what we demonstrate for hGDM in this study), which were captured by both criteria and the difference in GDM incidence suggests differences in over-diagnosis of women at lower risk. These trials, therefore, support our findings of overestimation of risk by the IADPSG criterion. This concurs with a report that the selection of screening criteria may not have a major impact on the prevalence of GDM in a high-risk group.18 This state of affairs has also resulted in variability in GDM detection, affecting accurate calculation of GDM prevalence. A review that aimed to see how different diagnostic criteria for GDM affected its prevalence in a general population of pregnant women throughout the world collected data from 51 population-based studies totaling 5,349,476 pregnant women.19 The pooled global prevalence of GDM, independent of screening threshold category, was 4.4%. The pooled overall prevalence of GDM using the IADPSG diagnostic threshold was 10.6%, the highest pooled prevalence of GDM among studies examined. Meta-regression revealed the prevalence of GDM was substantially greater (6-11 times) in studies that utilized the IADPSG criterion than in other subgroups.
Given that the standard individual time-point approach results in a binary classification, it is expected that making the cut-offs more stringent may reduce over-diagnosis, but this will simply be a trade-off with under-diagnosis. This is consistent with our results, since we demonstrate the frequency of the underlying time-point abnormalities shifts to TP2 and TP3 with increasingly dysglycemic NPRP groups and to a combination of both TP2 and TP3 with hGDM. As our study reports, the IADPSG criterion (which is the least stringent of the individual time-point criteria) downgraded risk in 261 women with high risk by the unified NPRP criterion in this study, and indeed “no individual time-point abnormality” was the third most common biochemical phenotype in the NPRP-based glucose excursion category of GDM. We have previously demonstrated the NPRP groups correlate with glucose excursion under the GTT known to be predictive of the net effect of insulin resistance and beta-cell function.15 Therefore, those deemed non-GDM in this category (by IADPSG) must still have abnormalities in glucose excursion that this standard criterion fails to detect. This is a limitation of the standard criterion, since it could potentially miss opportunities to mitigate consequences of dysglycemia. This again serves to emphasize that, in the absence of a natural threshold, the precise quantitative cutoff values of maternal glycemia utilized for diagnosis, despite being more or less stringent will not be equivalent to the unified criterion, and this is important given the cut-offs at individual time-points may also not be suited for universal global application,10 while the unified criterion that is linked to glucose excursion15 may not have this drawback.
Recent opinion has recommended widespread adoption of the IADPSG criterion with claims that conducting randomized clinical trials in this domain is no longer ethical, since the IADPSG criterion-based diagnosis has demonstrated clinical benefit in terms of prevention of macrosomia and reduction of hypertensive disorders of pregnancy.20 With this rationale, conducting a randomized clinical trial to test new diagnostic criteria for GDM would be deemed unethical. However, given the evidence in support of the IADPSG criterion leading to overdiagnosis, along with increased healthcare costs, this perhaps may need to be revisited.
This study included a large number of women in pregnancy, which is a strength of our findings. However, there were no characteristics of the women included, so a description of the population in terms of past medical history and indices of obesity were not available. In addition, no outcome data were available for evaluation. Nevertheless, this was a study of the biochemical phenotype of these women that occurs as a consequence of these characteristics, and since the aim was to compare two methods of classifying their biochemical phenotype perhaps, this is not a serious limitation. All the women were from Brisbane, which may limit the generalizability of the findings, although it is expected that the biochemical phenotype will be similar across populations and vary for reasons other than ethnicity.
Conclusion
In conclusion, a diagnosis of GDM is critical for providing adequate care and treatment to reduce the risk of developing complications for both the mother and the baby. However, there is much controversy and dispute about the standard individual time-point type criteria used to diagnose GDM, which has several different sets of thresholds and the potential for overdiagnosis. The NPRP criterion were established to aid healthcare practitioners in risk stratification, diagnosis, and control of hyperglycemia developing during gestation in pregnant women and may serve as an alternative to the standard individual time-point criteria. The findings of this study suggest individual time-point thresholds and the unified NPRP criterion are not equivalent in their selection of women to be labeled as normal or abnormal, since the NPRP criterion is a measure of glucose excursion while the standard criterion is not. Further research is required to validate the NPRP criterion and determine the efficacy of this strategy in clinical practice. Overall, this study highlights the need for ongoing evaluation and improvement of diagnostic criteria for GDM to ensure optimal maternal and fetal benefit.
Footnotes
Disclosures: The authors have declared no financial support for this work. All authors declare that there are no relationships or activities that might bias or be perceived to bias their work. The authors confirm that they do not have any affiliations or engagement with any organization or entity that has a financial or non-financial interest in the subject matter or materials discussed in this manuscript.
Data Availability: All data used in this study are publicly available as a supplement to the paper: d’Emden M, McLeod D, Ungerer J, Appleton C, Kanowski D. Development of a fasting blood glucose-based strategy to diagnose women with gestational diabetes mellitus at increased risk of adverse outcomes in a COVID-19 environment. PLoS One. 2020;15(12):e0243192
Author Contributions: AH: Methodology, Formal analysis, Data Curation, Writing - Original Draft, Project administration. AZ: Methodology, Formal analysis, Data Curation, Writing - Original Draft. FRA: Methodology, Formal analysis, Data Curation, Writing – Original Draft. MNA: Methodology, Formal analysis, Data Curation, Writing - Original Draft. NA: Methodology, Formal analysis, Data Curation, Writing – Original Draft. HK: Writing - Review & Editing. KB: Writing - Review & Editing. SB: Writing - Review & Editing. MB: Writing - Review & Editing. ABAS: Writing - Review & Editing. SARD: Conceptualization, Methodology, Formal analysis, Data Curation, Writing - Review & Editing, Supervision.
- Received November 2, 2024.
- Revision received June 15, 2025.
- Accepted June 26, 2025.
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