Impact of the International Association of Diabetes and Pregnancy Study Groups criteria for gestational diabetes

diabetes research and clinical practice 108 (2015) 288–295

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Diabetes Research and Clinical Practice jou rnal hom ep ag e: w ww.e l s e v i er . c om/ loca te / d i ab r es

Impact of the International Association of Diabetes and Pregnancy Study Groups criteria for gestational diabetes Janet Trujillo a,*, Alvaro Vigo a, Bruce B. Duncan a, Maicon Falavigna a,b, Eliana M. Wendland c, Maria A. Campos d, Maria I. Schmidt a a

Post Graduate Studies Program in Epidemiology, School of Medicine, Federal University of Rio Grande do Sul, Porto Alegre, Brazil b Institute for Education and Research, Hospital Moinhos de Vento, Porto Alegre, Brazil c Federal University of Health Sciences, Porto Alegre, Brazil d Conceic¸a˜o Hospital, Porto Alegre, Brazil

article info

abstract

Article history:

Aims: To evaluate the diagnostic criteria of the International Association of Diabetes and

Received 29 July 2014

Pregnancy Study Groups (IADPSG) and alternative criteria in terms of resultant prevalence

Received in revised form

of gestational diabetes mellitus (GDM) and measures of diagnostic impact.

11 November 2014

Methods: The Brazilian Gestational Diabetes Study (EBDG) is a cohort of pregnant women

Accepted 6 February 2015

enrolled consecutively in prenatal care clinics of the Brazilian National Health Service from

Available online 21 February 2015

1991 to 1995, a time and setting in which those with lesser than diabetes hyperglycemia rarely received drug treatment. Eligibility criteria were age 20 years, gestational age 20–28

Keywords:

weeks and no history of diabetes outside pregnancy. After interview and anthropometric

Diagnostic criteria

measurements, a standardized 2 h 75 g OGTT was scheduled. Women were followed

Gestational diabetes mellitus

through early postpartum.

Large for gestational age

Results: Prevalence of GDM defined by IADPSG criteria was 18.0% (95% CI 16.9–19.0), ranging

Preeclampsia

from 2.7 to 17.0% with the alternative criteria. Relative risks for large for gestational age (LGA) and preeclampsia were generally small. The diagnostic impact assessed by pre- to post-test gain in the probability of an outcome was also small (3.6% for LGA and 0.5% for preeclampsia). Alternative criteria reached maximum gains of 9.7% and 5.3%, respectively. The fractions of LGA births and preeclampsia attributable to GDM by the IADPSG criteria were small, 6.7% and 3.5%, respectively. Conclusions: The IADPSG criteria identify more women as having GDM but their diagnostic and population impacts with respect to adverse outcomes are small. Alternative definitions, although also presenting small diagnostic and population impacts, showed advantages which may be useful in specific settings. # 2015 Elsevier Ireland Ltd. All rights reserved.

* Corresponding author at: Rua Ramiro Barcelos 2600, sala 414, 90035-003 Porto Alegre, RS, Brazil. Tel.: +55 51 33085347. E-mail address: [email protected] (J. Trujillo). http://dx.doi.org/10.1016/j.diabres.2015.02.007 0168-8227/# 2015 Elsevier Ireland Ltd. All rights reserved.

diabetes research and clinical practice 108 (2015) 288–295

1.

Introduction

Gestational diabetes mellitus (GDM), a state of carbohydrate intolerance first detected during pregnancy, although recognized for decades as a relevant clinical condition, does not have a consensual definition, and the exact approach for its diagnosis has been controversial over the years. The American Diabetes Association (ADA) and the American College of Obstetricians and Gynecologists (ACOG) have traditionally recommended pregnancy-specific procedures and criteria based on a 3 h 100 g oral glucose tolerance test (OGTT), as initially derived and validated by O’Sullivan’s group [1]. More recently, these cut-offs for plasma glucose have been adapted for modern laboratory procedures [2], and for use during a 2 h 75 g OGTT [3]. In 1999, the World Health Organization (WHO) Expert Committee, reiterating previous positions, recommended diagnosing GDM based on procedures and criteria established for use outside of pregnancy, labeling as GDM women who meet criteria for diabetes or impaired glucose tolerance during a 75 g OGTT [4]. These recommendations have been largely used around the world, frequently with minor adaptations, for example, also labeling as GDM women meeting cut-offs for impaired fasting glucose [5–7]. In 2010, the International Association of Diabetes and Pregnancy Study Groups (IADPSG), after analyzing results of the Hyperglycemia Adverse Pregnancy Outcome (HAPO) study [8], proposed new diagnostic criteria for GDM based on a 75 g OGTT utilizing fasting, 1 h and 2 h plasma glucose samples. The cut offs chosen indicated a 75% increased risk of adverse pregnancy outcomes [9]. These recommendations have been endorsed by World Health Organization panel in 2013 [10]. The U.S. Preventive Services Task Force did not endorse these recommendations, highlighting that additional research is needed to help determine the most beneficial glucose cut offs [11]. The aim of this study is to evaluate, in a preexisting cohort of pregnant women, the impact of the IADPSG diagnostic criteria, as well as alternative ones, in terms of resulting GDM prevalence, and in terms of capacity to predict preeclampsia and large for gestational age (LGA) newborns.

2.

Materials and methods

These analyses are based on the Brazilian Gestational Diabetes Study (EBDG), a cohort study of 5564 pregnant women, 20 years or older with no history of diabetes outside pregnancy, consecutively enrolled at gestational weeks 20–28 in prenatal care clinics at the National Health Service of Brazil from May, 1991 to August, 1995 [12]. Ethics committees of each center approved the study protocol (Institutional Review Board project number 90058), and all patients gave informed consent to participate. The study was observational in nature and occurred at a time when screening for GDM was not standardized and treatment for those with lesser than diabetes hyperglycemia (defined by the 1980 WHO diagnostic recommendations, fasting plasma glucose 140 mg/dl and 2 h post 75 g OGTT 200 mg/dl) was uncommon.

289

After excluding 566 women who did not perform or had incomplete values for the OGTT, 21 women reaching criteria for diabetes as defined by the 1999 WHO diagnostic criteria (fasting plasma glucose level 126 mg/dl and/or 2 h plasma glucose level 200 mg/dl), 2 additional women who received insulin treatment, and 49 women with multiple pregnancies, data were available for 4926 (89%) women. Missing values for the different outcomes led to variation in the total number available for specific analyses. At enrolment, all women responded to a structured questionnaire and were then scheduled for a 2 h 75 g anhydrous glucose OGTT according to standardized WHO procedures (plasma glucose was measured in fasting, after load in 1 h and 2 h) [4]. The blood samples were collected in fluoride tubes and kept at 4 8C until centrifugation, up to 2 h later. Plasma glucose was measured by glucose oxidase method in local laboratories previously certified by the Study’s quality control committee. External quality controls with three different glucose concentrations were used for certification and monitoring. A coefficient of variation 5% at any point was a reason to suspend glucose determinations. Women were followed through delivery, data on outcomes being collected from chart review using a structured protocol. LGA was defined as a birth weight at or above the gestational age-specific (by week) 90th percentile for the study sample, as previously described [12]. Preeclampsia (or eclampsia) was ascertained as either chronic or incident hypertension associated with proteinuria (or convulsions) after the 20th week of gestation, in accordance with the recommendations of the National High Blood Pressure Education Program Working Group [13]. Body mass index (BMI) was calculated from anthropometric measures at enrolment obtained in duplicate following a standardized protocol. GDM was defined according to the IADPSG criteria (at least one value 92 mg/dl, 180 mg/dl, or 153 mg/dl, respectively, for the fasting, 1 h, and 2 h values) [9]. Alternatives to the IADPSG criteria were also examined using cut-off points defined by a 100%, rather than 75% increased risk (fasting 95 mg/dl, 1 h 191 mg/dl and 2 h 162 mg/dl) [14]; using only the fasting (92 mg/dl), the 1 h (180 mg/dl), or the 2 h (153 mg/dl) samples; and using only both fasting and 1 h samples [15] or both 1 h and 2 h samples. We also considered a more strict GDM definition, requiring the presence of at least two results at or above IADPSG cut-offs, rather than just one. Additionally, we evaluated alternative options for the 1999 WHO criteria (fasting <126 mg/dl and 2 h 140 mg/dl) [4], considering as GDM also women with impaired fasting glucose (IFG) with cut-off points 100 mg/dl or 110 mg/dl. Finally, for comparison, we also examined the classification of GDM according to the ADA criteria for a 75 g OGTT, which was recommended until 2010: any combination of fasting 95 mg/ dl, 1 h 180 mg/dl and 2 h 155 mg/dl [3]. Relative risks (RR) for outcomes were estimated according to various GDM diagnostic criteria so as to furnish a measure of the prognostic capacity of the criteria, and are thus presented without adjustment for potential confounders. The percent attributable fraction in the population (AFp) was calculated as the difference in the incidence of outcomes between women with and without GDM times the prevalence of GDM, divided by the overall incidence of outcome in the

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Table 1 – Characteristics of the 4926a participants, Brazilian Gestational Diabetes Study. Clinical characteristics Maternal age (years) BMI at the enrolment (kg/m2) Gestational age at delivery (weeks) Ethnicity (%) White Black Mixed Other Education (%) <8 years 8–11 years >11 years Parity (%) 0 1 2 3 Family history of diabetes (%) Cesarean delivery (%) Preeclampsia (%) Birth weight (g) Large for gestational age (%) Small for gestational age (%)

N 4926 4912 4428

Mean (SD) or N (%) 27.8 26.0 38.4

(5.4) (4.0) (2.4)

estimated the sensitivity (Se), specificity (Sp), positive (+PTP) and negative (PTP) post-test probabilities and gains in posttest probability in comparison with pre-test probability (prevalence) of the different diagnostic criteria in terms of detection of outcomes. The statistical software package Statistical Analysis System (version 9.2 SAS Institute, Cary, NC) was used for all analyses.

4925 2206 673 2026 20

(44.8) (13.7) (41.1) (0.4)

2159 2275 482

(43.9) (46.3) (9.8)

1350 1472 829 741 685 1624 149 3201 481 347

(30.7) (33.5) (19.0) (16.8) (14.8) (37.8) (3.0) 570.5 (11.8) (8.5)

4916

4392

4638 4295 4926 4333 4077 4077

a Number of women for each characteristic varies due to missing values.

sample; their 95% confidence intervals were estimated as described by Hildebrandt et al. [16]. The prognostic accuracy of the diagnostic criteria was assessed by the area under the receiver operating characteristic (ROC) curve (AUC). We also

3.

Results

Characteristics of pregnant women enrolled in the EBDG study are presented in Table 1. Means (SD) of plasma glucose for fasting, 1 h and 2 h values were 81.5 (10.6) mg/dl, 121.2 (28.0) mg/dl, 103.2 (22.5) mg/dl, respectively. The distributions of the glucose levels for women who underwent the 75 g OGTT are shown in Fig. 1. Preeclampsia developed in 149 (3.0% of 4926) women, and 481 (11.8% of 4077) delivered LGA newborns. As shown in Table 2, the prevalence of GDM by the IADPSG criteria was 18.0% (95% CI 16.9–19.0%). Applying the more stringent criteria of requiring at least two abnormal values to define GDM, prevalence decreased to only 2.7% (95% CI 2.3– 3.2%), and applying higher plasma glucose cut-offs (see Section 2), to 12.7% (95% CI 11.7–13.6%). GDM prevalence based on just an abnormal fasting value was 15.6% (95% CI 14.6–16.6%), detecting 86% of all women labeled as GDM by the full IADPSG criteria. Similarly, if only the fasting and 1 h samples were considered, the prevalence was 17.0% (95% CI 15.9–18.0%), detecting 94.4% of all GDM cases by the full IADPSG criteria. Considering just the 1 h or just the 2 h sample, or just one of these two samples, produced markedly lower prevalences of GDM. In comparison, the 1999 WHO criteria

Fig. 1 – Distribution of fasting, 1 h and 2 h glucose values for 4926 women who underwent the 75 g oral glucose tolerance test in the Brazilian Study of Gestational Diabetes. Dashed lines indicate the International Association of Diabetes in Pregnancy Study Groups (IADPSG) cut-offs for fasting (92 mg/dl or 5.1 mmol/l), 1 h (180 mg/dl or 10.0 mmol/l) and 2 h (153 mg/dl or 8.5 mmol/l) plasma glucose.

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Table 2 – Resultant prevalence of GDM and additional selected properties of diagnostic criteria in the prediction of adverse pregnancy outcomes. GDM Prevalence

LGA (11.8%) Relative Risk

Preeclampsia (3.0%) AFp

Relative risk

Diagnostic definitions

(%)

(95% CI)

RR

(95% CI)

(%)

(95% CI)

RR

(95% CI)

IADPSG criteriaa More stringent criteriab Alternative cut-offsc IADPSG cut-offs with just Fasting sample Fasting or 1 h samples 1 h sample 2 h sample 1 h or 2 h samples 1999 WHO +IFG  110 mg/dl +IFG  100 mg/dl 2010 ADAd

18.0 2.7 12.7

(16.9–19.0) (2.3–3.2) (11.7–13.6)

1.40 1.62 1.27

(1.15–1.70) (1.08–2.43) (1.01–1.60)

6.7 1.5 3.4

(2.2–11.0) (0.07 to 3.2) (0.04 to 6.9)

1.20 2.90 1.46

(0.8–1.7) (1.6–5.2) (0.9–2.2)

15.6 17.0 3.1 2.7 4.5 7.1 8.0 11.9 2.3

(14.6–16.6) (15.9–18.0) (2.7–3.6) (2.3–3.2) (4.0–5.1) (6.4–7.9) (7.2–8.7) (11.0–12.8) (1.9–2.8)

1.31 1.34 1.86 1.48 1.77 1.67 1.62 1.60 1.50

(1.07–1.62) (1.10–1.64) (1.31–2.65) (0.98–2.25) (1.31–2.39) (1.30–2.15) (1.27–2.06) (1.30–2.00) (0.95–2.34)

4.7 5.4 2.5 1.2 3.3 4.7 4.8 6.9 1.1

(0.8–8.7) (1.3–9.6) (0.6–4.4) (0.3 to 2.9) (1.0–5.6) (1.9–7.6) (1.8–7.8) (3.2–10.5) (0.3 to 2.6)

1.31 1.23 2.00 2.32 1.85 2.26 2.24 1.95 3.30

(0.90–2.00) (0.83–1.83) (1.03–3.83) (1.21–4.44) (1.04–3.30) (1.45–3.51) (1.46–3.42) (1.33–2.90) (1.84–5.94)

AFp (%)

(95% CI)

3.5 4.8 5.4

(4.2 to 11.3) (0.6–9.0) (1.3 to 12.3)

4.6 3.8 3.0 3.4 3.6 8.2 8.9 10.1 5.1

(2.7 to 12.0) (3.7–11.4) (0.8 to 6.8) (0.4 to 7.2) (0.7 to 8.1) (2.2–14.2) (2.6–15.1) (2.9–17.4) (0.9–9.3)

GDM = gestational diabetes mellitus; LGA = large for gestational age; AFp = Attributable fraction in the population. Any one value reaching IADPSG cut-offs (fasting, 1 h or 2 h values during a 2 h 75 g OGTT) [9]. b At least 2 values reaching IADPSG cut-offs (fasting, 1 h or 2 h values during a 2 h 75 g OGTT). c Any one value reaching alternative (higher) cut-offs (fasting, 1 h or 2 h values during a 2 h 75 g OGTT) [9,14]. d At least 2 values reaching fasting, 1 h or 2 h values of 95, 180 and 155 mg/dL, respectively, during a 2 h 75 g OGTT [3]. a

classified 7.1% (95% CI 6.4–7.9%) of women as presenting GDM. This prevalence increased to 8.0% (95% CI 7.2–8.7%) or to 11.9% (95% CI 11.0–12.8%) when also labeling as GDM women with fasting glucose 110 mg/dl or 100 mg/dl, respectively. As also shown in Table 2, women meeting the IADPSG criteria showed only small increments in relative risk of LGA and preeclampsia, the latter not statistically significant (RR = 1.40, 95% CI 1.15–1.70; and RR = 1.20, 95% CI 0.81–1.77, respectively). When the more stringent criteria of at least two abnormal results were required to label GDM, relative risks were larger: 1.62 (95% CI 1.08–2.43) and 2.90 (95% CI 1.61–5.22) for LGA and preeclampsia, respectively. When applying the IADPSG cut-offs only for fasting or fasting/1 h samples, relative risks were similar to those found for the full criteria, but associations were larger for the post load values than for the fasting value. In comparison, relative risks for the 1999 WHO criteria and their modified criteria were of intermediate size, all being statistically significant. The attributable fraction in the population, here expressing the percentage of the outcome observed in the population that was attributable to the diagnosis of GDM by the IADPSG criteria (in other words, additionally detected through use of the criteria), was only 6.7% for LGA and 3.5% for preeclampsia. Table 3 presents the diagnostic performance of the various criteria in terms of their capacity to indicate women with a future adverse pregnancy outcome. Being more inclusive, the IADPSG criteria showed higher sensitivity and lower specificity for such outcomes as compared to most criteria. However, the diagnostic yield, expressed as the increased probability of eventually experiencing an adverse outcome (positive post-test probability minus pre-test probability) were very small – for LGA only 3.6% (15.4–11.8%); for preeclampsia only 0.5% (3.5–3%). Negative post-test probabilities, defined as the probability of suffering an outcome for those not diagnosed as GDM, were minimally altered and were frequently close the values (positive post-test probabilities) for those diagnosed as having GDM.

The three alternative options most approaching the sensitivity seen for the IADPSG criteria were: an abnormal fasting and/or 1 h value (21.6% and 20.1%, for LGA and preeclampsia, respectively), an abnormal fasting value considered alone (19.7% and 19.5%, respectively), and the modified 1999 WHO criteria including IFG (100 mg/dl) (18.3% and 20.8%, respectively). Diagnostic yields of these three criteria were similar, but the modified 1999 WHO criteria (with IFG defined 100 mg/dl) presented the highest attributable fractions for both outcomes. As expected, Tables 2 and 3 indicate that using the IADPSG cut-offs with the more stringent criteria of requiring at least two abnormal results produced findings that were quite similar to those found using the similar approach that had been previously recommended by the ADA for a 75 g OGTT. The generally low prognostic capacity of the various criteria is consistent with the small AUCs for fasting, 1 h and 2 h plasma glucose values in the prediction of both outcomes, with the post load values showing larger AUCs than the fasting value. For LGA, AUCs were 0.553 (95% CI 0.526– 0.581), 0.578 (95% CI 0.551–0.605), and 0.573 (95% CI 0.546–0.600) for fasting, 1 h and 2 h values, respectively ( p = 0.10 for 1 h versus fasting values; p = 0.19 for 2 h versus fasting values), and 0.583 (95% CI 0.556–0.610) when all three values were considered together. For preeclampsia, AUCs were 0.562 (95% CI 0.514–0.610), 0.601 (95% CI 0.553–0.648) and 0.621 (95% CI 0.573–0.669), respectively ( p = 0.16 for 1 h versus fasting values; p = 0.03 for 2 h versus fasting values), and 0.623 (95% CI 0.575–0.669) when all three were considered together. Fig. 2 shows the cross-classification of GDM definitions based on the IADPSG and on the modified 1999 WHO criteria (100 mg/dl cut-off for fasting plasma glucose). Of note, most outcomes occurred among women without GDM. However, given the greater number of women diagnosed with GDM by the IADPSG criteria, more outcomes were seen for this group of women than that meeting the modified 1999 WHO criteria (Fig. 2a and b).

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Table 3 – Diagnostic performance, based on the development of adverse pregnancy outcomes, of the criteria for gestational diabetes proposed by the International Association of Diabetes in Pregnancy Study Groups (IADPSG) and alternative criteria. Gestational diabetes

Pregnancy outcomes

Criteria

IADPSG criteriaa More stringent criteriab Alternative cut-offsc IADPSG cut-offs with only Fasting sample Fasting or 1 h samples 1 h sample 2 h sample 1 h or 2 h samples 1999 WHO +IFG  110 mg/dl +IFG  100 mg/dl 2010 ADAd

LGA (11.8%)

Preeclampsia (3.0%)

Se (%)

Sp (%)

+PTP (%)

Gain (%)

PTP (%)

Gain (%)

Se (%)

Sp (%)

+PTP (%)

Gain (%)

PTP (%)

Gain (%)

23.7 4.2 16.0

82.6 97.6 87.4

15.4 18.9 14.5

3.6 7.1 2.7

11.0 11.6 11.4

0.8 0.2 0.4

20.8 7.4 17.4

82.2 97.5 87.5

3.5 8.3 4.2

0.5 5.3 1.2

3.0 2.9 2.9

0 0.1 0.1

19.7 21.6 5.4 4.0 7.7 11.8 12.7 18.3 3.3

85.0 83.5 97.4 97.5 96.0 93.2 92.3 88.6 97.9

14.8 15.0 21.5 17.3 20.2 18.8 18.1 17.6 17.4

3 3.2 9.7 5.5 8.4 7 7.7 5.8 5.6

11.2 11.1 11.5 11.6 11.4 11.2 11.2 11.0 11.7

0.6 0.7 0.3 0.2 0.4 0.6 0.6 0.8 0.1

19.5 20.1 6.0 6.0 8.0 14.8 16.1 20.8 7.4

84.5 83.2 97.0 97.4 95.6 93.1 92.4 88.4 97.8

3.8 3.6 5.8 6.8 5.4 6.3 6.2 5.3 9.5

0.8 0.6 2.8 3.8 2.4 3.3 3.2 2.3 6.5

2.9 3.0 3.0 3.0 3.0 2.8 2.8 2.7 2.9

0.1 0 0 0 0 0.2 0.2 0.3 0.1

LGA = large for gestational age, Se = sensitivity; Sp = specificity; +PTP = positive post-test probability;–PTP = negative post-test probability, Gain = change from pre- to post-test probability, the pre-test probability being the overall prevalence of the outcome in the sample. a Any one value reaching IADPSG cut-offs (fasting, 1 h or 2 h values during a 2 h 75 g OGTT) [9]. b At least 2 values reaching IADPSG cut-offs (fasting, 1 h or 2 h values during a 2 h 75 g OGTT). c Any one value reaching alternative (higher) cut-offs (fasting, 1 h or 2 h values during a 2 h 75 g OGTT) [9,14]. d At least 2 values reaching fasting, 1 h or 2 h values of 95, 180 and 155 mg/dL, respectively, during a 2 h 75 g OGTT [3].

4.

Discussion

Applying the IADPSG diagnostic criteria as well as alternative definitions to the EBDG cohort of pregnant women allowed evaluation of various diagnostic properties for GDM. Briefly, the IADPSG criteria, while labeling more women as having GDM (greater sensitivity), did not result in larger relative and absolute risks of adverse pregnancy outcomes. The diagnostic impact in terms of the change in pre- to post-test probability of having an adverse outcome and the increased diagnostic yield as expressed by the attributable fraction were generally small for all criteria examined. None of the criteria evaluated stood out as the best. Rather, each presented potential advantages and disadvantages which may be of particular relevance to specific settings. The high prevalence of GDM by the IADPSG criteria (18.0%; 95% CI 16.9–19.0; plus an additional 0.4% of women detected as meeting the diagnostic criteria for diabetes outside of pregnancy) in our sample was similar to that seen in the HAPO study (16.1%; plus 1.7% of those excluded because of elevated glucose levels) [9]. Applying these criteria in lieu of traditional ones will inevitably produce an increase in prevalence, of variable magnitude, depending on the test being used and the population characteristics such as ethnicity and obesity rates [17–21]. The modest relative and absolute risks seen are consistent with findings of a recent systematic review of cohort studies, and a simulation study of the impact of screening for GDM [22,23]. Although the IADPSG criteria showed higher sensitivities when compared to the alternative criteria, percentages were still quite low (23.7% and 20.8% for LGA and preeclampsia, respectively) and did not translate into net gains in terms

of post-test probabilities of adverse outcomes. In fact, as illustrated by Fig. 2, most women who went on to have an adverse event were not diagnosed as having GDM. These findings are in consonance with the large numbers of women needed to be screened using the IADPSG criteria to detect and prevent one adverse pregnancy outcome – 117 for LGA birth and 257 for preeclampsia [23]. These generally poor diagnostic properties for GDM deserve comment. First, pregnancy outcomes were poorly related to plasma glucose levels, as indicated by all of the AUCs analyzed. Second, we excluded women meeting diabetes cutoffs and/or receiving insulin treatment and, as such, the diagnostic performance here described refers to GDM presenting lesser than diabetes hyperglycemia. Though screening in the clinical setting will also detect the more severe cases, resulting measures of performance would be only slightly better as only 0.4% of the women were excluded from EBDG for these reasons. In 2013, a WHO panel recommended the use of IADPSG cutoffs and proposed a screening approach, but the level of this recommendation was graded as weak and the quality of the evidence, as very low [10]. The panel, in a separate article, suggests alternative options for the implementation of the IADPSG cut-offs in different settings, some of these being evaluated here [24]. Those here evaluated did not improve all the metrics examined, but frequently showed specific advantages and disadvantages that may be useful in given settings. For example, when health services cannot reasonably be expected to handle the greater number of GDM cases which would be detected by the IADPSG criteria, a better option might be a criteria leading to a lower prevalence and higher +PTP. In such settings, those with only one abnormal value (the current IADPSG criteria) could be labeled as ‘‘at risk’’ and managed in

diabetes research and clinical practice 108 (2015) 288–295

293

Fig. 2 – Overlap of cases of gestational diabetes (GDM) diagnosed by the International Association of Diabetes in Pregnancy Study Groups (IADPSG) and the modified 1999 World Health Organization (WHO) criteria using the I100 mg/dl cut-off for fasting plasma glucose shown together with (a) cases of large for gestational age (LGA) and (b) cases of preeclampsia.

primary care with lifestyle interventions and limited monitoring; while those with at least two abnormal values (as shown here 2.7% of women, having a +PTP of 18.9% for LGA birth) could be labeled and treated as GDM from that point in their pregnancy onward.

Additionally, when the convenience to pregnant women undergoing the screening is considered to be of relevance to increase the scope of the screening, simplifying the diagnostic testing strategy may be an important consideration. The choice of using fasting or post load values should thus in part

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depend on the practicalities of obtaining each sample and on the relative benefits with regard to each different sample’s potential to predict adverse outcomes. Our results showed that the post load values performed generally better than the fasting values, in part due to the fact that the IADPSG fasting cut-off is less strict than the 1 h and 2 h cut-offs (Fig. 1). Similar findings have been reported by Black et al. [25]. In 2013 the National Institutes of Health Consensus Conference on Diagnosing Gestational Diabetes Mellitus concluded that current evidence was insufficient to permit adoption of the IADPSG as a one-step approach [26]. Our findings provide objective measures which permit evaluation of the pros and cons of the IADPSG criteria vis-a`-vis various alternative options for 1-step 75 g OGTT testing. Some strengths of our current analysis are worth mentioning. The EBDG study was composed of unselected pregnant women, enrolled consecutively from general health services and prospectively followed after a standardized, universally applied 75 g OGTT. It permits the evaluation of untreated pregnant women across the complete spectrum of glucose values below those diagnostic of diabetes outside of pregnancy. As studies evaluating the diagnostic criteria for GDM are hindered by ethical constraints mandating treatments proved to be beneficial, evaluation of diagnostic criteria will greatly depend on results from studies already conducted. Limitations of our analyses also merit comment. As data collection was done in the 1990s, the prevalence of GDM in EBDG, 18% by the IADPSG criteria, is most likely an underestimate for today’s women living in the midst the obesity/diabetes epidemic. However, it is unlikely that this change in prevalence will alter, in relative terms, the associations here described. Nevertheless, an increase in prevalence would raise somewhat attributable fractions and alter slightly post test probabilities. Another potential limitation is that losses to follow-up could bias our results. However, LGA status was ascertained for births to 82% of women who underwent a 2 h 75 g OGTT; preeclampsia, requiring a less lengthy follow-up for ascertainment, was ascertained in almost 100%. Comparison of baseline socioeconomic and clinical data between those lost to follow-up and those analyzed presented only small differences. Additionally, a problem for all studies evaluating GDM screening is the limitation imposed by the outcomes available for analysis. Many relevant outcomes, such as birth trauma and increased hospitalization of neonates, are rare, and thus, for meaningful analysis, require enrollment of numbers of women far beyond those of most of the studies conducted. Other outcomes, such as future maternal diabetes and future obesity or metabolic diseases in offspring, require years of follow-up. In this regard, Werner et al. found that the IADPSG recommendations were cost-effective only when post-delivery counseling and intervention strategies to reduce future diabetes incidence in the mother are considered [27]. Finally, since our study is observational in nature, we did not evaluate the effectiveness of treating GDM defined by the IADPSG and other criteria. A systematic review has summarized relevant effects when treating women diagnosed with the 1999 WHO criteria and older ADA criteria [28], but to the

best of our knowledge, effectiveness has not been evaluated for women diagnosed with the IADPSG criteria. Thus, more studies evaluating the effects of implementing the IADPSG recommendations need to be conducted in different settings, particularly given the growing rates of diabetes and obesity in childbearing age women and the burdens imposed upon patients and health systems in diagnosing and treating GDM [29]. Furthermore, in evaluating effectiveness of screening, potential harms, including overdiagnosis, must be considered. Among these are the potential increase in elective cesarean deliveries and the excessive medicalization of mothers and their offspring. In summary, the IADPSG diagnostic criteria, although labeling a larger number of women as having GDM, provides little diagnostic benefit in terms of the detection of adverse pregnancy outcomes. Alternative criteria did not uniformly improve diagnostic properties, highlighting the difficulties of establishing criteria based on validating abnormal plasma glucose values against pregnancy outcomes. A growing international consensus for the definition of plasma glucose cut offs in pregnancy is desirable. However, diagnostic strategies based on these cut offs will vary across different settings, and require further evaluation.

Conflict of interest The authors report no conflict of interest.

Acknowledgments We are grateful to the women who participated at this study and the members of the Brazilian Gestational Diabetes Study group. The study was supported in part by the Brazilian Ministry of Health, the Pan-American Health Organization (PAHO), Awards for Groups of Excellence (PRONEX No. 661041/19980) of the Brazilian National Council for Technologic and Scientific Development (CNPq), the Foundation for the Support of Research of the State of Rio Grande do Sul (FAPERGS), Bristol-Meyers Squibb Foundation, Becton Dickinson, Bayer of Brasil and Biobra´s. JT received a doctoral fellowship from Capes/CNPq-IEL National – Brazil (No. 013/2008).

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