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Screening for Gestational Diabetes: A Systematic Review and Meta-Analysis Gabriela J. Prutsky, Juan Pablo Domecq, Vishnu Sundaresh, Tarig Elraiyah, Mohammed Nabhan, Larry J. Prokop, Adrian Vella, Victor M. Montori, and Mohammad Hassan Murad Knowledge and Evaluation Research Unit (G.J.P., J.P.D., V.S., T.E., M.N., L.J.P., V.M.M., M.H.M.) and Divisions of Endocrinology, Diabetes, Metabolism, and Nutrition (A.V., V.M.M.) and Preventive, Occupational, and Aerospace Medicine (M.H.M.), Mayo Clinic, Rochester, Minnesota 55905; Unidad de Conocimiento y Evidencia (G.J.P., J.P.D., V.M.M.), Universidad Peruana Cayetano Heredia, Lima 31, Peru; Division of Endocrinology and Metabolism (V.S.), Louisiana State University Health Sciences Center, Shreveport, Louisiana 70112; Department of Pediatrics (G.J.P.), Children’s Hospital of Michigan, Wayne State University School of Medicine/Detroit Medical Center, Detroit, Michigan 48201; and Department of Internal Medicine (J.P.D.), Henry Ford Hospital, Detroit, Michigan 48202
Context: Gestational diabetes mellitus (GDM) is defined as any degree of hyperglycemia with first recognition during pregnancy. The optimal time to screen for GDM that would maximize the yield and benefits remains unclear. Objective: Our objective was to appraise the evidence regarding screening for GDM (accuracy, correlation with adverse outcomes, and harms). Data Sources: We searched Ovid Medline, OVID EMBASE, OVID Cochrane Library, Web of Science, Scopus, PsycInfo, and CINAHL through May 2011. Study Selection: We included randomized controlled trials and observational studies that enrolled pregnant woman who were evaluated using different GDM screening tests. Data extraction: Two reviewers working independently abstracted the data. Results: We did not find any randomized controlled trials of GDM screening that measured fetomaternal outcomes. A 1-hour 50-g glucose challenge test with a cutoff point at 140 mg/dL was the most commonly used screening method. The results of this test were statistically associated with feto-maternal outcomes (P ⬍ .001), even though only 11% of individuals with a positive test (according to Carpenter and Coustan criteria) developed GDM. Positive Carpenter and Coustan criteria were associated with macrosomia (odds ratio [OR] ⫽ 2.4, 95% confidence interval [CI] ⫽ 1.9 –3.1, P ⬍ .001) and gestational hypertension (OR ⫽ 1.7, CI ⫽ 1.3–2.1, P ⬍ .001). Positive National Diabetes Data Group criteria were also associated with macrosomia (OR ⫽ 3.2, CI ⫽ 2.3– 4.4, P ⬍ .001) and gestational hypertension (OR ⫽ 2.1, CI ⫽ 1.6 –2.8, P ⬍ .001). Conclusions: Indirect evidence supports the use of contemporary screening tests for GDM to identify pregnancies at increased risk of adverse feto-maternal outcomes. It also suggests that use of these tests will place some women under unnecessary treatment for GDM. (J Clin Endocrinol Metab 98: 4311– 4318, 2013)
ISSN Print 0021-972X ISSN Online 1945-7197 Printed in U.S.A. Copyright © 2013 by The Endocrine Society Received June 6, 2013. Accepted September 10, 2013. First Published Online October 22, 2013
doi: 10.1210/jc.2013-2460
Abbreviations: C&C, Carpenter and Coustan; CI, confidence interval; FBG, fasting blood glucose; GCT, glucose challenge test; GDM, gestational diabetes mellitus; LGA, large for gestational age; NDDG, National Diabetes Data Group; OR, odds ratio; RCT, randomized controlled trial; USPSTF, U.S. Preventive Services Task Force.
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uring pregnancy, hyperplasia of the pancreatic -cells occurs, leading to increased insulin secretion, and an early increase in insulin sensitivity is followed by progressive insulin resistance (1) due to the placental secretion of diabetogenic hormones (2). Gestational diabetes mellitus (GDM), defined as glucose intolerance with onset or first recognition during pregnancy (3), is caused by the inability of pancreatic cells to overcome the insulin resistance created. The prevalence of GDM in the United States is around 4% of pregnancies (4). This prevalence greatly varies based on the risk factors present in the population, such as maternal age and weight (5) among others, but also varies based on the testing method and screening technique. The optimal time to screen and which test to use for GDM remains unclear. The most recent and comprehensive systematic review was commissioned by the U.S. Preventive Services Task Force (USPSTF) in November 2007 (6), it identified minimal data to answer this question. However, since then, a large, well-designed study (the Hyperglycemia and Adverse Pregnancy Outcome Study) demonstrated that maternal hyperglycemia, even to a lesser degree than that observed in diabetes mellitus is associated with increased risks of adverse pregnancy outcomes such as increased birth weight, neonatal hypoglycemia, primary cesarean delivery, and preeclampsia (7). This information makes the screening question more important and compelling. An expert panel from The Endocrine Society was charged with developing clinical practice guidelines to aid patients and clinicians in making decisions regarding screening for GDM. To aid in the development of the Society guidelines, we conducted a systematic review and meta-analysis to appraise and summarize the available evidence regarding screening for GDM.
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Materials and Methods The search and analyses methods, eligibility criteria, and the outcomes of interest were specified in advance in a protocol developed by the study investigators and the expert panel from The Endocrine Society.
Eligibility criteria We included randomized controlled trials (RCTs) and observational studies that enrolled pregnant woman of any age who were screened for GDM.
Search methods An expert reference librarian (L.J.P.) designed and conducted an electronic search strategy (Supplemental Table 6, published on The Endocrine Society’s Journals Online website at http:// jcem.endojournals.org) with input from study investigators with
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expertise in conducting systematic reviews (M.H.M. and V.M.M.). We searched electronic databases to identify relevant studies (Ovid Medline, OVID EMBASE, OVID Cochrane Library, Web of Science, Scopus, PsycInfo, and CINAHL) from November 2007 through May 2011. References published before this date were obtained from Hillier et al (6). To identify additional candidate studies, we reviewed the reference lists of the eligible primary studies, narrative reviews, and systematic reviews; and we queried the expert members of the commissioning task force.
Selection of studies Two reviewers working independently considered the potential eligibility of each of the abstracts and titles that result from executing the search strategy. All the available versions of the eligible studies were reviewed in full-text versions. Agreement for inclusion was measured by inter-reviewer agreement beyond chance (-coefficient).
Data extraction and management Using a standardized, piloted, and web-based data extraction form and working in duplicates, we abstracted the following descriptive data from each study: full description of participants enrolled (principal baseline characteristics such as age, ethnicity, and risk factors), the screening test they received, the outcomes of interest, and the source of funding. The outcomes of interest for this review were 1) screening yield (proportion of women with a positive screening results), 2) sensitivity/specificity of the test, 3) maternal outcomes (maternal mortality, preeclampsia, or gestational hypertension), and 4) fetal outcomes (neonatal mortality, brachial plexus injury, clavicle fracture, admission to a neonatal intensive care unit, neonatal hypoglycemia, neonatal hyperbilirubinemia, respiratory distress syndrome, and macrosomia). Additionally, the population of each study was classified according to the baseline risk for developing GDM as 1 of 3 categories (high, average, and low-risk) (8).
Author contact We planned to contact the authors of original studies by email when data were not available from the published papers or required clarification (with a repeat e-mail in 2 weeks if no response). We were able to contact only one author for successful clarification. After author contact, studies with data insufficient for analysis were excluded.
Assessment of risk of bias in included studies To assess the methodological quality of the included RCTs, we used the Cochrane risk of bias assessment tool to evaluate randomization performance and methods, allocation concealment, baseline imbalances, extent of blinding (patients, caregivers, data collectors, outcome assessors, and data analysts), and rate of loss to follow-up. For the observational studies, we used the Newcastle-Ottawa scale to evaluate how the groups were selected, the comparability between them, whether there was adequate follow-up, and how outcomes/exposures were ascertained.
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Results
Figure 1. Flow chart of selected studies.
Meta-analysis This systematic review included dichotomous outcomes; therefore, we measured the effect size using the odds ratio (OR) and 95% confidence interval (CI). The I2 statistic was used to measure inconsistency in results across and within the studies that was not attributable to chance (9). To pool data across studies, we used the random-effect models because it provides a more reliable estimate of the variance between studies when the number of included studies is small. Analyses were performed using Comprehensive Meta-Analysis (CMA) version 2.2 (Biostat Inc).
Assessment of publication bias We planned to evaluate for publication bias by visually inspecting funnel plots and conducting statistical testing for plot symmetry using the Egger test. However, the assumptions of publication bias testing require a large number (⬎20) of homogeneous studies (10).
Subgroup analysis, meta-regression, and sensitivity analysis We determined a priori hypotheses (limited to a small number to avoid chance findings) to explore subgroup interactions and give a potential explanation for heterogeneity. Subgroup analyses were based on 1) timing of screening in pregnancy, 2) modality of screening, and 3) time of day for glucose tolerance test (morning vs afternoon). We planned to conduct a test of interaction (11) to evaluate the significance of subgroup analyses and potential correlation between subgroups and the pooled effect size. We conducted meta-regression to assess the correlation between the glucose value obtained in the screening test (independent variable) and the development of the outcomes previously mentioned (dependent variable).
Search results and study description A literature search identified 915 articles of which 39 original studies in 42 publications met the eligibility criteria and were included in the systematic review (Figure 1). Disagreement between the reviewers in the full-text screening was minimal (, 0.91). No unpublished relevant studies were identified. Studies enrolled a total of 87 837 pregnant women with a mean age of 30 (range, 13– 41) years. Of the included studies, 2 were RCTs and 37 were cohort studies. The evaluated tests are summarized in supplemental Table 1. Twentythree of the included studies compared the results of their screening test against a test considered by the study authors to be the gold standard. These data were used to evaluate the diagnostic performance measures for the tests. According to the baseline risk, 17 studies included highrisk patients, 16 included patients with average risk, 2 included patients with low risk, and 4 included patients with mixed or unclear risk. Supplemental Table 2 describes the characteristics of included trials. We did not find any additional studies, other than the 3 included in the previous systematic review, evaluating the harms of the screening methods. Risk of bias The 2 included RCTs had adequate randomization methods, preserved randomization by implementing concealed allocation, and had an acceptable proportion of attrition (2.13% and 5.89%). Both were unblinded (blinding patients was unfeasible considering the characteristics of the compared tests), a fact that we considered of low importance because the outcomes of interest were measured objectively and studies did not explicitly report bias caused by co-interventions. Of the 37 observational studies included, 21 were single-cohort studies and the other 16 were controlled-cohort studies. Their quality was quite variable; 19 of them represented well the spectrum of the population of interest for this screening test. All the studies had an adequate follow-up and assessment of outcomes. In the comparative studies, both populations were assessed similarly. Of the 3 studies included for the assessment of harms, 2 were prospective-cohort, and 1 was a cross-sectional
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Table 1.
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Sensitivity and Specificity for 1-Hour 50-g GCT 1-Hour 50-g GCT
Cutoff points No. of studies Sensitivity range, % Specificity range, %
130 4 54 –100 69 –90
140 9 55–98 30 –96
150 3 75–93 26 –96
study. Supplemental Table 3 describes the quality of the included trials. Assessment of publication bias was not possible due to heterogeneity and the small number of studies included per analysis. The included studies did not have published protocols; therefore, assessment for reporting bias was not possible. However; we did not find clear signs of reporting bias in the published version of the studies. Outcomes of interest We did not find any studies that compared the maternal-fetal outcomes of women who received screening vs women who did not receive screening. Yield of the evaluated tests The most commonly used test was a 1-hour 50-g glucose challenge test (GCT) evaluated in 23 of the included studies, and the most commonly used cutoff point was 140 mg/dL. The overall yield for this test at the mentioned cutoff point was 0.181 (95% CI ⫽ 0.178 – 0.183; I2 ⫽ 99.48). As expected, the yield of this test changed according to the risk (interaction test; P ⬍ .05): For low risk the yield was 0.16 (95% CI: 0.153– 0.159, I2: NA), for average risk 0.18 (95% CI: 0.17– 0.18, I2: 98.47) and for high risk 0.24 (95% CI: 0.235– 0.25, I2:99.72). Carpenter and Coustan (C&C) (12) and National Diabetes Data Group (NDDG) criteria (13) were evaluated only in women who had a previous positive 1-hour 50-g GCT; this is why this population was considered as highrisk. The C&C showed a yield of 0.11 (95% CI ⫽ 0.11– 0.12, I2 ⫽ 99.83), and for the NDDG criteria, it was 0.08 (95% CI ⫽ 0.078 – 0.082, I2 ⫽ 99.78). This means that of all women screened, only 8% to 11% will be finally diagnosed with GDM, depending on the diagnosis criteria used. Sensitivity and specificity Sensitivity and specificity were reported in 13 of the studies. It was most commonly reported for the 1-hour 50-g GCT (10 studies) with a cutoff point of 140 mg/dL (9 studies). For this cutoff point, the sensitivity ranged from 55% to 98% and the specificity ranged from 30% to 96%. The results are summarized in Table 1. The diagnostic accuracy for fasting blood glucose (FBG) was more het-
160 4 58 – 82 60 –98
170 3 41–71 76 –97
180 4 35–57 87–91
190 5 21– 46 93–97
200 4 12–38 96 –99
erogeneous across studies (results are summarized in Supplemental Table 4). We did not find any study evaluating the sensitivity or specificity of C&C or NDDG criteria. These criteria are commonly considered as gold standards. Association with outcomes of interest Considering that there were several cutoff points available for the 1-hour 50-g GCT, we decided to conduct meta-regressions to assess the relationship between the value of the screening test and the maternal-fetal outcomes. We found a direct association for the development of neonatal hypoglycemia (slope ⫽ 0.02, 95% CI ⫽ 0.01– 0.03, P ⬍ .001) but not for other fetal-maternal outcomes including large for gestational age (LGA), macrosomia (defined as a birth weight over 4 or 4.5 kg), admission to a neonatal intensive care unit, neonatal hyperbilirubinemia, and preeclampsia (Supplemental Figures 1–7). C&C and NDDG criteria showed a statistically significant correlation between a positive test and the development of macrosomia and gestational hypertension. The diagnosis of GDM according to C&C criteria showed an OR of 2.435 (95% CI ⫽ 1.89 –3.15, P ⬍ .001, I2 ⫽ 85.76%) for the development of macrosomia and OR of 1.66 (95% CI ⫽ 1.32–2.08, P ⬍ .001, I2 ⫽ 85.76%) for gestational hypertension. According to the NDDG criteria, the presence of GDM is associated with an OR of 3.16 (95% CI ⫽ 2.25– 4.42, P ⬍ .001, I2 ⫽ 85.76%) for macrosomia and OR of 2.13 (95% CI ⫽ 1.62–2.79, P ⬍ .001, I2 ⫽ 78.5%) for gestational hypertension; the stronger association can be explained by the higher cutoff point considered by the second test. The association between these two tests and the mentioned outcomes are shown in Table 2. We also evaluated the absolute number of macrosomic babies in women who tested positive according to these criteria and the effect of treatment (Figure 2). As per the previous approach, meta-regression analysis of the relationship between FBG and risk of adverse events was undertaken. We found that as the FBG level increases, the OR for the development of the outcome increases proportionally. This, for the development of LGA (slope ⫽ 0.02, 95% CI ⫽ 0.008 – 0.02, P ⫽ .0001), neonatal hypoglycemia (slope ⫽ 0.02, 95% CI ⫽ 0.008 – 0.004, P ⫽
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Table 2.
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Discussion
C&C and NDDG: Outcomes 95% CI
Outcome C&C Macrosomia Cheng, 2009 (28) Chou, 2010 (29) Overall Gestational hypertension Cheng, 2009 (28) Chou, 2010 (29) Overall NDDG Macrosomia Cheng, 2009 (28) Chou, 2010 (29) Overall Gestational hypertension Cheng, 2009 (28) Chou, 2010 (29) Overall
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OR
Lower Limit
Upper Limit
P
1.335 2.976 2.435
0.800 2.210 1.885
2.230 4.001 3.147
.269 .000 .000
1.575 1.783 1.655
1.175 1.247 1.320
2.111 2.549 2.076
.002 .002 .000
0.629 4.137 3.156
0.258 2.873 2.252
1.532 5.957 4.423
.307 .000 .000
1.657 3.025 2.130
1.164 1.992 1.626
2.359 4.592 2.789
.005 .000 .000
.005), and preeclampsia (slope ⫽ 0.03, 95% CI ⫽ 0.017– 0.04, P ⬍ .0001) (Supplemental Figures 8 –10). We also evaluated the relationship between different cutoff points for the 1- and 2-hour postprandial tests (after a glucose load of 75 g) and the mentioned outcomes (LGA, neonatal hypoglycemia, and preeclampsia). For both tests, a statically significant relationship was found with LGA (1-hour postprandial: slope ⫽ 0.003, 95% CI ⫽ 0.001– 0.005, P ⫽ .002; 2-hour postprandial: slope ⫽ 0.003, 95% CI ⫽ 0.001– 0.006, P ⫽ .004). In both cases, an increase in the glucose level will generate an increased OR but not for preeclampsia or neonatal hypoglycemia (Supplemental Figures 11–16). We did not find any study reporting maternal or neonatal mortality, brachial plexus injury, clavicle fractures, or distress syndrome as outcomes of a screening strategy. Data were reported in the studies as aggregates, making planned subgroup analyses not feasible. Harms associated with screening In terms of harms associated with screening, the 3 included studies evaluated the psychological effect and burden of screening using appropriate scoring systems. The studies used Australasian Diabetes in Pregnancy Society criteria, 4-hour oral glucose tolerance test and 1-hour 50-g GCT followed by a 75-g oral glucose tolerance test, as GDM screening methods. In general, there was no statistically significant difference between women with positive and negative results of screening tests in terms of anxiety, depression, or health perception. These studies and their results are summarized in Supplemental Table 5.
Main findings We conducted a systematic review and meta-analysis to evaluate the different screening tests for GDM in terms of accuracy, correlation with adverse outcomes, and harms. Unfortunately, we did not find any studies that compared the maternal-fetal outcomes of women who received screening compared with women who did not. However, we were able to evaluate other aspects of the available screening tests, specifically the yield of the tests and how it correlates with risk factors and sensitivity and specificity of the tests as well as the association with maternal and fetal outcomes. The 1-hour 50-g GCT with a cutoff point at 140 mg/dL was the most commonly used screening method. It showed a sensitivity of 55% to 98% and a specificity of 30% to 96%. The overall yield of the test was 81%, which increased with a decrease in the cutoff point and increased in parallel to the risk factors for the development of GDM. The positive result of this test showed a significant association only with the development of neonatal hypoglycemia. A positive result using the C&C and NDDG criteria was positively associated with the development of gestational hypertension and macrosomia. NDDG criteria showed a stronger association, which can be explained by the higher threshold of this test. FBG correlated with an increased risk to of develop preeclampsia, LGA, and neonatal hypoglycemia. However, 1-hour postprandial and 2-hour postprandial tests (after a glucose load of 75 g) demonstrated a correlation only with the development of LGA. Comparison with other reviews Our results are consistent to a great extent with systematic reviews commissioned by the USPSTF. One review evaluated benefits and harms of the treatment for GDM (6). Two trials in that review demonstrated that for women diagnosed after 24 weeks, treatment was shown to reduce the risk of macrosomia, preeclampsia, gestational hypertension, and a composite outcome that included stillbirth, neonatal death, shoulder dystocia, bone fractures, and nerve palsy compared with no treatment (14, 15). They did not find major differences between different treatment strategies. Women diagnosed before 24 weeks had a higher rate of preexistent comorbidities and more adverse feto-maternal outcomes. The systematic review included 7 studies evaluating harms with limited data where no major adverse effects were found (6). This review did not evaluate gestational hypertension or macrosomia. In our review, we brought this evidence base up to date and were able to include the Hyperglycemia and Adverse Preg-
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Figure 2. Absolute number of macrosomic babies in women who tested positive according to the 2-step approach (1-hour 50-g GCT and C&C and NDDG criteria) and the effect of treatment.
nancy Outcome Study (16 –19), which was not available during the development of this previous systematic review. The second systematic review commissioned by the USPSTF (20) was a diagnostic systematic review (included only studies that used reference tests and reported sufficient data to calculate sensitivity and specificity). Therefore, it had a somewhat different focus. They also found that a 50-g GCT was most commonly reported using 140 mg/dL as the threshold. The pooled estimates of sensitivity and specificity for this test are consistent with our findings. Limitations and strengths The quality of evidence supporting screening for diabetes in pregnant women is very low. This is because there are no comparative studies of a screening strategy compared with no screening approach. The available evidence is indirect and informed only by studies reporting the diagnostic accuracy of various tests or the expected yield of
different tests. In addition, the definition of gestational screening varied across studies and so did the tests and timing of screening. Clinicians in practice often interpret multiple simultaneous screening tests. Data from primary studies are unavailable to guide interpretation of multiple tests. The strength of this review relates to the comprehensive nature of the literature search and the measures undertaken to reduce the effect of bias and random error: predefined protocol-driven work, duplicate review, and attempts of author contact. Implications for practice and research Unfortunately, we do not have high-quality evidence to determine the best screening strategy for GDM (test and timing). The available literature does not include studies that compared the maternal-fetal outcomes of women who received screening for GDM vs women who did not
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receive screening and measured the impact on outcomes that are important to the patient (21). Such a study design would have been the most informative to the development of screening guidelines. However, conducting studies with this design is challenging considering ethical issues and also considering the common practice of GDM screening in some countries such as the United States. Therefore, clinicians and guideline developers have to use the available evidence and acknowledge its limitations and consider patients’ individual characteristics (ethnicity, comorbidities, etc,) while incorporating their values and preferences and the availability of resources. Clinical factors can help stratify patients’ risk for GMD and guide screening strategies. For example, twin pregnancies are at higher risk of an abnormal screening test and may have different diagnostic accuracy than singleton pregnancies (22). Gaps in the literature are also demonstrated in the lack of available well-conducted cost-benefit assessments, considering the reduction of feto-maternal complications and the possible future development of diabetes, and comparing the available screening strategies in different populations. It is well known that the treatment of GDM decreases possible complications generated by the disease (14, 15, 23) and can be helpful in preventing the future development of type 2 diabetes mellitus (24). This makes it possible to balance the potential adverse effects generated by the tests (anxiety, psychological distress, and future perception of health) (25–27) and potential benefits considering individual risk factors and discussing them with each patient. Conclusions The most commonly evaluated screening test in the literature is 1-hour 50-g GCT, and the most commonly used cutoff point is 140 mg/dL. As expected, the yield of this test directly correlates with the population risk. Only 11% of the patients who had a positive screening test developed GDM according to C&C criteria. FBG strongly correlates with the maternal-fetal outcomes. The available literature does not include studies that compare the maternal-fetal outcomes of women who received screening for GDM vs women who did not receive screening. Such a study design would have been the most informative for the development of screening guidelines.
Acknowledgments Address all correspondence and requests for reprints to: Mohammad Hassan Murad, MD, MPH, Knowledge and Evalua-
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tion Research Unit, Mayo Clinic, 200 First Street SW, Rochester, Minnesota 55905. E-mail: [email protected]. This review was commissioned and funded by a contract from The Endocrine Society. Disclosure Summary: All co-authors have seen and agree with the contents of the review, and there is no financial interest to report. We certify that the submission is original, that the manuscript does not, in whole or in part, infringe any copyright or violate any right of privacy or other personal or property right whatsoever, and that it has not been published in total or in part and is not being submitted or considered for publication in total or in part elsewhere.
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Medical Applications of Research. Ann Intern Med. 2013;159:123– 129. Feig DS, Zinman B, Wang X, Hux JE. Risk of development of diabetes mellitus after diagnosis of gestational diabetes. CMAJ. 2008; 179:229 –234. Rumbold AR, Crowther CA. Women’s experiences of being screened for gestational diabetes mellitus. Aust N Z J Obstet Gynaecol. 2002;42:131–137. Daniells S, Grenyer BF, Davis WS, Coleman KJ, Burgess JA, Moses RG. Gestational diabetes mellitus: is a diagnosis associated with an increase in maternal anxiety and stress in the short and intermediate term? Diabetes Care. 2003;26:385–389. Spirito A, Williams C, Ruggiero L, Bond A, McGarvey ST, Coustan D. Psychological impact of the diagnosis of gestational diabetes. Obstet Gynecol. 1989;73:562–566. Cheng YW, Block-Kurbisch I, Caughey AB. Carpenter-Coustan criteria compared with the national diabetes data group thresholds for gestational diabetes mellitus. Obstet Gynecol. 2009;114(2 Pt 1):326 –332. Chou CY, Lin CL, Yang CK, Yang WC, Lee FK, Tsai MS. Pregnancy outcomes of Taiwanese women with gestational diabetes mellitus: a comparison of Carpenter-Coustan and National Diabetes Data Group criteria. J Womens Health (Larchmt). 2010;19(5):935–939.
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F E A T U R E R e v i e w
Screening for Gestational Diabetes: A Systematic Review and Meta-Analysis Gabriela J. Prutsky, Juan Pablo Domecq, Vishnu Sundaresh, Tarig Elraiyah, Mohammed Nabhan, Larry J. Prokop, Adrian Vella, Victor M. Montori, and Mohammad Hassan Murad Knowledge and Evaluation Research Unit (G.J.P., J.P.D., V.S., T.E., M.N., L.J.P., V.M.M., M.H.M.) and Divisions of Endocrinology, Diabetes, Metabolism, and Nutrition (A.V., V.M.M.) and Preventive, Occupational, and Aerospace Medicine (M.H.M.), Mayo Clinic, Rochester, Minnesota 55905; Unidad de Conocimiento y Evidencia (G.J.P., J.P.D., V.M.M.), Universidad Peruana Cayetano Heredia, Lima 31, Peru; Division of Endocrinology and Metabolism (V.S.), Louisiana State University Health Sciences Center, Shreveport, Louisiana 70112; Department of Pediatrics (G.J.P.), Children’s Hospital of Michigan, Wayne State University School of Medicine/Detroit Medical Center, Detroit, Michigan 48201; and Department of Internal Medicine (J.P.D.), Henry Ford Hospital, Detroit, Michigan 48202
Context: Gestational diabetes mellitus (GDM) is defined as any degree of hyperglycemia with first recognition during pregnancy. The optimal time to screen for GDM that would maximize the yield and benefits remains unclear. Objective: Our objective was to appraise the evidence regarding screening for GDM (accuracy, correlation with adverse outcomes, and harms). Data Sources: We searched Ovid Medline, OVID EMBASE, OVID Cochrane Library, Web of Science, Scopus, PsycInfo, and CINAHL through May 2011. Study Selection: We included randomized controlled trials and observational studies that enrolled pregnant woman who were evaluated using different GDM screening tests. Data extraction: Two reviewers working independently abstracted the data. Results: We did not find any randomized controlled trials of GDM screening that measured fetomaternal outcomes. A 1-hour 50-g glucose challenge test with a cutoff point at 140 mg/dL was the most commonly used screening method. The results of this test were statistically associated with feto-maternal outcomes (P ⬍ .001), even though only 11% of individuals with a positive test (according to Carpenter and Coustan criteria) developed GDM. Positive Carpenter and Coustan criteria were associated with macrosomia (odds ratio [OR] ⫽ 2.4, 95% confidence interval [CI] ⫽ 1.9 –3.1, P ⬍ .001) and gestational hypertension (OR ⫽ 1.7, CI ⫽ 1.3–2.1, P ⬍ .001). Positive National Diabetes Data Group criteria were also associated with macrosomia (OR ⫽ 3.2, CI ⫽ 2.3– 4.4, P ⬍ .001) and gestational hypertension (OR ⫽ 2.1, CI ⫽ 1.6 –2.8, P ⬍ .001). Conclusions: Indirect evidence supports the use of contemporary screening tests for GDM to identify pregnancies at increased risk of adverse feto-maternal outcomes. It also suggests that use of these tests will place some women under unnecessary treatment for GDM. (J Clin Endocrinol Metab 98: 4311– 4318, 2013)
ISSN Print 0021-972X ISSN Online 1945-7197 Printed in U.S.A. Copyright © 2013 by The Endocrine Society Received June 6, 2013. Accepted September 10, 2013. First Published Online October 22, 2013
doi: 10.1210/jc.2013-2460
Abbreviations: C&C, Carpenter and Coustan; CI, confidence interval; FBG, fasting blood glucose; GCT, glucose challenge test; GDM, gestational diabetes mellitus; LGA, large for gestational age; NDDG, National Diabetes Data Group; OR, odds ratio; RCT, randomized controlled trial; USPSTF, U.S. Preventive Services Task Force.
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uring pregnancy, hyperplasia of the pancreatic -cells occurs, leading to increased insulin secretion, and an early increase in insulin sensitivity is followed by progressive insulin resistance (1) due to the placental secretion of diabetogenic hormones (2). Gestational diabetes mellitus (GDM), defined as glucose intolerance with onset or first recognition during pregnancy (3), is caused by the inability of pancreatic cells to overcome the insulin resistance created. The prevalence of GDM in the United States is around 4% of pregnancies (4). This prevalence greatly varies based on the risk factors present in the population, such as maternal age and weight (5) among others, but also varies based on the testing method and screening technique. The optimal time to screen and which test to use for GDM remains unclear. The most recent and comprehensive systematic review was commissioned by the U.S. Preventive Services Task Force (USPSTF) in November 2007 (6), it identified minimal data to answer this question. However, since then, a large, well-designed study (the Hyperglycemia and Adverse Pregnancy Outcome Study) demonstrated that maternal hyperglycemia, even to a lesser degree than that observed in diabetes mellitus is associated with increased risks of adverse pregnancy outcomes such as increased birth weight, neonatal hypoglycemia, primary cesarean delivery, and preeclampsia (7). This information makes the screening question more important and compelling. An expert panel from The Endocrine Society was charged with developing clinical practice guidelines to aid patients and clinicians in making decisions regarding screening for GDM. To aid in the development of the Society guidelines, we conducted a systematic review and meta-analysis to appraise and summarize the available evidence regarding screening for GDM.
D
Materials and Methods The search and analyses methods, eligibility criteria, and the outcomes of interest were specified in advance in a protocol developed by the study investigators and the expert panel from The Endocrine Society.
Eligibility criteria We included randomized controlled trials (RCTs) and observational studies that enrolled pregnant woman of any age who were screened for GDM.
Search methods An expert reference librarian (L.J.P.) designed and conducted an electronic search strategy (Supplemental Table 6, published on The Endocrine Society’s Journals Online website at http:// jcem.endojournals.org) with input from study investigators with
J Clin Endocrinol Metab, November 2013, 98(11):4311– 4318
expertise in conducting systematic reviews (M.H.M. and V.M.M.). We searched electronic databases to identify relevant studies (Ovid Medline, OVID EMBASE, OVID Cochrane Library, Web of Science, Scopus, PsycInfo, and CINAHL) from November 2007 through May 2011. References published before this date were obtained from Hillier et al (6). To identify additional candidate studies, we reviewed the reference lists of the eligible primary studies, narrative reviews, and systematic reviews; and we queried the expert members of the commissioning task force.
Selection of studies Two reviewers working independently considered the potential eligibility of each of the abstracts and titles that result from executing the search strategy. All the available versions of the eligible studies were reviewed in full-text versions. Agreement for inclusion was measured by inter-reviewer agreement beyond chance (-coefficient).
Data extraction and management Using a standardized, piloted, and web-based data extraction form and working in duplicates, we abstracted the following descriptive data from each study: full description of participants enrolled (principal baseline characteristics such as age, ethnicity, and risk factors), the screening test they received, the outcomes of interest, and the source of funding. The outcomes of interest for this review were 1) screening yield (proportion of women with a positive screening results), 2) sensitivity/specificity of the test, 3) maternal outcomes (maternal mortality, preeclampsia, or gestational hypertension), and 4) fetal outcomes (neonatal mortality, brachial plexus injury, clavicle fracture, admission to a neonatal intensive care unit, neonatal hypoglycemia, neonatal hyperbilirubinemia, respiratory distress syndrome, and macrosomia). Additionally, the population of each study was classified according to the baseline risk for developing GDM as 1 of 3 categories (high, average, and low-risk) (8).
Author contact We planned to contact the authors of original studies by email when data were not available from the published papers or required clarification (with a repeat e-mail in 2 weeks if no response). We were able to contact only one author for successful clarification. After author contact, studies with data insufficient for analysis were excluded.
Assessment of risk of bias in included studies To assess the methodological quality of the included RCTs, we used the Cochrane risk of bias assessment tool to evaluate randomization performance and methods, allocation concealment, baseline imbalances, extent of blinding (patients, caregivers, data collectors, outcome assessors, and data analysts), and rate of loss to follow-up. For the observational studies, we used the Newcastle-Ottawa scale to evaluate how the groups were selected, the comparability between them, whether there was adequate follow-up, and how outcomes/exposures were ascertained.
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Results
Figure 1. Flow chart of selected studies.
Meta-analysis This systematic review included dichotomous outcomes; therefore, we measured the effect size using the odds ratio (OR) and 95% confidence interval (CI). The I2 statistic was used to measure inconsistency in results across and within the studies that was not attributable to chance (9). To pool data across studies, we used the random-effect models because it provides a more reliable estimate of the variance between studies when the number of included studies is small. Analyses were performed using Comprehensive Meta-Analysis (CMA) version 2.2 (Biostat Inc).
Assessment of publication bias We planned to evaluate for publication bias by visually inspecting funnel plots and conducting statistical testing for plot symmetry using the Egger test. However, the assumptions of publication bias testing require a large number (⬎20) of homogeneous studies (10).
Subgroup analysis, meta-regression, and sensitivity analysis We determined a priori hypotheses (limited to a small number to avoid chance findings) to explore subgroup interactions and give a potential explanation for heterogeneity. Subgroup analyses were based on 1) timing of screening in pregnancy, 2) modality of screening, and 3) time of day for glucose tolerance test (morning vs afternoon). We planned to conduct a test of interaction (11) to evaluate the significance of subgroup analyses and potential correlation between subgroups and the pooled effect size. We conducted meta-regression to assess the correlation between the glucose value obtained in the screening test (independent variable) and the development of the outcomes previously mentioned (dependent variable).
Search results and study description A literature search identified 915 articles of which 39 original studies in 42 publications met the eligibility criteria and were included in the systematic review (Figure 1). Disagreement between the reviewers in the full-text screening was minimal (, 0.91). No unpublished relevant studies were identified. Studies enrolled a total of 87 837 pregnant women with a mean age of 30 (range, 13– 41) years. Of the included studies, 2 were RCTs and 37 were cohort studies. The evaluated tests are summarized in supplemental Table 1. Twentythree of the included studies compared the results of their screening test against a test considered by the study authors to be the gold standard. These data were used to evaluate the diagnostic performance measures for the tests. According to the baseline risk, 17 studies included highrisk patients, 16 included patients with average risk, 2 included patients with low risk, and 4 included patients with mixed or unclear risk. Supplemental Table 2 describes the characteristics of included trials. We did not find any additional studies, other than the 3 included in the previous systematic review, evaluating the harms of the screening methods. Risk of bias The 2 included RCTs had adequate randomization methods, preserved randomization by implementing concealed allocation, and had an acceptable proportion of attrition (2.13% and 5.89%). Both were unblinded (blinding patients was unfeasible considering the characteristics of the compared tests), a fact that we considered of low importance because the outcomes of interest were measured objectively and studies did not explicitly report bias caused by co-interventions. Of the 37 observational studies included, 21 were single-cohort studies and the other 16 were controlled-cohort studies. Their quality was quite variable; 19 of them represented well the spectrum of the population of interest for this screening test. All the studies had an adequate follow-up and assessment of outcomes. In the comparative studies, both populations were assessed similarly. Of the 3 studies included for the assessment of harms, 2 were prospective-cohort, and 1 was a cross-sectional
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Table 1.
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Sensitivity and Specificity for 1-Hour 50-g GCT 1-Hour 50-g GCT
Cutoff points No. of studies Sensitivity range, % Specificity range, %
130 4 54 –100 69 –90
140 9 55–98 30 –96
150 3 75–93 26 –96
study. Supplemental Table 3 describes the quality of the included trials. Assessment of publication bias was not possible due to heterogeneity and the small number of studies included per analysis. The included studies did not have published protocols; therefore, assessment for reporting bias was not possible. However; we did not find clear signs of reporting bias in the published version of the studies. Outcomes of interest We did not find any studies that compared the maternal-fetal outcomes of women who received screening vs women who did not receive screening. Yield of the evaluated tests The most commonly used test was a 1-hour 50-g glucose challenge test (GCT) evaluated in 23 of the included studies, and the most commonly used cutoff point was 140 mg/dL. The overall yield for this test at the mentioned cutoff point was 0.181 (95% CI ⫽ 0.178 – 0.183; I2 ⫽ 99.48). As expected, the yield of this test changed according to the risk (interaction test; P ⬍ .05): For low risk the yield was 0.16 (95% CI: 0.153– 0.159, I2: NA), for average risk 0.18 (95% CI: 0.17– 0.18, I2: 98.47) and for high risk 0.24 (95% CI: 0.235– 0.25, I2:99.72). Carpenter and Coustan (C&C) (12) and National Diabetes Data Group (NDDG) criteria (13) were evaluated only in women who had a previous positive 1-hour 50-g GCT; this is why this population was considered as highrisk. The C&C showed a yield of 0.11 (95% CI ⫽ 0.11– 0.12, I2 ⫽ 99.83), and for the NDDG criteria, it was 0.08 (95% CI ⫽ 0.078 – 0.082, I2 ⫽ 99.78). This means that of all women screened, only 8% to 11% will be finally diagnosed with GDM, depending on the diagnosis criteria used. Sensitivity and specificity Sensitivity and specificity were reported in 13 of the studies. It was most commonly reported for the 1-hour 50-g GCT (10 studies) with a cutoff point of 140 mg/dL (9 studies). For this cutoff point, the sensitivity ranged from 55% to 98% and the specificity ranged from 30% to 96%. The results are summarized in Table 1. The diagnostic accuracy for fasting blood glucose (FBG) was more het-
160 4 58 – 82 60 –98
170 3 41–71 76 –97
180 4 35–57 87–91
190 5 21– 46 93–97
200 4 12–38 96 –99
erogeneous across studies (results are summarized in Supplemental Table 4). We did not find any study evaluating the sensitivity or specificity of C&C or NDDG criteria. These criteria are commonly considered as gold standards. Association with outcomes of interest Considering that there were several cutoff points available for the 1-hour 50-g GCT, we decided to conduct meta-regressions to assess the relationship between the value of the screening test and the maternal-fetal outcomes. We found a direct association for the development of neonatal hypoglycemia (slope ⫽ 0.02, 95% CI ⫽ 0.01– 0.03, P ⬍ .001) but not for other fetal-maternal outcomes including large for gestational age (LGA), macrosomia (defined as a birth weight over 4 or 4.5 kg), admission to a neonatal intensive care unit, neonatal hyperbilirubinemia, and preeclampsia (Supplemental Figures 1–7). C&C and NDDG criteria showed a statistically significant correlation between a positive test and the development of macrosomia and gestational hypertension. The diagnosis of GDM according to C&C criteria showed an OR of 2.435 (95% CI ⫽ 1.89 –3.15, P ⬍ .001, I2 ⫽ 85.76%) for the development of macrosomia and OR of 1.66 (95% CI ⫽ 1.32–2.08, P ⬍ .001, I2 ⫽ 85.76%) for gestational hypertension. According to the NDDG criteria, the presence of GDM is associated with an OR of 3.16 (95% CI ⫽ 2.25– 4.42, P ⬍ .001, I2 ⫽ 85.76%) for macrosomia and OR of 2.13 (95% CI ⫽ 1.62–2.79, P ⬍ .001, I2 ⫽ 78.5%) for gestational hypertension; the stronger association can be explained by the higher cutoff point considered by the second test. The association between these two tests and the mentioned outcomes are shown in Table 2. We also evaluated the absolute number of macrosomic babies in women who tested positive according to these criteria and the effect of treatment (Figure 2). As per the previous approach, meta-regression analysis of the relationship between FBG and risk of adverse events was undertaken. We found that as the FBG level increases, the OR for the development of the outcome increases proportionally. This, for the development of LGA (slope ⫽ 0.02, 95% CI ⫽ 0.008 – 0.02, P ⫽ .0001), neonatal hypoglycemia (slope ⫽ 0.02, 95% CI ⫽ 0.008 – 0.004, P ⫽
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Table 2.
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Discussion
C&C and NDDG: Outcomes 95% CI
Outcome C&C Macrosomia Cheng, 2009 (28) Chou, 2010 (29) Overall Gestational hypertension Cheng, 2009 (28) Chou, 2010 (29) Overall NDDG Macrosomia Cheng, 2009 (28) Chou, 2010 (29) Overall Gestational hypertension Cheng, 2009 (28) Chou, 2010 (29) Overall
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OR
Lower Limit
Upper Limit
P
1.335 2.976 2.435
0.800 2.210 1.885
2.230 4.001 3.147
.269 .000 .000
1.575 1.783 1.655
1.175 1.247 1.320
2.111 2.549 2.076
.002 .002 .000
0.629 4.137 3.156
0.258 2.873 2.252
1.532 5.957 4.423
.307 .000 .000
1.657 3.025 2.130
1.164 1.992 1.626
2.359 4.592 2.789
.005 .000 .000
.005), and preeclampsia (slope ⫽ 0.03, 95% CI ⫽ 0.017– 0.04, P ⬍ .0001) (Supplemental Figures 8 –10). We also evaluated the relationship between different cutoff points for the 1- and 2-hour postprandial tests (after a glucose load of 75 g) and the mentioned outcomes (LGA, neonatal hypoglycemia, and preeclampsia). For both tests, a statically significant relationship was found with LGA (1-hour postprandial: slope ⫽ 0.003, 95% CI ⫽ 0.001– 0.005, P ⫽ .002; 2-hour postprandial: slope ⫽ 0.003, 95% CI ⫽ 0.001– 0.006, P ⫽ .004). In both cases, an increase in the glucose level will generate an increased OR but not for preeclampsia or neonatal hypoglycemia (Supplemental Figures 11–16). We did not find any study reporting maternal or neonatal mortality, brachial plexus injury, clavicle fractures, or distress syndrome as outcomes of a screening strategy. Data were reported in the studies as aggregates, making planned subgroup analyses not feasible. Harms associated with screening In terms of harms associated with screening, the 3 included studies evaluated the psychological effect and burden of screening using appropriate scoring systems. The studies used Australasian Diabetes in Pregnancy Society criteria, 4-hour oral glucose tolerance test and 1-hour 50-g GCT followed by a 75-g oral glucose tolerance test, as GDM screening methods. In general, there was no statistically significant difference between women with positive and negative results of screening tests in terms of anxiety, depression, or health perception. These studies and their results are summarized in Supplemental Table 5.
Main findings We conducted a systematic review and meta-analysis to evaluate the different screening tests for GDM in terms of accuracy, correlation with adverse outcomes, and harms. Unfortunately, we did not find any studies that compared the maternal-fetal outcomes of women who received screening compared with women who did not. However, we were able to evaluate other aspects of the available screening tests, specifically the yield of the tests and how it correlates with risk factors and sensitivity and specificity of the tests as well as the association with maternal and fetal outcomes. The 1-hour 50-g GCT with a cutoff point at 140 mg/dL was the most commonly used screening method. It showed a sensitivity of 55% to 98% and a specificity of 30% to 96%. The overall yield of the test was 81%, which increased with a decrease in the cutoff point and increased in parallel to the risk factors for the development of GDM. The positive result of this test showed a significant association only with the development of neonatal hypoglycemia. A positive result using the C&C and NDDG criteria was positively associated with the development of gestational hypertension and macrosomia. NDDG criteria showed a stronger association, which can be explained by the higher threshold of this test. FBG correlated with an increased risk to of develop preeclampsia, LGA, and neonatal hypoglycemia. However, 1-hour postprandial and 2-hour postprandial tests (after a glucose load of 75 g) demonstrated a correlation only with the development of LGA. Comparison with other reviews Our results are consistent to a great extent with systematic reviews commissioned by the USPSTF. One review evaluated benefits and harms of the treatment for GDM (6). Two trials in that review demonstrated that for women diagnosed after 24 weeks, treatment was shown to reduce the risk of macrosomia, preeclampsia, gestational hypertension, and a composite outcome that included stillbirth, neonatal death, shoulder dystocia, bone fractures, and nerve palsy compared with no treatment (14, 15). They did not find major differences between different treatment strategies. Women diagnosed before 24 weeks had a higher rate of preexistent comorbidities and more adverse feto-maternal outcomes. The systematic review included 7 studies evaluating harms with limited data where no major adverse effects were found (6). This review did not evaluate gestational hypertension or macrosomia. In our review, we brought this evidence base up to date and were able to include the Hyperglycemia and Adverse Preg-
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Figure 2. Absolute number of macrosomic babies in women who tested positive according to the 2-step approach (1-hour 50-g GCT and C&C and NDDG criteria) and the effect of treatment.
nancy Outcome Study (16 –19), which was not available during the development of this previous systematic review. The second systematic review commissioned by the USPSTF (20) was a diagnostic systematic review (included only studies that used reference tests and reported sufficient data to calculate sensitivity and specificity). Therefore, it had a somewhat different focus. They also found that a 50-g GCT was most commonly reported using 140 mg/dL as the threshold. The pooled estimates of sensitivity and specificity for this test are consistent with our findings. Limitations and strengths The quality of evidence supporting screening for diabetes in pregnant women is very low. This is because there are no comparative studies of a screening strategy compared with no screening approach. The available evidence is indirect and informed only by studies reporting the diagnostic accuracy of various tests or the expected yield of
different tests. In addition, the definition of gestational screening varied across studies and so did the tests and timing of screening. Clinicians in practice often interpret multiple simultaneous screening tests. Data from primary studies are unavailable to guide interpretation of multiple tests. The strength of this review relates to the comprehensive nature of the literature search and the measures undertaken to reduce the effect of bias and random error: predefined protocol-driven work, duplicate review, and attempts of author contact. Implications for practice and research Unfortunately, we do not have high-quality evidence to determine the best screening strategy for GDM (test and timing). The available literature does not include studies that compared the maternal-fetal outcomes of women who received screening for GDM vs women who did not
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receive screening and measured the impact on outcomes that are important to the patient (21). Such a study design would have been the most informative to the development of screening guidelines. However, conducting studies with this design is challenging considering ethical issues and also considering the common practice of GDM screening in some countries such as the United States. Therefore, clinicians and guideline developers have to use the available evidence and acknowledge its limitations and consider patients’ individual characteristics (ethnicity, comorbidities, etc,) while incorporating their values and preferences and the availability of resources. Clinical factors can help stratify patients’ risk for GMD and guide screening strategies. For example, twin pregnancies are at higher risk of an abnormal screening test and may have different diagnostic accuracy than singleton pregnancies (22). Gaps in the literature are also demonstrated in the lack of available well-conducted cost-benefit assessments, considering the reduction of feto-maternal complications and the possible future development of diabetes, and comparing the available screening strategies in different populations. It is well known that the treatment of GDM decreases possible complications generated by the disease (14, 15, 23) and can be helpful in preventing the future development of type 2 diabetes mellitus (24). This makes it possible to balance the potential adverse effects generated by the tests (anxiety, psychological distress, and future perception of health) (25–27) and potential benefits considering individual risk factors and discussing them with each patient. Conclusions The most commonly evaluated screening test in the literature is 1-hour 50-g GCT, and the most commonly used cutoff point is 140 mg/dL. As expected, the yield of this test directly correlates with the population risk. Only 11% of the patients who had a positive screening test developed GDM according to C&C criteria. FBG strongly correlates with the maternal-fetal outcomes. The available literature does not include studies that compare the maternal-fetal outcomes of women who received screening for GDM vs women who did not receive screening. Such a study design would have been the most informative for the development of screening guidelines.
Acknowledgments Address all correspondence and requests for reprints to: Mohammad Hassan Murad, MD, MPH, Knowledge and Evalua-
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tion Research Unit, Mayo Clinic, 200 First Street SW, Rochester, Minnesota 55905. E-mail: [email protected]. This review was commissioned and funded by a contract from The Endocrine Society. Disclosure Summary: All co-authors have seen and agree with the contents of the review, and there is no financial interest to report. We certify that the submission is original, that the manuscript does not, in whole or in part, infringe any copyright or violate any right of privacy or other personal or property right whatsoever, and that it has not been published in total or in part and is not being submitted or considered for publication in total or in part elsewhere.
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