| Literature DB >> 28450368 |
Pamela Ghosh1, Miguel A Luque-Fernandez2,3, Anand Vaidya4, Dongdong Ma1, Rupam Sahoo1, Michael Chorev1, Chloe Zera5, Thomas F McElrath5, Michelle A Williams3, Ellen W Seely4, Jose A Halperin6.
Abstract
OBJECTIVE: Plasma glycated CD59 (pGCD59) is an emerging biomarker in diabetes. We assessed whether pGCD59 could predict the following: the results of the glucose challenge test (GCT) for screening of gestational diabetes mellitus (GDM) (primary analysis); and the diagnosis of GDM and prevalence of large for gestational age (LGA) newborns (secondary analyses). RESEARCH DESIGN AND METHODS: Case-control study of 1,000 plasma samples from women receiving standard prenatal care, 500 women having a normal GCT (control subjects) and 500 women with a failed GCT and a subsequent oral glucose tolerance test (case patients).Entities:
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Year: 2017 PMID: 28450368 PMCID: PMC5481979 DOI: 10.2337/dc16-2598
Source DB: PubMed Journal: Diabetes Care ISSN: 0149-5992 Impact factor: 19.112
Figure 1A and B: pGCD59 probability density functions by case-control status and between control subjects vs. GDM. Glucose challenge tests were adjudicated using American Congress of Obstetricians and Gynecologists guidelines: failed 50-g GCT, ≥140 mg/dL; 100-g, 3-h OGTT: no GDM, zero or one abnormal glucose value; GDM, two or more abnormal glucose values based on C&C criteria. A: Control subjects vs. case patients. B: Control subjects vs. GDM patients. The red dotted lines indicate the median pGCD59 values for the respective groups; the difference in median values between two groups and 95% CIs are mentioned in the figure (n = 1,000). C and D: ROC curve AUCs by case-control status and control subjects vs. GDM patients. C: Control subjects vs. case patients. D: Control subjects vs. GDM patients. Marginal and conditional ROC curves were computed and adjusted for maternal age, BMI, race/ethnicity, multiplicity, and gestational age at GCD59 determination and history of diabetes. AUROCs were derived using the DeLong et al. (20) nonparametric tied corrected estimator, and the percentile values of the case patient observations with respect to the control distribution were used to derive the tied corrected estimator (20). Under nonparametric estimation, SEs and derived AUROCs and 95% CIs were estimated using cross-validation and bootstrapping procedures with 1,000 replications. Dashed lines, ROC curves adjusted for maternal age, race/ethnicity, BMI, gestation week at pGCD59 determination, and a history of diabetes (n = 1,000); insets, adjusted AUC, sensitivity, and specificity with 95% CI; solid lines, unadjusted ROC curves.