Journal of Pediatric Endocrinology and Metabolism
Editor-in-Chief: Kiess, Wieland
Ed. by Bereket, Abdullah / Cohen, Pinhas / Darendeliler, Feyza / Dattani, Mehul / Gustafsson, Jan / Luo, Feihong / Mericq, Veronica / Roth, Christian / Toppari, Jorma
Editorial Board Member: Battelino, Tadej / Buyukgebiz, Atilla / Cassorla, Fernando / Chrousos, George P. / Cutfield, Wayne / Fideleff, Hugo L. / Hershkovitz, Eli / Hiort, Olaf / LaFranchi, Stephen H. / Lanes M. D., Roberto / Mohn, Angelika / Root, Allen W. / Rosenfeld, Ron G. / Werther, George / Zadik, Zvi
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A risk score for identifying overweight adolescents with dysglycemia in primary care settings1)
1Division of Pediatric Endocrinology, University of Michigan, Ann Arbor, MI
2Child Health Evaluation and Research (CHEAR) Unit, Division of General Pediatrics, University of Michigan, Ann Arbor, MI
3Department of Health Behavior and Health Education, University of Michigan School of Public Health, Ann Arbor, MI
4Department of Epidemiology and Cancer Control, St. Jude Children’s Research Hospital, Memphis, TN
5Pediatric Endocrinology and Health Services Research, Child Health Evaluation and Research (CHEAR) Unit, University of Michigan, 300 NIB, Room 6E18, Campus Box 5456, Ann Arbor, 48109-5456 MI
Citation Information: Journal of Pediatric Endocrinology and Metabolism. Volume 26, Issue 5-6, Pages 477–488, ISSN (Online) 2191-0251, ISSN (Print) 0334-018X, DOI: 10.1515/jpem-2012-0259, February 2013
- Published Online:
Objective: To develop a clinical risk scoring system for identifying adolescents with dysglycemia (prediabetes or diabetes) who need further confirmatory testing and to determine whether the addition of non-fasting tests would improve the prediction of dysglycemia.
Study Design: A sample of 176 overweight and obese adolescents (10–17 years) had a history/physical exam, a 2-h oral glucose tolerance test, and non-fasting tests [hemoglobin A1c, 1-h glucose challenge test (GCT), and random glucose test] performed. Given the low number of children with diabetes, we created several risk scoring systems combining the clinical characteristics with non-fasting tests for identifying adolescents with dysglycemia and compared the test performance.
Results: Sixty percent of participants were white and 32% were black; 39.2% had prediabetes and 1.1% had diabetes. A basic model including demographics, body mass index percentile, family history of diabetes, and acanthosis nigricans had reasonable test performance [area under the curve (AUC), 0.75; 95% confidence interval (95% CI), 0.68–0.82]. The addition of random glucose (AUC, 0.81; 95% CI, 0.75–0.87) or 1-h GCT (AUC, 0.82; 95% CI, 0.75–0.88) to the basic model significantly improved the predictive capacity, but the addition of hemoglobin A1c did not (AUC, 0.76; 95% CI, 0.68–0.83). The clinical score thresholds to consider for the basic plus random glucose model are total score cutoffs of 60 or 65 (sensitivity 86% and 65% and specificity 60% and 78%, respectively) and for the basic plus 1-h GCT model are total score cutoffs of 50 or 55 (sensitivity 87% and 73% and specificity 59% and 76%, respectively).
Conclusions: Pending a validation in additional populations, a risk score combining the clinical characteristics with non-fasting test results may be a useful tool for identifying children with dysglycemia in the primary care setting.