Journal of pediatric endocrinology & metabolism : JPEM · 2013
A risk score for identifying overweight adolescents with dysglycemia in primary care settings.
СтатьяПоддержка NIH: внешняя программаПоддержка исследования: вне правительства СШАНазвание и аннотация: Перевод пока не подготовлен
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Lee Joyce M, Gebremariam Achamyeleh, Woolford Susan J, Tarini Beth A, Valerio Melissa A, Bashir Surair, Eason Ashley J, Choi Preciosa Y, Gurney James G
Аннотация
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.
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.