Development and validation of prediabetes risk score for predicting prediabetes among Indonesian adults in primary care: Cross-sectional diagnostic study

This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium for non-commercial purposes, provided the original author and source are credited.Objective\udTo develop and validate a risk score model for recognizing prediabetes among Indonesian adults in primary care.\ud\udMethods\udThis was a cross-sectional diagnostic study. After excluding subjects with diabetes from Indonesian National Basic Health Survey (INBHS) data set, 21,720 subjects who have completed fasting plasma glucose test and aged >18 years were selected for development stage. About 6,933 subjects were selected randomly from INBHS for validation stage in different diagnostic criteria of prediabetes-based random plasma glucose. Logistic regression was used to determine significant diagnostic variable and the receiver operating characteristic analysis was used to calculate area under the curve (AUC), cutoff point, sensitivity, specificity, and predictive values.\ud\udResults\udAge, sex, education level, family history of diabetes, smoking habit, physical activity, body mass index, and hypertension were significant variables for Indonesian Prediabetes Risk Score (INA-PRISC). The scoring range from 0 to 24, the AUC was 0.623 (95% CI 0.616–0.631) and cutoff point of 12 yielded sensitivity/specificity (50.03%/67.19%, respectively). The validation study showed the AUC was 0.646 (95% CI 0.623–0.669) and cutoff point of 12 yielded sensitivity/specificity (55.11%/65.81%, respectively).\ud\udConclusion\udINA-PRISC, which consists of eight demographical and clinical variables, is a valid and a simple prediabetes risk score in primary care