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

Isti Ilmiati Fujiati, Harun Alrasyid Damanik, Adang Bachtiar, Andi Armyn Nurdin, Paul Ward

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

Objective: To develop and validate a risk score model for recognizing prediabetes among Indonesian adults in primary care. Methods: This 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. Results: Age, 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). Conclusion: INA-PRISC, which consists of eight demographical and clinical variables, is a valid and a simple prediabetes risk score in primary care.

Original languageEnglish
Pages (from-to)76-85
Number of pages10
JournalInterventional Medicine and Applied Science
Volume9
Issue number2
DOIs
Publication statusPublished - 1 Jun 2017

Keywords

  • Development
  • Prediabetes
  • Primary care
  • Risk score model
  • Validation

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