The predicting value of resting heart rate to identify undiagnosed diabetes in Korean adult: Korea National Health and Nutrition Examination Survey

Abstract

Objectives: The purpose of the current study is to examine 1) whether the addition of resting heart rate (RHR) to existing undiagnosed diabetes (UnDM) prediction model would improve predictability, 2) to develop and validate UnDM prediction model by only using easily assessable variables such as age, gender, RHR and waist circumference (WC).

Methods: Korea National Health and Nutrition Examination Survey (KNHANES) 2010, 2012, 2014, 2016 data were used to develop the model (model building set, N=19,675) and KNHANES data from 2011, 2013, 2015, 2017 were used to validate the model (validation set, N=19,917). UnDM was defined as a fasting glucose level ≥ 126mg/dL or hemoglobin A1c ≥6.5%, yet has not been diagnosed by doctors. SPSS logistic regression analysis was used to determine predictors of UnDM.

Results: Age, RHR, waist circumference (WC) were associated with UnDM. When RHR was added to the existing model, sensitivity was reduced (86% vs. 73%) while specificity was increased (49% vs. 65%), expressed as higher Youden index (35 vs. 38). When only age, sex, WC and RHR were used in the model, sensitivity of 70%, and specificity of 67% with Youden index of 37 were observed.

Conclusion: Adding RHR to existing UnDM prediction model improved specificity and Youden index. Furthermore, prediction model only used age, sex, RHR and WC were not inferior to existing prediction model.