Develop and Apply Electrocardiography-Based Risk Score to Identify Community-Based Elderly Individuals at High-Risk of Mortality

• DOI: 10.3389/fcvm.2021.738061
• Publication Date: 2021-10-10T15:24:39Z
• Authors: Tzu-Pin Lu; Amrita Chattopadhyay; Kuan-Chen Lu; Jing-Yuan Chuang; Shih-Fan Sherri Yeh; I-Shou Chang; Ching-Yu Julius Chen; I-Chien Wu; Chih-Cheng Hsu; Tzu-Yu Chen; Wei-Ting Tseng; Chao Agnes Hsiung; Jyh-Ming Jimmy Juang
• Keywords: Han Chinese population; 03 medical and health sciences; 0302 clinical medicine; RC666-701; prevalence; community-based; Diseases of the circulatory (Cardiovascular) system; long-term prognosis; electrocardiographic abnormality score; Cardiovascular Medicine; 3. Good health

With an aging world population, risk stratification of community-based, elderly population is required for primary prevention. This study proposes a combined score developed using electrocardiographic (ECG) parameters and determines its long-term prognostic value predicting cardiovascular mortality. A cohort-study, conducted from December 2008 to April 2019, enrolled 5,380 subjects in Taiwan, who were examined, three-serial-12-lead ECGs, their health/demographic information recorded. To understand the predictive effects ECG on overall-survival, Cox hazard regression analysis performed. The mean age at enrollment was 69.04 ± 8.14 years, 47.4% males. abnormalities, LVH [hazard ratio (HR) = 1.39, 95% confidence intervals (CI) (1.16-1.67), P 0.0003], QTc [HR 1.31, CI (1.07-1.61), 0.007] PR interval 1.40, (1.01-1.95), 0.04], significantly associated with outcome all-cause death. Furthermore, 2.37, (1.48-3.79), 0.0003] death, while 2.63, (1.24- 5.57), 0.01] unexplained abnormality (EA) defined based number abnormal each patient, which used divide all patients into sub-groups. Competing survival EA performed by Gray's test, reported that high-risk groups showed higher cumulative incidence three outcomes. Prognostic models as predictor 10-fold cross validation design adopted conduct calibration discrimination analysis, establish efficacy proposed models. Overall, model could successfully predict people, susceptible death outcomes (P < 0.05), high efficacy. Statistically significant 0.001) improvement c-indices further demonstrated robustness prediction parameters, opposed traditional no predictor. highly increased mortality may be clinical practice.