Chen YY, Chung FP, Lin YJ, Chien KL, Chang WT. Exploring the Risk Factors of Sudden Cardiac Death Using an Electrocardiography and Medical Ultrasonography for the General Population Without a History of Coronary Artery Disease or Left Ventricular Ejection Fraction <35% and Aged >35 Years - A Novel Point-Based Prediction Model Based on the Chin-Shan Community Cardiovascular Cohort.
Circ J 2022;
87:139-149. [PMID:
36047166 DOI:
10.1253/circj.cj-22-0322]
[Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/27/2022]
Abstract
BACKGROUND
Most of the factors and prediction models of sudden cardiac death (SCD) have been developed without considering the Asia population. The purpose of this study is to construct a point-based prediction model for the general population in Asia.Methods and Results: Chin-Shan Community Cardiovascular Cohort (CCCC) is a community-based longitudinal cohort initiated between 1990 and 1991, enrolling participants aged ≥35 years and following them up until 2005. Participants with coronary artery disease (CAD) or a left ventricular ejection fraction (LVEF) of 35% were excluded from this study. The Framingham risk score function was used to derive a simple point-based prediction model. Based on bootstrapping, a novel model (CCCC-SCD-Score) was validated. A total of 2,105 participants were analyzed. The incidence rate of SCD was 0.406 per 1,000 person-years. The CCCC-SCD-Score score was calculated using age groups (maximal points=4), left ventricular hypertrophy, hypertension, left ventricular ejection fraction <40%, aortic flow rate >190 cm/s, and carotid plaque scores ≥5 (point=1 for each risk factor). The C-index of the CCCC-SCD-Score in predicting SCD risks was 0.888 (95% confidence interval: 0.807-0.969).
CONCLUSIONS
For the general Asian population without a history of CAD or a LVEF <35% and who are aged >35 years, the novel model-based scoring system effectively identifies the risk for SCD using the clinical factors, electrocardiographic and echocardiographic data.
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