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

Area of Science:

• Cardiology
• Gerontology
• Preventive Medicine

Background:

• The global aging population necessitates improved risk stratification for primary cardiovascular disease prevention.
• Electrocardiographic (ECG) parameters offer potential for assessing long-term mortality risk in community-dwelling elderly individuals.

Purpose of the Study:

• To develop and validate a combined electrocardiographic abnormality (EA) score for predicting cardiovascular and all-cause mortality in the elderly.
• To assess the long-term prognostic value of ECG parameters in a Taiwanese elderly cohort.

Main Methods:

• A cohort study of 5,380 elderly subjects in Taiwan (December 2008 - April 2019) utilizing serial 12-lead ECGs and health data.
• Cox hazard regression and competing risk survival analysis (Gray's test) were employed to evaluate ECG parameters and the EA score.
• Prognostic models incorporating the EA score were developed and validated using 10-fold cross-validation for calibration and discrimination.

Main Results:

• ECG abnormalities including Left Ventricular Hypertrophy (LVH), prolonged QTc, and PR interval were significantly associated with all-cause death.
• LVH and PR interval were independently linked to cardiovascular death and unexplained death, respectively.
• The developed EA score demonstrated significant predictive capability for all-cause, cardiovascular, and unexplained death, outperforming traditional models.

Conclusions:

• The ECG abnormality (EA) score is a robust predictor of increased mortality risk in the elderly population.
• This novel EA score can be effectively integrated into clinical practice for enhanced cardiovascular risk stratification and primary prevention strategies.
• ECG-based risk models show high efficacy in predicting susceptibility to various death outcomes in older adults.