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Risk factor and prediction modeling for sudden cardiac death in women with coronary artery disease
Rajat Deo1, Eric Vittinghoff, Feng Lin
1Section of Electrophysiology, Division of Cardiovascular Medicine, University of Pennsylvania, 3400 Spruce Street, Philadelphia, PA 19104, USA. Rajat.Deo@uphs.upenn.edu
Insights
Sudden cardiac death (SCD) is a major concern for women with coronary artery disease (CAD). Key risk factors like heart failure and diabetes significantly increase SCD risk, improving prediction when combined with LVEF.
Area of Science:
- Cardiology
- Women's Health
- Public Health
Background:
- Sudden cardiac death (SCD) risk and prediction models are understudied in women with coronary artery disease (CAD).
- This study addresses the incidence of SCD and its risk factors in this population.
Purpose of the Study:
- To evaluate the incidence of SCD in postmenopausal women with CAD.
- To identify independent risk factors for SCD.
- To assess the predictive accuracy of these risk factors, alone and with left ventricular ejection fraction (LVEF).
Main Methods:
- Analysis of 2763 postmenopausal women with CAD from the Heart and Estrogen/progestin Replacement Study.
- Cox proportional hazards models to identify SCD predictors.
- C-index and net reclassification improvement to compare predictive models.
Main Results:
- SCD accounted for 136 of 254 cardiac deaths, with an annual incidence of 0.79%.
- Independent predictors of SCD included myocardial infarction, heart failure, low estimated glomerular filtration rate, atrial fibrillation, physical inactivity, and diabetes.
- Combining clinical risk factors with LVEF improved SCD prediction (C-index 0.681) compared to LVEF alone (C-index 0.600).
Conclusions:
- SCD is the predominant cause of cardiac death in postmenopausal women with CAD.
- Identified risk factors significantly enhance SCD prediction beyond LVEF alone.
- These findings are crucial for risk stratification and targeted interventions in women with CAD.
Background:
To our knowledge, the risk of sudden cardiac death (SCD) and the assessment of risk factors in prediction models have not been evaluated in women with coronary artery disease (CAD). We sought to evaluate the incidence of SCD as well as its risk factors and their predictive accuracy among a population of women with CAD.
Methods:
The Heart and Estrogen/progestin Replacement Study evaluated the effects of hormone replacement therapy on cardiovascular events among 2763 postmenopausal women with CAD. Sudden cardiac death was defined as death resulting from a cardiac origin that occurred within 1 hour of symptom onset. The associations between candidate predictor variables and SCD were evaluated in a Cox proportional hazards model. The C-index was used to compare the predictive value of the clinical risk factors with left ventricular ejection fraction (LVEF) alone and in combination. The net reclassification improvement was also computed.
Results:
Over a mean follow-up of 6.8 years, SCD comprised 136 of the 254 cardiac deaths. The annual SCD event rate was 0.79% (95% confidence interval, 0.67-0.94). The following variables were independently associated with SCD in the multivariate model: myocardial infarction, heart failure, an estimated glomerular filtration rate of less than 40 mL/min/1.73 m(2), atrial fibrillation, physical inactivity, and diabetes. The incidences of SCD among women with 0 (n = 683), 1 (n = 1224), 2 (n = 610), and 3 plus (n = 246) risk factors at baseline were 0.3%, 0.5%, 1.2%, and 2.9% per year, respectively. The combination of clinical risk factors and LVEF (C-index, 0.681) were better predictors of SCD than LVEF alone (C-index, 0.600) and resulted in a net reclassification improvement of 0.20 (P < .001).
Conclusions:
Sudden cardiac death comprised the majority of cardiac deaths among postmenopausal women with CAD. Independent predictors of SCD, including myocardial infarction, congestive heart failure, an estimated glomerular filtration rate of less than 40 mL/min/1.73 m(2), atrial fibrillation, physical inactivity, and diabetes, improved SCD prediction when they were considered in addition to LVEF.
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