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Sudden cardiac death after myocardial infarction: individual participant data from pooled cohorts
Niels Peek1,2, Gerhard Hindricks3,4, Artur Akbarov1
1Division of Informatics, Imaging and Data Science, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK.
Insights
Risk stratification for sudden cardiac death after myocardial infarction using left ventricular ejection fraction (LVEF) is unreliable. Current methods, including LVEF and other predictors, cannot accurately identify high- or low-risk patients for defibrillator therapy.
Area of Science:
- Cardiology
- Preventive Medicine
- Medical Imaging
Background:
- Sudden cardiac death (SCD) risk stratification post-myocardial infarction (MI) often relies on left ventricular ejection fraction (LVEF).
- Accurate risk assessment across the entire LVEF spectrum is crucial for guiding defibrillator implantation decisions.
- Existing methods may not adequately identify individuals who would benefit from or be harmed by defibrillator therapy.
Purpose of the Study:
- To evaluate the predictive performance of LVEF and other clinical parameters for SCD risk stratification in post-MI patients.
- To determine if multivariable models can improve risk prediction compared to LVEF alone.
- To assess the generalizability of risk prediction models across different patient subgroups.
Main Methods:
- Pooled analysis of 20 datasets comprising 140,204 post-MI patients.
- Separate analyses for implantable cardioverter-defibrillator (ICD) patients (LVEF ≤ 35%), non-ICD patients (LVEF ≤ 35%), and non-ICD patients (LVEF > 35%).
- Development and external validation of LVEF-only, parametric survival, and random forest survival models; performance assessed via meta-analysis.
Main Results:
- LVEF demonstrated poor predictive ability for SCD in all analyzed subgroups (c-statistics 0.50–0.56).
- Inclusion of additional clinical parameters did not enhance model calibration, discrimination, or generalizability.
- Significant numbers of primary outcomes (SCD or appropriate defibrillator therapy) were observed across all patient groups.
Conclusions:
- Accurate risk stratification for SCD in post-MI patients remains challenging, even with comprehensive data.
- Neither LVEF alone nor multivariable models incorporating other predictors reliably identify low-risk individuals with reduced LVEF or high-risk individuals with preserved LVEF.
- Current risk stratification tools are insufficient for optimizing defibrillator implantation decisions across the full LVEF range.
Background And Aims:
Risk stratification of sudden cardiac death after myocardial infarction and prevention by defibrillator rely on left ventricular ejection fraction (LVEF). Improved risk stratification across the whole LVEF range is required for decision-making on defibrillator implantation.
Methods:
The analysis pooled 20 data sets with 140 204 post-myocardial infarction patients containing information on demographics, medical history, clinical characteristics, biomarkers, electrocardiography, echocardiography, and cardiac magnetic resonance imaging. Separate analyses were performed in patients (i) carrying a primary prevention cardioverter-defibrillator with LVEF ≤ 35% [implantable cardioverter-defibrillator (ICD) patients], (ii) without cardioverter-defibrillator with LVEF ≤ 35% (non-ICD patients ≤ 35%), and (iii) without cardioverter-defibrillator with LVEF > 35% (non-ICD patients >35%). Primary outcome was sudden cardiac death or, in defibrillator carriers, appropriate defibrillator therapy. Using a competing risk framework and systematic internal-external cross-validation, a model using LVEF only, a multivariable flexible parametric survival model, and a multivariable random forest survival model were developed and externally validated. Predictive performance was assessed by random effect meta-analysis.
Results:
There were 1326 primary outcomes in 7543 ICD patients, 1193 in 25 058 non-ICD patients ≤35%, and 1567 in 107 603 non-ICD patients >35% during mean follow-up of 30.0, 46.5, and 57.6 months, respectively. In these three subgroups, LVEF poorly predicted sudden cardiac death (c-statistics between 0.50 and 0.56). Considering additional parameters did not improve calibration and discrimination, and model generalizability was poor.
Conclusions:
More accurate risk stratification for sudden cardiac death and identification of low-risk individuals with severely reduced LVEF or of high-risk individuals with preserved LVEF was not feasible, neither using LVEF nor using other predictors.
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