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Author Spotlight: Enhancing Coronary Artery Revascularization
Published on: September 15, 2023
Heterogeneous treatment effects of coronary artery bypass grafting in ischemic cardiomyopathy: A machine learning
Zhuoming Zhou1, Bohao Jian1, Xuanyu Chen2
1Department of Cardiac Surgery, First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China.
Insights
Coronary artery bypass grafting offers survival benefits for younger ischemic cardiomyopathy patients with severe left ventricular enlargement. Machine learning identified specific patient subgroups who benefit most from this procedure over medical therapy alone.
Area of Science:
- Cardiology
- Surgical Interventions
- Medical Therapy
Background:
- Ischemic cardiomyopathy presents complex treatment challenges.
- Coronary artery bypass grafting (CABG) is a potential intervention.
- Identifying optimal candidates for CABG versus medical therapy is crucial.
Purpose of the Study:
- To evaluate heterogeneous treatment effects of CABG in ischemic cardiomyopathy patients.
- To identify patient subgroups benefiting more from CABG compared to medical therapy alone.
Main Methods:
- Utilized machine learning causal forest modeling on data from the Surgical Treatment for Ischemic Heart Failure trial.
- Assessed risks of all-cause and cardiovascular death for CABG versus medical therapy in identified subgroups.
Main Results:
- Left ventricular end-systolic volume index, serum creatinine, and age identified heterogeneous treatment effects.
- Patients with LVESVI > 84 mL/m² and age ≤ 60.27 years showed significantly lower all-cause and cardiovascular death risk with CABG.
- Benefits diminished in patients with LVESVI ≤ 84 mL/m² and serum creatinine ≤ 1.04 mg/dL, or LVESVI > 84 mL/m² and age > 60.27 years.
Conclusions:
- Post hoc analysis of the Surgical Treatment for Ischemic Heart Failure trial revealed heterogeneous treatment effects for CABG in ischemic cardiomyopathy.
- Younger patients with severe left ventricular enlargement are more likely to experience greater survival benefits from CABG.
Objectives:
We aim to evaluate the heterogeneous treatment effects of coronary artery bypass grafting in patients with ischemic cardiomyopathy and to identify a group of patients to have greater benefits from coronary artery bypass grafting compared with medical therapy alone.
Methods:
Machine learning causal forest modeling was performed to identify the heterogeneous treatment effects of coronary artery bypass grafting in patients with ischemic cardiomyopathy from the Surgical Treatment for Ischemic Heart Failure trial. The risks of death from any cause and death from cardiovascular causes between coronary artery bypass grafting and medical therapy alone were assessed in the identified subgroups.
Results:
Among 1212 patients enrolled in the Surgical Treatment for Ischemic Heart Failure trial, left ventricular end-systolic volume index, serum creatinine, and age were identified by the machine learning algorithm to distinguish patients with heterogeneous treatment effects. Among patients with left ventricular end-systolic volume index greater than 84 mL/m2 and age 60.27 years or less, coronary artery bypass grafting was associated with a significantly lower risk of death from any cause (adjusted hazard ratio, 0.61; 95% CI, 0.45-0.84) and death from cardiovascular causes (adjusted hazard ratio, 0.63; 95% CI, 0.45-0.89). By contrast, the survival benefits of coronary artery bypass grafting no longer exist in patients with left ventricular end-systolic volume index 84 mL/m2 or less and serum creatinine 1.04 mg/dL or less, or patients with left ventricular end-systolic volume index greater than 84 mL/m2 and age more than 60.27 years.
Conclusions:
The current post hoc analysis of the Surgical Treatment for Ischemic Heart Failure trial identified heterogeneous treatment effects of coronary artery bypass grafting in patients with ischemic cardiomyopathy. Younger patients with severe left ventricular enlargement were more likely to derive greater survival benefits from coronary artery bypass grafting.
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