Abstract
Background
The role of preoperative β-blocker therapy in patients with ventricular dysfunction undergoing coronary artery bypass grafting (CABG) remains unclear.Objective
We aim to evaluate heterogeneous treatment effects of preoperative β-blocker therapy in patients with ventricular dysfunction undergoing CABG and to identify subgroups that may derive greater benefit from preoperative β-blocker therapy than untreated controls.Methods
To investigate the heterogeneous treatment effects of preoperative β-blocker therapy on 30-day mortality in patients with ventricular dysfunction undergoing CABG, we analyzed data on 6,492 patients in the Chinese Cardiac Surgery Registry database between 2017 and 2020. After propensity score matching, we applied a machine-learning iterative causal forest (iCF) algorithm to estimate individualized treatment effects (ITEs) of β-blockers on 30-day all-cause mortality after CABG.Results
The iCF models showed heterogeneity in the effects of preoperative β-blockers on 30-day mortality. Estimated glomerular filtration rate (eGFR), left ventricular end-diastolic diameter (LVEDD) and body mass index (BMI) were identified by the algorithm to distinguish patients with heterogeneous treatment effects. Among patients with eGFR 66 mL/min/1.73 m2 or less, preoperative β-blocker therapy was associated with a significantly lower risk of death from any cause (adjusted odds ratio [aOR], 0.39; 95% CI, 0.22 to 0.67; p = 0.001). No significant benefits were found for other subgroups.Conclusion
Machine learning analysis revealed treatment effect heterogeneity, with preoperative β-blockers demonstrating superior outcomes specifically in CABG patients with ventricular dysfunction and concomitant renal dysfunction (eGFR ≤ 66 mL/min/1.73 m2).