Predictive value of heart rate variability for major adverse cardiovascular events after percutaneous coronary intervention in patients with acute coronary syndrome: a retrospective cohort study.

BACKGROUND: Acute coronary syndrome (ACS) remains a leading cause of cardiovascular mortality globally. Although percutaneous coronary intervention (PCI) has markedly improved outcomes, the rate of major adverse cardiovascular events (MACE) following PCI remains clinically significant. Heart rate variability (HRV), a noninvasive marker reflecting cardiac autonomic function, may facilitate early risk stratification; however, a systematic evaluation comparing individual time-domain and frequency-domain HRV parameters for predicting MACE after PCI across the full ACS spectrum in the contemporary PCI era is lacking.

METHODS: This retrospective cohort study enrolled 487 consecutive ACS patients who underwent successful PCI at a single tertiary center between January 2019 and December 2023. Twenty-four-hour Holter monitoring was performed within 72 h post-PCI. Time-domain (SDNN, SDANN, rMSSD, pNN50) and frequency-domain (total power, LF, HF, LF/HF ratio) HRV parameters were analyzed. The primary endpoint was 12-month composite MACE. Univariate and multivariable Cox proportional hazards regression (including analyses stratified by beta-blocker use and an extended model adjusting for troponin, NT-proBNP, renal function and revascularization completeness), receiver operating characteristic (ROC) analysis, Kaplan-Meier survival analysis, and incremental predictive value assessment were performed.

RESULTS: During a median follow-up of 11.7 months, 95 patients (19.5%) experienced MACE. The MACE group had significantly lower SDNN (median 85.4 vs. 104.4 ms, P < 0.001). SDNN exhibited the highest area under the curve (AUC) of 0.671, followed by rMSSD (AUC = 0.669). In multivariable Cox regression, SDNN (hazard ratio [HR] = 2.15 per 1-SD decrease, 95% CI: 1.68-2.75, P < 0.001) and rMSSD (HR = 2.18, 95% CI: 1.70-2.80, P < 0.001) were independent predictors of MACE in separate models. The association of SDNN with MACE persisted in the extended model and in both beta-blocker users and non-users (interaction P = 0.55). Adding SDNN to a conventional risk factor model improved discrimination (ΔAUC = 0.026; NRI = 0.179, P = 0.004; IDI = 0.059, P < 0.001).

CONCLUSIONS: SDNN and rMSSD are independent predictors of 12-month MACE in ACS patients following PCI and provide significant incremental prognostic value beyond established clinical risk factors. Because the association between reduced HRV and adverse outcomes is well established, the principal contribution of this contemporary all-ACS cohort is to quantify that association and its added value under current PCI and guideline-directed therapy. Routine HRV assessment may enhance post-PCI risk stratification and guide individualized secondary prevention.