Joint blood pressure and resting heart rate trajectories and net adverse clinical events risk following PCI: an inverse probability of treatment weighting analysis

Vollständiger Abstract

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Background Evidence is limited on the prospective prognostic value of longitudinal blood pressure (BP) and resting heart rate (RHR) dynamics after percutaneous coronary intervention (PCI). Aim This study aimed to identify joint BP-RHR trajectories and evaluate their impact on net adverse clinical events (NACE). Methods In a prospective post-PCI cohort, latent class trajectory modeling identified 6-month patterns of systolic BP, diastolic BP, and RHR, classifying patients into four joint trajectories. Inverse probability of treatment weighting (IPTW) was employed to rigorously balance baseline confounders. The primary endpoint was NACE. The incremental predictive value of the joint trajectories was assessed using the C-index, continuous net reclassification improvement (cNRI), and integrated discrimination improvement (IDI). Results Among 736 patients (71 NACE events during follow-up), four distinct joint trajectory groups were identified: Double Stable ( n = 329), BP-Fluctuating ( n = 215), RHR-Fluctuating ( n = 108), and Double Fluctuating ( n = 84). After IPTW adjustment, compared with the Double Stable group, the risk of NACE was significantly elevated in the BP-Fluctuating group (HR: 2.21, 95% CI: 1.23–3.97), the RHR-Fluctuating group (HR: 1.85, 95% CI: 1.09–3.13), and peaked in the Double Fluctuating group (HR: 2.69, 95% CI: 1.18–6.14). Furthermore, incorporating the joint trajectory groups into a baseline clinical risk model significantly improved prognostic discrimination and reclassification, with significant increases in the C-index ( p < 0.001), IDI improvement ( p = 0.033), and continuous net reclassification improvement. Conclusion Joint BP and RHR trajectories effectively stratify post-PCI NACE risk. Patients with combined fluctuations face the highest risk, highlighting the need for dynamic hemodynamic monitoring over static single-point assessments.