Association between estimated pulse wave velocity and mortality risk in patients with acute ischemic stroke

估算脉搏波速度与急性缺血性卒中患者死亡风险之间的关联

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Abstract

Estimated pulse wave velocity (ePWV) has been proposed as a potential predictor of mortality in patients with acute ischemic stroke (AIS). This study aimed to evaluate the relationship between ePWV and all-cause mortality in AIS patients. Among 2,416 AIS patients initially screened, 2176 met the inclusion criteria and were included in the final analysis. ePWV was calculated using a validated formula based on age and mean blood pressure. Patients were stratified into high and low ePWV groups using a cut-off value of 12.33 m/s derived from the ROC curve for 360-day mortality. Cox proportional hazards models, adjusted for clinical and laboratory variables, were used to assess the association between ePWV and mortality at 30, 90, 180, and 360 days. Restricted cubic spline (RCS) analysis was performed to explore potential non-linear associations. Predictive performance was evaluated using area under the ROC curve (AUC), and subgroup analyses were conducted across demographic and clinical strata. Higher ePWV was independently associated with increased mortality at all time points, with adjusted hazard ratios of 1.54 (95% CI 1.26-1.90) at 30 days, 1.58 (1.32-1.89) at 90 days, 1.58 (1.33-1.88) at 180 days, and 1.60 (1.36-1.89) at 360 days (all P < 0.001). Kaplan-Meier analysis showed significantly lower survival in the high ePWV group (P < 0.001). RCS analysis suggested a positive linear relationship between ePWV and mortality. ePWV showed modest discriminative power (AUC 0.62-0.63), outperforming MBP but slightly inferior to age. However, the combination of ePWV with the SOFA score improved prognostic accuracy (AUC up to 0.72), outperforming the age + SOFA model at all time points. Elevated ePWV is independently associated with increased risk of mortality in patients with AIS. As a simple, non-invasive indicator of arterial stiffness, ePWV may serve as a valuable tool for risk stratification and early identification of high-risk patients who may benefit from intensified monitoring and management.

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