Combining Pulse Wave Velocity With Galectin-3 to Predict Mortality and Cerebrovascular and Cardiovascular Events in Hemodialysis Patients.

将脉搏波速度与半乳糖凝集素-3 相结合,预测血液透析患者的死亡率、脑血管事件和心血管事件

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作者:Zhang Qi, Yin Kanhua, Zhu Mingli, Lin Xinghui, Fang Yan, Lu Jiayue, Li Zhenyuan, Ni Zhaohui
Background: Cerebrovascular and cardiovascular diseases contribute substantially to the mortality of end-stage renal disease patients. We sought to combine pulse wave velocity (PWV) with galectin-3 to predict the mortality and cerebrovascular and cardiovascular events in hemodialysis patients. Methods and Results: End-stage renal disease patients who underwent stable hemodialysis were screened for inclusion. Patients with preexisting cardiovascular and cerebrovascular diseases were excluded. The primary endpoint was a composite of all-cause mortality and major adverse cerebrovascular and cardiovascular events. Receiver operating characteristic curve analysis was used to determine the optimal cutoffs to dichotomize PWV and galectin-3. The study population was then stratified into four groups based on these cutoffs. Both univariable and multivariable Cox regression analyses were performed to estimate the hazard ratio and 95% confidence interval (CI) for clinical factors. Model performance was compared among models with or without PWV and galectin-3. A total of 284 patients were enrolled. During a median follow-up of 31 months, 57 patients (20.1%) reached the primary endpoint. The optimal cutoffs for PWV and galectin-3 were 7.9 m/s and 30.5 ng/ml, respectively. In the multivariable regression analysis, the high PWV-high galectin-3 group was associated with a 3-fold increased risk of all-cause mortality and major adverse cerebrovascular and cardiovascular events (hazard ratio = 3.19, 95% CI: 1.05-9.66, p = 0.04) compared with the low PWV-low galectin-3 group. The combination of PWV and galectin-3 was associated with improved model discrimination, calibration, and reclassification. Conclusions: The combination of PWV and galectin-3 can be used to predict mortality and cerebral and cardiovascular complications in hemodialysis patients.

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