five

Data_Sheet_1_Cardio-Ankle Vascular Index Reflects Impaired Exercise Capacity and Predicts Adverse Prognosis in Patients With Heart Failure.docx

收藏
NIAID Data Ecosystem2026-03-12 收录
下载链接:
https://figshare.com/articles/dataset/Data_Sheet_1_Cardio-Ankle_Vascular_Index_Reflects_Impaired_Exercise_Capacity_and_Predicts_Adverse_Prognosis_in_Patients_With_Heart_Failure_docx/14332352
下载链接
链接失效反馈
官方服务:
资源简介:
Aims: We aimed to assess the associations of CAVI with exercise capacity in heart failure (HF) patients. In addition, we further examined their prognosis. Methods: We collected the clinical data of 223 patients who had been hospitalized for decompensated HF and had undergone both CAVI and cardiopulmonary exercise testing. Results: For the prediction of an impaired peak oxygen uptake (VO2) of < 14 mL/kg/min, receiver-operating characteristic curve demonstrated that the cutoff value of CAVI was 8.9. In the multivariate logistic regression analysis for predicting impaired peak VO2, high CAVI was found to be an independent factor (odds ratio 2.343, P = 0.045). We divided these patients based on CAVI: the low-CAVI group (CAVI < 8.9, n = 145) and the high-CAVI group (CAVI ≥ 8.9, n = 78). Patient characteristics and post-discharge cardiac events were compared between the two groups. The high-CAVI group was older (69.0 vs. 58.0 years old, P < 0.001) and had lower body mass index (23.0 vs. 24.1 kg/m2, P = 0.013). During the post-discharge follow-up period of median 1,623 days, 58 cardiac events occurred. The Kaplan–Meier analysis demonstrated that the cardiac event rate was higher in the high-CAVI group than in the low-CAVI group (log–rank P = 0.004). The multivariate Cox proportional hazard analysis revealed that high CAVI was an independent predictor of cardiac events (hazard ratio 1.845, P = 0.035). Conclusion: High CAVI is independently associated with impaired exercise capacity and a high cardiac event rate in HF patients.
创建时间:
2021-03-29
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作