• Yi-Hsueh Liu, Wei-Chung Tsai, Nai-Yu Chi, Ching-Tang Chang, Wen-Hsien Lee, Chun-Yuan Chu, Tsung-Hsien Lin, Sheng-Hsiung Sheu, Ho-Ming Su, and Po-Chao Hsu.
• Division of Cardiology, Department of Internal Medicine, Kaohsiung Medical University Hospital, Kaohsiung, Taiwan.
• Int J Med Sci. 2024 Jan 1; 21 (11): 211921262119-2126.

AbstractBackground: Acute myocardial infarction (AMI) is a critical cardiovascular disease with high morbidity and mortality. Identifying practical parameters for predicting long-term mortality is crucial in this patient group. The percentage of mean arterial pressure (%MAP) is a useful parameter used to assess peripheral artery disease. It can be easily calculated from ankle pulse volume recording. Previous studies have shown that %MAP is a useful predictor of all-cause mortality in specific populations, but its relationship with mortality in AMI patients is unclear. Methods: In this observational cohort study, 191 AMI patients were enrolled between November 2003 and September 2004. Ankle-brachial index (ABI) and %MAP were measured using an ABI-form device. All-cause and cardiovascular mortality data were collected from a national registry until December 2018. Cox proportional hazards model and Kaplan-Meier survival plot were used to analyze the association between %MAP and long-term mortality in AMI patients. Results: The median follow-up to mortality was 65 months. There were 130 overall and 36 cardiovascular deaths. High %MAP was associated with increased overall mortality after multivariable analysis (HR = 1.062; 95% CI: 1.017-1.109; p =0.006). However, high % MAP was only associated with cardiovascular mortality in the univariable analysis but became insignificant after the multivariable analysis. Conclusions: In conclusion, this study is the first to evaluate the usefulness of %MAP in predicting long-term mortality in AMI patients. Our study shows that %MAP might be an independent predictor of long-term overall mortality in AMI patients and has better predictive power than ABI.© The author(s).

23 keywords...

hide…