主动脉夹层
医学
观察研究
回顾性队列研究
肌萎缩
外科
解剖(医学)
普通外科
内科学
主动脉
作者
Joon-Suk Bom,Hong‐Beom Bae,Joungmin Kim
出处
期刊:Medical Biological Science and Engineering
[The Institute of Medical Science, Chosun University]
日期:2025-07-28
卷期号:8 (2): 72-81
被引量:1
标识
DOI:10.30579/mbse.2025.8.2.72
摘要
Acute type A aortic dissection (AAAD) is a life-threatening condition requiring immediate surgical intervention, and despite advances in perioperative care, postoperative mortality remains a major concern.Sarcopenia, characterized by reduced muscle mass and function, has emerged as a prognostic factor in various surgical populations.This retrospective single-center study assessed the prognostic impact of sarcopenia on postoperative outcomes in patients who underwent surgery for AAAD at Chonnam National University Hospital between January 2021 and December 2023.Sarcopenia was defined using total psoas area derived from preoperative computed tomography scans, with automated segmentation performed using the pre-trained Segment Anything Model 2 (SAM2) optimized for psoas detection.A total of 83 patients were included, of whom 31 (37.3%) were classified as having sarcopenia.The primary outcome was all-cause mortality, further classified into early mortality (within 30 days, including in-hospital deaths occurring after 30 days) and late mortality (beyond 30 days postoperatively).While early mortality did not differ significantly between the sarcopenia and non-sarcopenia groups, late mortality was significantly higher in the sarcopenia group (22.6% vs. 5.8%, p=0.023).Multivariable Cox regression analysis identified age (hazard ratio: 1.072, p=0.001) and sarcopenia (hazard ratio: 0.289, p=0.005) as independent predictors of late mortality.These findings suggest that while sarcopenia does not affect early mortality following AAAD surgery, it is significantly associated with increased late mortality, underscoring the need for early detection and management strategies to improve long-term outcomes in this high-risk population.
科研通智能强力驱动
Strongly Powered by AbleSci AI