Automated CT‐Based Muscle Density Predicts Mortality Regardless of Muscle Area

医学 百分位 回顾性队列研究 危险系数 骨骼肌 霍恩斯菲尔德秤 内科学 比例危险模型 死亡率 心脏病学 肌萎缩 生存分析 人口 死亡风险 年轻人 存活率 腰大肌 试验预测值 队列研究 外科 队列 年龄调整 流行病学 肌肉组织
作者
Adam J. Kuchnia,Glen M. Blake,Minjung Lee,Jevin Lortie,Rachel J. Fenske,John W. Garrett,Perry J. Pickhardt
出处
期刊:Journal of Cachexia, Sarcopenia and Muscle [Springer Science+Business Media]
卷期号:17 (2)
标识
DOI:10.1002/jcsm.70268
摘要

ABSTRACT Background Abdominal CT‐based assessments of skeletal muscle may provide important prognostic information for all‐cause mortality in aging adults. We aimed to evaluate whether AI‐segmented muscle area and muscle density predict long‐term survival in a large, retrospective adult population. Methods This retrospective study included 151 141 adult patients who underwent an abdominal CT examination for any indication between 2000 and 2021. A validated automated AI‐based algorithm measured L3‐level muscle area (cm 2 ) and muscle density in Hounsfield units (HU). Demographic and clinical data (age, sex, BMI and date of death) were extracted from electronic health records. Survival analyses included Kaplan–Meier curves and multivariable hazard ratio (HR) models to determine the relationship between these muscle metrics and mortality. Results Among the 138 535 adults (66 468 men and 72 067 women) included, 28 489 died over the 20‐year period post‐CT, yielding an overall 20‐year survival rate of 0.620 (95% CI: 0.611–0.629). Of these, 9343 deaths occurred within the first year [survival rate: 0.933 (95% CI: 0.932–0.934)]. Mean and median follow‐up time was 6.4 and 4.9 years, respectively. Lower muscle density significantly predicted higher mortality when each patient's measurement was expressed by its percentile within the age and sex‐matched population (HR up to 3.5 in women and 4.0 in men), with decreasing mortality throughout the higher percentiles. Lower muscle area showed a more modest effect on mortality in both sexes when expressed in percentiles. Individuals with high muscle density demonstrated the most favourable survival and those with low density demonstrated the worst survival. Low muscle density significantly predicted mortality across all age groups and both sexes. Conversely, muscle area predicted mortality in all age groups in men, albeit to a lesser degree and did not predict mortality in any age group among women. Conclusions Automated CT‐based measurements of muscle density are superior to muscle area in predicting all‐cause mortality in a large, heterogeneous adult population. Incorporating AI‐driven muscle density assessments into routine clinical practice could substantially improve patient risk stratification and management, of particular relevance for aging and sarcopenic patients.

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