Correlation of CT-derived pectoralis muscle status and COVID-19 induced lung injury in elderly patients

Author:

Ying-hao Pei,Hai-dong Zhang,Yuan Fang,Yong-kang Liu,Sen Liang,Wei-long Xu,Yu-shan Yang,Jun-feng Zhu,Hai-qi Zhou,Hua Jiang

Abstract

Abstract Objectives To explore the association between CT-derived pectoralis muscle index (PMI) and COVID-19 induced lung injury. Methods We enrolled 116 elderly COVID-19 patients linked to the COVID-19 outbreak in Nanjing Lukou international airport. We extracted three sessions of their CT data, including one upon admission (T1), one during the first 2 weeks when lung injury peaked (T2) and one on day 14 ± 2 (T3). Lung injury was assessed by CT severity score (CTSS) and pulmonary opacity score (POS). Pneumonia evolution was evaluated by changes of CT scores at T2 from T1(Δ). Results The maximum CT scores in low PMI patients were higher than those of normal PMI patients, including CTSS1 (7, IQR 6–10 vs. 5, IQR 3–6, p < 0.001), CTSS2 (8, IQR 7–11 vs. 5, IQR 4–7, p < 0.001) and POS (2, IQR 1–2.5 vs. 1, IQR 1–2, p < 0.001). Comorbidity (OR = 6.15, p = 0.023) and the presence of low PMI (OR = 5.43, p = 0.001) were predictors of lung injury aggravation with ΔCTSS1 > 4. The presence of low PMI (OR = 5.98, p < 0.001) was the predictor of lung injury aggravation with ΔCTSS2 > 4. Meanwhile, presence of low PMI (OR = 2.82, p = 0.042) and incrementally increasing D-dimer (OR = 0.088, p = 0.024) were predictors of lung injury aggravation with ΔPOS = 2. Conclusions PMI can be easily assessed on chest CT images and can potentially be used as one of the markers to predict the severity of lung injury in elderly COVID-19 patients.

Funder

National Natural Science Foundation of China

Publisher

Springer Science and Business Media LLC

Subject

Radiology, Nuclear Medicine and imaging

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3