ArticleBMC medical imaging2022
Correlation of CT-derived pectoralis muscle status and COVID-19 induced lung injury in elderly patients.
Article in BMC medical imaging, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.
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Who cites it
5 citing papers in PubMed, 1 synthesis or guideline pooled it, 5 citations in OpenAlex.
- Prevalence and clinical implications of abnormal body composition phenotypes in patients with COVID-19: a systematic review.The American journal of clinical nutrition · 2023Pooled it
- Article
- Multidimensional integrated lung protection measures attenuate pulmonary inflammation and improve lung function by inhibiting the NF-κB signaling pathway in elderly patients with lung dysfunction.Clinical and experimental medicine · 2025Article
- CT-derived pectoralis composition and incident pneumonia hospitalization using fully automated deep-learning algorithm: multi-ethnic study of atherosclerosis.European radiology · 2024Article
- The identification of an optimal body size parameter to adjust skeletal muscle area on chest CT in COVID-19 patients.Journal of frailty, sarcopenia and falls · 2024Article
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Authors and funding
10 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectivesTo explore the association between CT-derived pectoralis muscle index (PMI) and COVID-19 induced lung injury.
methodsWe 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).
resultsThe 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.
conclusionsPMI 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.
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