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Thoracic muscle density index in the short-term prognosis of early-stage lung adenocarcinoma after video-assisted thoracoscopic surgery

Year: 2025
Type: article
Study design: Observational Study
Abstract: Nutritional status can significantly impact patients’ prognosis. This study aims to identify a more accurate nutritional indicator that can predict the short-term prognosis of these patients. 132 patients of early-stage lung adenocarcinoma (LUAD) were included. Postoperative hospital stays (PHS) served as the primary outcome. We performed correlation analysis of PHS using the T4 skeletal mass index (T4-SMI), T4 skeletal muscle density (T4-SMD), and BMI. The predictive performance of these nutritional indicators was validated with receiver operating characteristic curves, decision curves, and calibration curves. The Thoracic Muscle Density Index (TMDI) was created by combining T4-SMI and T4-SMD, and ROC analysis was used to determine cut-off values for identifying high-risk patients. Additionally, we evaluated the predictive performance of TMDI for postoperative complications. Higher T4-SMI (r = −0.38) and T4-SMD(r = −0.40) were significantly associated with shorter PHS in LUAD patients, and their correlation coefficients were significantly higher than BMI(r = −0.09). The ROC curve analysis of TMDI demonstrated that for males, the AUC was 0.83 ( p < 0.01 ), and for female, the AUC was 0.87 ( p < 0.0001 ), with TMDI cut-off values are 0.18 for females and 0.27 for males. Patients with postoperative complications had significantly higher TMDI values compared to those without complications (male: 0.46 ± 0.03 vs. 0.13 ± 0.15, p < 0.001 ; female: 0.41 ± 0.12 vs. 0.19 ± 0.20, p < 0.01 ). There was no significant correlation between the patient's TMDI and albumin, pulmonary function. TMDI as a nutritional indicator, demonstrates strong predictive performance for short-term prognosis in early-stage LUAD patients after VATS. It can effectively assist clinicians in managing perioperative care.
Authors: Jieming Cao, Mengqi Shao, Yazhuo Liu, Wanwen Li, Wei Han, Ji'an Zou, Yan Hu, Li Wang, Wenliang Liu
Language: English
Field: Medicine
Open Access status: gold
Estimated APC paid: $1,200
OpenAlex ID: W4416195863
FWCI:
Cites: 35
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