ArticleChinese medical journal pulmonary and critical care medicine2024
Association of ratios of visceral fat area/subcutaneous fat area and muscle area/standard body weight at T12 CT level with the prognosis of acute respiratory distress syndrome.
Article in Chinese medical journal pulmonary and critical care medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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4 citing papers in PubMed.
- Opportunistic Screening on Chest CT, From theAJR. American journal of roentgenology · 2026Review
- Testosterone therapy effects adipose distribution in older females post hip-fracture: The STEP-HI study.Obesity pillars · 2026Article
- The Fat-Pancreas Axis: A Narrative Review Unraveling the Role of Obesity in Pancreatic Diseases.Cureus · 2025Review
- Comments on "Analysis of Physiological Oxygen Concentrations in Different Abdominal Fat Layers by Body Mass Index".Aesthetic plastic surgery · 2025Article
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7 authors.
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Abstract
Background: It is well-known that body composition metrics can influence the prognosis of various diseases. This study investigated how body composition metrics predict acute respiratory distress syndrome (ARDS) prognosis, focusing on the ratio of visceral fat area (VFA) to subcutaneous fat area (SFA), SFA to standard body weight (SBW), VFA to SBW, and muscle area (MA) to SBW. These metrics were assessed at the level of the twelfth thoracic vertebra (T12 computed tomography [CT] level) to determine their correlation with the outcomes of ARDS. The goal was to utilize these findings to refine and personalize treatment strategies for ARDS. Methods: Patients with ARDS admitted to the intensive care units (ICUs) of three hospitals from January 2016 to July 2023 were enrolled in this study. Within 24 hours of ARDS onset, we obtained chest CT scans to measure subcutaneous fat, visceral fat, and muscle area at the T12 level. We then compared these ratios between survivors and non-survivors. Logistic regression was employed to identify prognostic risk factors. Receiver operating characteristic (ROC) curve analysis was utilized to determine the optimal cutoff for predictors of in-hospital mortality. Based on this cutoff, patients with ARDS were stratified. To reduce confounding factors, 1:1 propensity score matching (PSM) was applied. We conducted analyses of clinical feature and prognostic differences pre- and post-PSM between the stratified groups. Additionally, Kaplan-Meier survival curves were generated to compare the survival outcomes of these groups. Results: Of 258 patients with ARDS, 150 survived and 108 did not. Non-survivors had a higher VFA/SFA ratio ( Conclusions: Among all patients with ARDS, the VFA to SFA ratio, MA to SBW ratio at the T12 level, age, APACHE II score, and lactate levels emerged as independent risk factors for mortality.
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