ArticleThe clinical respiratory journal2026
Opportunistic Chest CT-Derived Body Composition for Predicting 90-Day Adverse Outcomes After Hospitalization for Acute Exacerbation of Chronic Obstructive Pulmonary Disease.
Article in The clinical respiratory journal, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
backgroundPatients hospitalized for acute exacerbation of chronic obstructive pulmonary disease (AECOPD) remain at risk of readmission and death after discharge. Opportunistic chest computed tomography (CT) body-composition metrics may provide additional prognostic information beyond conventional clinical scores.
objectiveTo develop and validate a 90-day adverse-outcome prediction model for hospitalized AECOPD using admission clinical variables and opportunistic chest CT body-composition metrics.
methodsA retrospective modelling cohort of 203 AECOPD admissions from the index centre was analysed. Admissions from 2021 to 2024 formed the development cohort (n = 152), and 2025 admissions formed the temporal-validation cohort (n = 51). An external-validation cohort from another centre included 103 admissions from records screened between 1 January 1 and 1 January 2025 after the model was locked. The primary outcome was 90-day readmission or death. LASSO was used for variable screening in the development cohort. A feature-count AUC plateau analysis and prespecified multialgorithm screening were used to lock the final model before validation. DECAF and BAP-65 were retained as comparator scores.
resultsThe 90-day adverse outcome occurred in 66 of 152 development patients (43.4%), 18 of 51 temporal-validation patients (35.3%) and 35 of 103 external-validation patients (34.0%). LASSO retained prior AECOPD admissions, home oxygen before admission, diabetes mellitus, intermuscular adipose tissue area, long-term NIV before admission, heart rate and coronary artery disease. Feature-count analysis supported this seven-predictor set, and multialgorithm screening selected HistGradientBoosting for validation. In temporal validation, the locked model achieved AUC 0.80 (0.64-0.95), sensitivity 0.78 (0.59-0.94), specificity 0.88 (0.76-0.97) and Brier score 0.15 (0.09-0.21), with imperfect calibration (Hosmer-Lemeshow p < 0.001). In external validation, the locked model achieved AUC 0.77 (0.66-0.87), sensitivity 0.66 (0.49-0.80), specificity 0.79 (0.71-0.88) and Brier score 0.18 (0.15-0.21); the Hosmer-Lemeshow p value was 0.209.
conclusionsA 90-day AECOPD prediction model combining clinical and opportunistic CT body-composition variables showed consistent discrimination across validation cohorts, but calibration remained a key implementation boundary. Formal multicentre validation and calibration updating are needed before routine clinical use.
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