ArticleInternational journal of colorectal disease2025
Combination of radiomic and clinical characteristics to predict mortality in patients with colorectal perforation.
Article in International journal of colorectal disease, 2025. 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
purposeWe aim to construct and verify a model combining radiomic and clinical data to predict early mortality in patients with colorectal perforation in a two-center study.
methodsData from 147 patients at Xiaogan Central Hospital (2014-2024) and 52 patients at Southern Hospital of Southern Medical University (2021-2023) were collected for model training and validation. Univariate and multivariate analyses were performed to identify risk factors associated with mortality. Radiomic characteristics from CT scans were extracted via least absolute shrinkage and selection operator (LASSO) regression to construct an imaging score. A nomogram was developed by integrating the findings from the multivariate analysis. Predictive performance was evaluated via the area under the receiver operating characteristic curve (AUC), and clinical utility was assessed via decision curve analysis (DCA).
resultsUnivariate analysis highlighted age, ASA classification, shock index, rad-score, white blood cell (WBC) count, neutrophil (N) and lymphocyte (L) counts, sodium (Na
conclusionA nomogram combining radiomic features and clinical characteristics effectively predicts mortality in patients with colorectal perforation, providing a valuable tool for clinical decision-making and patient management.
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