Radiomic analysis of abdominal organs during sepsis of digestive origin in a French intensive care unit
| Autor: | Louis Boutin, Louis Morisson, Florence Riché, Romain Barthélémy, Alexandre Mebazaa, Philippe Soyer, Benoit Gallix, Anthony Dohan, Benjamin G Chousterman |
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| Jazyk: | angličtina |
| Rok vydání: | 2023 |
| Předmět: | |
| Zdroj: | Acute and Critical Care, Vol 38, Iss 3, Pp 343-352 (2023) |
| Druh dokumentu: | article |
| ISSN: | 2586-6052 2586-6060 |
| DOI: | 10.4266/acc.2023.00136 |
| Popis: | Background Sepsis is a severe and common cause of admission to the intensive care unit (ICU). Radiomic analysis (RA) may predict organ failure and patient outcomes. The objective of this study was to assess a model of RA and to evaluate its performance in predicting in-ICU mortality and acute kidney injury (AKI) during abdominal sepsis. Methods This single-center, retrospective study included patients admitted to the ICU for abdominal sepsis. To predict in-ICU mortality or AKI, elastic net regularized logistic regression and the random forest algorithm were used in a five-fold cross-validation set repeated 10 times. Results Fifty-five patients were included. In-ICU mortality was 25.5%, and 76.4% of patients developed AKI. To predict in-ICU mortality, elastic net and random forest models, respectively, achieved areas under the curve (AUCs) of 0.48 (95% confidence interval [CI], 0.43–0.54) and 0.51 (95% CI, 0.46–0.57) and were not improved combined with Simplified Acute Physiology Score (SAPS) II. To predict AKI with RA, the AUC was 0.71 (95% CI, 0.66–0.77) for elastic net and 0.69 (95% CI, 0.64–0.74) for random forest, and these were improved combined with SAPS II, respectively; AUC of 0.94 (95% CI, 0.91–0.96) and 0.75 (95% CI, 0.70–0.80) for elastic net and random forest, respectively. Conclusions This study suggests that RA has poor predictive performance for in-ICU mortality but good predictive performance for AKI in patients with abdominal sepsis. A secondary validation cohort is needed to confirm these results and the assessed model. |
| Databáze: | Directory of Open Access Journals |
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