Volumetric computed tomography measurements as predictors for outcomes in a cohort of Fournier’s gangrene patients

Purpose This study evaluates the prognostic value of CT findings, including volumetric measurements, in predicting outcomes for patients with Fournier gangrene (FG), focusing on mortality, ICU admission, hospital stay length, and healthcare costs. Methods A retrospective study was conducted on 38 FG...

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Veröffentlicht in:Emergency radiology 2024-08, Vol.31 (4), p.481-489
Hauptverfasser: Ganapathy, Aravinda, Ballard, David H., Garuba, Favour, Lovato, Adriene, Mazaheri, Parisa, Chen, David Z., Schneider, McGinness, Lanier, M. Hunter, Ilahi, Obeid, Kirby, John P., Raptis, Constantine A., Mellnick, Vincent M.
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Sprache:eng
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Zusammenfassung:Purpose This study evaluates the prognostic value of CT findings, including volumetric measurements, in predicting outcomes for patients with Fournier gangrene (FG), focusing on mortality, ICU admission, hospital stay length, and healthcare costs. Methods A retrospective study was conducted on 38 FG patients who underwent CT scans before surgical debridement. We analyzed demographic data, CT volumetric measurements, and clinical outcomes using logistic and linear regression models. Results No single CT measurement significantly predicted mortality or ICU admission. The best model for mortality prediction included age, air volume, NSTI score, and male sex, with an AUC of 0.911. Intubation likelihood was modeled with an AUC of 0.913 using age, NSTI score, and visceral to subcutaneous fat ratio. The ICU admission model achieved an AUC of 0.677. Hospital stay was predicted by air volume (β = 0.0002656, p = 0.0505) with an adjusted R-squared of 0.1287. Air volume significantly predicted hospital costs (β = 2.859, p = 0.00558), resulting in an adjusted R-squared of 0.2165. Conclusion Volumetric CT findings provide valuable prognostic insights for FG patients, suggesting a basis for informed clinical decisions and resource allocation. Further validation in larger, multi-center studies is recommended to develop robust predictive models for FG outcomes.
ISSN:1438-1435
1070-3004
1438-1435
DOI:10.1007/s10140-024-02251-z