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Development and validation of an interpretable model for predicting sepsis mortality across care settings.

Authors :
Lee, Young Seok
Han, Seungbong
Lee, Ye Eun
Cho, Jaehwa
Choi, Young Kyun
Yoon, Sun-Young
Oh, Dong Kyu
Lee, Su Yeon
Park, Mi Hyeon
Lim, Chae-Man
Moon, Jae Young
the Korean Sepsis Alliance (KSA) Investigators
Hong, Sang‑Bum
Hong, Suk‑Kyung
Suh, Gee Young
Jeon, Kyeongman
Ko, Ryoung‑Eun
Cho, Young‑Jae
Lee, Yeon Joo
Lim, Sung Yoon
Source :
Scientific Reports. 6/13/2024, Vol. 14 Issue 1, p1-11. 11p.
Publication Year :
2024

Abstract

There are numerous prognostic predictive models for evaluating mortality risk, but current scoring models might not fully cater to sepsis patients’ needs. This study developed and validated a new model for sepsis patients that is suitable for any care setting and accurately forecasts 28-day mortality. The derivation dataset, gathered from 20 hospitals between September 2019 and December 2021, contrasted with the validation dataset, collected from 15 hospitals from January 2022 to December 2022. In this study, 7436 patients were classified as members of the derivation dataset, and 2284 patients were classified as members of the validation dataset. The point system model emerged as the optimal model among the tested predictive models for foreseeing sepsis mortality. For community-acquired sepsis, the model’s performance was satisfactory (derivation dataset AUC: 0.779, 95% CI 0.765–0.792; validation dataset AUC: 0.787, 95% CI 0.765–0.810). Similarly, for hospital-acquired sepsis, it performed well (derivation dataset AUC: 0.768, 95% CI 0.748–0.788; validation dataset AUC: 0.729, 95% CI 0.687–0.770). The calculator, accessible at , is user-friendly and compatible. The new predictive model of sepsis mortality is user-friendly and satisfactorily forecasts 28-day mortality. Its versatility lies in its applicability to all patients, encompassing both community-acquired and hospital-acquired sepsis. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
20452322
Volume :
14
Issue :
1
Database :
Academic Search Index
Journal :
Scientific Reports
Publication Type :
Academic Journal
Accession number :
177936577
Full Text :
https://doi.org/10.1038/s41598-024-64463-0