Development and validation of an interpretable model for predicting sepsis mortality across care settings.
Young Seok Lee, Seungbong Han, Ye Eun Lee, Jaehwa Cho, Young Kyun Choi, Sun-Young Yoon, Dong Kyu Oh, Su Yeon Lee, Mi Hyeon Park, Chae-Man Lim, Jae Young Moon, Korean Sepsis Alliance (KSA) Investigators
Author Information
Young Seok Lee: Division of Pulmonary, Allergy, and Critical Care Medicine, Department of Internal Medicine, Korea University Guro Hospital, Seoul, Republic of Korea.
Seungbong Han: Department of Biostatistics, Korea University College of Medicine, Seoul, Republic of Korea.
Ye Eun Lee: Department of Biostatistics, Korea University College of Medicine, Seoul, Republic of Korea.
Jaehwa Cho: Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, Gangnam Severance Hospital, Yonsei University College of Medicine, Seoul, Republic of Korea.
Young Kyun Choi: Division of Infectious Disease and Critical Care Medicine, Department of Internal Medicine, Chungnam National University College of Medicine, Chungnam National University Sejong Hospital, Sejong, Republic of Korea.
Sun-Young Yoon: Division of Pulmonary, Allergy, and Critical Care Medicine, Department of Internal Medicine, Chungnam National University College of Medicine, Chungnam National University Sejong Hospital, Sejong, Republic of Korea.
Dong Kyu Oh: Department of Pulmonary and Critical Care Medicine, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea.
Su Yeon Lee: Department of Pulmonary and Critical Care Medicine, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea.
Mi Hyeon Park: Department of Pulmonary and Critical Care Medicine, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea.
Chae-Man Lim: Department of Pulmonary and Critical Care Medicine, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea.
Jae Young Moon: Division of Pulmonary, Allergy, and Critical Care Medicine, Department of Internal Medicine, Chungnam National University College of Medicine, Chungnam National University Sejong Hospital, Sejong, Republic of Korea. diffable@hanmail.net.
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 https://avonlea76.shinyapps.io/shiny_app_up/ , 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.
