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Early prediction of renal replacement therapy within 24 hours after septic shock recognition in the emergency department using machine learning: a retrospective analysis of a prospectively collected multicenter registry.

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Title: Early prediction of renal replacement therapy within 24 hours after septic shock recognition in the emergency department using machine learning: a retrospective analysis of a prospectively collected multicenter registry.
Authors: Nah S; Department of Emergency Medicine, Soonchunhyang University Bucheon Hospital, 170 Jomaru-ro, Bucheon, 14584, Republic of Korea., Lim TH; Department of Emergency Medicine, College of Medicine, Hanyang University, Seoul, Republic of Korea., Chung SP; Department of Emergency Medicine, Gangnam Severance Hospital, Yonsei University College of Medicine, Seoul, Korea., Suh GJ; Department of Emergency Medicine, Seoul National University Hospital, Seoul, Republic of Korea., Choi SH; Department of Emergency Medicine, Korea University Guro Hospital, Seoul, Korea., Kwon WY; Department of Emergency Medicine, Seoul National University Hospital, Seoul, Republic of Korea., Kim WY; Department of Emergency Medicine, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Korea., Kim K; Department of Emergency Medicine, CHA Bundang Medical Center, CHA University, Seongnam, Korea., Choi S; Department of Emergency Medicine, Soonchunhyang University Bucheon Hospital, 170 Jomaru-ro, Bucheon, 14584, Republic of Korea., You JS; Department of Emergency Medicine, Gangnam Severance Hospital, Yonsei University College of Medicine, Seoul, Korea., Choi HS; Department of Emergency Medicine, College of Medicine, Kyung Hee University, Seoul, Korea., Shin TG; Department of Emergency Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea. drshin88@gmail.com., Han S; Department of Emergency Medicine, Soonchunhyang University Bucheon Hospital, 170 Jomaru-ro, Bucheon, 14584, Republic of Korea. brayden0819@daum.net.
Source: BMC emergency medicine [BMC Emerg Med] 2026 Mar 27; Vol. 26 (1). Date of Electronic Publication: 2026 Mar 27.
Publication Type: Journal Article; Multicenter Study
Journal Info: Publisher: BioMed Central Country of Publication: England NLM ID: 100968543 Publication Model: Electronic Cited Medium: Internet ISSN: 1471-227X (Electronic) Linking ISSN: 1471227X NLM ISO Abbreviation: BMC Emerg Med Subsets: MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:1471-227X
DOI:10.1186/s12873-026-01558-z