A simple electronic medical record-based predictors of illness severity in sepsis (sepsis) score.


Journal

PloS one
ISSN: 1932-6203
Titre abrégé: PLoS One
Pays: United States
ID NLM: 101285081

Informations de publication

Date de publication:
2024
Historique:
received: 24 10 2023
accepted: 10 02 2024
medline: 26 6 2024
pubmed: 26 6 2024
entrez: 26 6 2024
Statut: epublish

Résumé

Current scores for predicting sepsis outcomes are limited by generalizability, complexity, and electronic medical record (EMR) integration. Here, we validate a simple EMR-based score for sepsis outcomes in a large multi-centre cohort. A simple electronic medical record-based predictor of illness severity in sepsis (SEPSIS) score was developed (4 additive lab-based predictors) using a population-based retrospective cohort study. Internal medicine services across four academic teaching hospitals in Toronto, Canada from April 2010-March 2015 (primary cohort) and 2015-2019 (secondary cohort). We identified patients admitted with sepsis based upon receipt of antibiotics and positive cultures. The primary outcome was in-hospital mortality and secondary outcomes were ICU admission at 72 hours, and hospital length of stay (LOS). We calculated the area under the receiver operating curve (AUROC) for the SEPSIS score, qSOFA, and NEWS2. We then evaluated the SEPSIS score in a secondary cohort (2015-2019) of hospitalized patients receiving antibiotics. Our primary cohort included 1,890 patients with a median age of 72 years (IQR: 56-83). 9% died during hospitalization, 18.6% were admitted to ICU, and mean LOS was 12.7 days (SD: 21.5). In the primary and secondary (2015-2019, 4811 patients) cohorts, the AUROCs of the SEPSIS score for predicting in-hospital mortality were 0.63 and 0.64 respectively, which were similar to NEWS2 (0.62 and 0.67) and qSOFA (0.62 and 0.68). AUROCs for predicting ICU admission at 72 hours, and length of stay > 14 days, were similar between scores, in the primary and secondary cohorts. All scores had comparable calibration for predicting mortality. An EMR-based SEPSIS score shows a similar ability to predict important clinical outcomes compared with other validated scores (qSOFA and NEWS2). Because of the SEPSIS score's simplicity, it may prove a useful tool for clinical and research applications.

Identifiants

pubmed: 38924010
doi: 10.1371/journal.pone.0299473
pii: PONE-D-23-29189
doi:

Types de publication

Journal Article Multicenter Study

Langues

eng

Sous-ensembles de citation

IM

Pagination

e0299473

Informations de copyright

Copyright: © 2024 Cressman et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Déclaration de conflit d'intérêts

The authors have declared that no competing interests exist.

Auteurs

Alex M Cressman (AM)

Temerty Faculty of Medicine, University of Toronto, Toronto, Toronto, Ontario, Canada.
Division of General Internal Medicine, University of Toronto, Toronto, Ontario, Canada.

Bijun Wen (B)

Li Ka Shing Knowledge Institute, Toronto, Ontario, Canada.

Sudipta Saha (S)

Li Ka Shing Knowledge Institute, Toronto, Ontario, Canada.

Hae Young Jun (HY)

Li Ka Shing Knowledge Institute, Toronto, Ontario, Canada.

Riley Waters (R)

Li Ka Shing Knowledge Institute, Toronto, Ontario, Canada.

Sharan Lail (S)

Unity Health Toronto, Toronto, Ontario, Canada.
Department of Family and Community Medicine, Temerty Faculty of Medicine, Toronto, Canada.

Aneela Jabeen (A)

Li Ka Shing Knowledge Institute, Toronto, Ontario, Canada.

Radha Koppula (R)

Li Ka Shing Knowledge Institute, Toronto, Ontario, Canada.

Lauren Lapointe-Shaw (L)

Temerty Faculty of Medicine, University of Toronto, Toronto, Toronto, Ontario, Canada.
Division of General Internal Medicine, University of Toronto, Toronto, Ontario, Canada.

Kathleen A Sheehan (KA)

Temerty Faculty of Medicine, University of Toronto, Toronto, Toronto, Ontario, Canada.
Division of Psychiatry, The University of Toronto, Toronto, Ontario, Canada.

Adina Weinerman (A)

Temerty Faculty of Medicine, University of Toronto, Toronto, Toronto, Ontario, Canada.
Sunnybrook Health Sciences Centre, University of Toronto, Toronto, Ontario, Canada.

Nick Daneman (N)

Temerty Faculty of Medicine, University of Toronto, Toronto, Toronto, Ontario, Canada.
Sunnybrook Health Sciences Centre, University of Toronto, Toronto, Ontario, Canada.

Amol A Verma (AA)

Temerty Faculty of Medicine, University of Toronto, Toronto, Toronto, Ontario, Canada.
Division of General Internal Medicine, University of Toronto, Toronto, Ontario, Canada.
Li Ka Shing Knowledge Institute, Toronto, Ontario, Canada.
Unity Health Toronto, Toronto, Ontario, Canada.

Fahad Razak (F)

Temerty Faculty of Medicine, University of Toronto, Toronto, Toronto, Ontario, Canada.
Division of General Internal Medicine, University of Toronto, Toronto, Ontario, Canada.
Li Ka Shing Knowledge Institute, Toronto, Ontario, Canada.
Unity Health Toronto, Toronto, Ontario, Canada.

Derek MacFadden (D)

The Ottawa Hospital Research Institute, Ottawa, Ontario, Canada.

Articles similaires

[Redispensing of expensive oral anticancer medicines: a practical application].

Lisanne N van Merendonk, Kübra Akgöl, Bastiaan Nuijen
1.00
Humans Antineoplastic Agents Administration, Oral Drug Costs Counterfeit Drugs

Smoking Cessation and Incident Cardiovascular Disease.

Jun Hwan Cho, Seung Yong Shin, Hoseob Kim et al.
1.00
Humans Male Smoking Cessation Cardiovascular Diseases Female
Humans United States Aged Cross-Sectional Studies Medicare Part C
1.00
Humans Yoga Low Back Pain Female Male

Classifications MeSH