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Yu SC, Shivakumar N, Betthauser K, et al. Comparison of early warning scores for sepsis early identification and prediction in the general ward setting. JAMIA Open. 2021;4(3):ooab062doi: 10.1093/jamiaopen/ooab062.
Yu, S. C., Shivakumar, N., Betthauser, K., Gupta, A., Lai, A. M., Kollef, M. H., Payne, P. R. O., & Michelson, A. P. (2021). Comparison of early warning scores for sepsis early identification and prediction in the general ward setting. JAMIA open, 4(3), ooab062. https://doi.org/10.1093/jamiaopen/ooab062
Yu, Sean C, et al. "Comparison of early warning scores for sepsis early identification and prediction in the general ward setting." JAMIA open vol. 4,3 (2021): ooab062. doi: https://doi.org/10.1093/jamiaopen/ooab062
Yu SC, Shivakumar N, Betthauser K, Gupta A, Lai AM, Kollef MH, Payne PRO, Michelson AP. Comparison of early warning scores for sepsis early identification and prediction in the general ward setting. JAMIA Open. 2021 Aug 02;4(3):ooab062. doi: 10.1093/jamiaopen/ooab062. eCollection 2021 Jul. PMID: 34820600; PMCID: PMC8607822.
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JAMIA Open. 2021 Aug 02;4(3):ooab062. doi: 10.1093/jamiaopen/ooab062. eCollection 2021 Jul.

Comparison of early warning scores for sepsis early identification and prediction in the general ward setting.

JAMIA open

Sean C Yu, Nirmala Shivakumar, Kevin Betthauser, Aditi Gupta, Albert M Lai, Marin H Kollef, Philip R O Payne, Andrew P Michelson

Affiliations

  1. Institute for Informatics, Department of Medicine, Washington University School of Medicine in St. Louis, St. Louis, Missouri, USA.
  2. Department of Biomedical Engineering, Washington University School in St. Louis, St. Louis, Missouri, USA.
  3. Department of Medicine, Washington University School of Medicine in St. Louis, St. Louis, Missouri, USA.
  4. Department of Pharmacy, Barnes-Jewish Hospital, St. Louis, Missouri, USA.
  5. Division of Pulmonary and Critical Care, Department of Medicine, Washington University School of Medicine in St. Louis, St. Louis, MO, USA.

PMID: 34820600 PMCID: PMC8607822 DOI: 10.1093/jamiaopen/ooab062

Abstract

The objective of this study was to directly compare the ability of commonly used early warning scores (EWS) for early identification and prediction of sepsis in the general ward setting. For general ward patients at a large, academic medical center between early-2012 and mid-2018, common EWS and patient acuity scoring systems were calculated from electronic health records (EHR) data for patients that both met and did not meet Sepsis-3 criteria. For identification of sepsis at index time, National Early Warning Score 2 (NEWS 2) had the highest performance (area under the receiver operating characteristic curve: 0.803 [95% confidence interval [CI]: 0.795-0.811], area under the precision recall curves: 0.130 [95% CI: 0.121-0.140]) followed NEWS, Modified Early Warning Score, and quick Sequential Organ Failure Assessment (qSOFA). Using validated thresholds, NEWS 2 also had the highest recall (0.758 [95% CI: 0.736-0.778]) but qSOFA had the highest specificity (0.950 [95% CI: 0.948-0.952]), positive predictive value (0.184 [95% CI: 0.169-0.198]), and F1 score (0.236 [95% CI: 0.220-0.253]). While NEWS 2 outperformed all other compared EWS and patient acuity scores, due to the low prevalence of sepsis, all scoring systems were prone to false positives (low positive predictive value without drastic sacrifices in sensitivity), thus leaving room for more computationally advanced approaches.

© The Author(s) 2021. Published by Oxford University Press on behalf of the American Medical Informatics Association.

Keywords: early warning score; predictive analytics; sepsis

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