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<p>Sepsis accounts for a substantial portion of global deaths and healthcare costs. The objective of this reproducibility study is to validate Duke Health’s Sepsis Watch ML model, in a new community healthcare setting and assess its performance and clinical utility in early sepsis detection at Summa Health’s emergency departments. The study analyzed the model’s ability to predict sepsis using a combination of static and dynamic patient data using 205,005 encounters between 2020 and 2021 from 101,584 unique patients. 54.7% (<i>n</i> = 112,223) patients were female and the average age was 50 (IQR [38,71]). The AUROC ranged from 0.906 to 0.960, and the AUPRC ranged from 0.177 to 0.252 across the four sites. Ultimately, the reproducibility of the Sepsis Watch model in a community health system setting confirmed its strong and robust performance and portability across different geographical and demographic contexts with little variation.</p>

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Evaluating sepsis watch generalizability through multisite external validation of a sepsis machine learning model

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年6月11日

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  • Bruno Valan,
  • Anusha Prakash,
  • William Ratliff,
  • Michael Gao,
  • Srikanth Muthya,
  • Ajit Thomas,
  • Jennifer L. Eaton,
  • Matt Gardner,
  • Marshall Nichols,
  • Mike Revoir,
  • Dustin Tart,
  • Cara O’Brien,
  • Manesh Patel,
  • Suresh Balu,
  • Mark Sendak

摘要

Sepsis accounts for a substantial portion of global deaths and healthcare costs. The objective of this reproducibility study is to validate Duke Health’s Sepsis Watch ML model, in a new community healthcare setting and assess its performance and clinical utility in early sepsis detection at Summa Health’s emergency departments. The study analyzed the model’s ability to predict sepsis using a combination of static and dynamic patient data using 205,005 encounters between 2020 and 2021 from 101,584 unique patients. 54.7% (n = 112,223) patients were female and the average age was 50 (IQR [38,71]). The AUROC ranged from 0.906 to 0.960, and the AUPRC ranged from 0.177 to 0.252 across the four sites. Ultimately, the reproducibility of the Sepsis Watch model in a community health system setting confirmed its strong and robust performance and portability across different geographical and demographic contexts with little variation.