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April 3, 2026Infection Control and Hospital Epidemiology0 citations

Use of a large language model for surveillance of central line-associated bloodstream infections at a pediatric medical center

CSConnor StevensonMMMatthew D. McHughAAAngela Alburei

Key Points

  • This research aims to evaluate the accuracy of a large language model for identifying central line-associated bloodstream infections.
  • Compared LLM-assisted reviews to manual reviews
  • Assessed sensitivity and specificity of LLM for CLABSI
  • Gathered satisfaction feedback from infection preventionists
  • LLM identified CLABSI and secondary BSIs with high sensitivity
  • LLM demonstrated high specificity
  • Infection preventionists reported high satisfaction with the LLM tool

Abstract

We assessed the accuracy of a large language model (LLM) for clinical decision support for central line-associated bloodstream infection (CLABSI) identification. Comparing LLM-assisted to manual review, the LLM could efficiently identify CLABSI and secondary BSIs with high sensitivity and specificity. Infection preventionists reported high satisfaction with the tool.

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Cite This Study

Stevenson et al. (2026) studied this question.

synapsesocial.com/papers/69cf5e2e5a333a821460c503https://doi.org/10.1017/ice.2026.10435
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Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

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