Identifying immunosuppressed patients using structured data can be challenging. Large language models effectively extract structured concepts from unstructured clinical text. Here we show that GPT-4o outperforms traditional approaches in identifying immunosuppressive conditions and medication use by processing hospital admission notes.
View Article and Find Full Text PDFJ Allergy Clin Immunol Pract
January 2025
Background: Antibiotic stewardship in critically ill pneumonia patients is crucial yet challenging, partly due to the limited diagnostic yield of noninvasive infectious tests. In this study, we report an antibiotic prescription pattern informed by bronchoalveolar lavage (BAL) results, where clinicians de-escalate antibiotics based on the combination of quantitative cultures and multiplex PCR rapid diagnostic tests.
Methods: We analyzed data from SCRIPT, a single-center prospective cohort study of mechanically ventilated patients who underwent a BAL for suspected pneumonia.