ArticleInfection control and hospital epidemiology2024
Application of OpenAI GPT-4 for the retrospective detection of catheter-associated urinary tract infections in a fictitious and curated patient data set.
Article in Infection control and hospital epidemiology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
6 citing papers in PubMed, 1 synthesis or guideline pooled it, 14 citations in OpenAlex.
- Automated surveillance of non-ventilator-associated hospital-acquired pneumonia (nvHAP): a systematic literature review.Antimicrobial resistance and infection control · 2024Pooled it
- Large Language Models in Infectious Diseases: A Systemic Review.Research square · 2026Article
- Leveraging a large language model to support expansion of surveillance activities to include cardiovascular implantable device infections in a large, integrated national healthcare system.Infection control and hospital epidemiology · 2026Article
- Multiple large language models versus experienced physicians in diagnosing challenging cases with gastrointestinal symptoms.NPJ digital medicine · 2025Article
- Application of large language models in disease diagnosis and treatment.Chinese medical journal · 2025Review
- Confronting the Disruption of the Infectious Diseases Workforce by Artificial Intelligence: What This Means for Us and What We Can Do About It.Open forum infectious diseases · 2024Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The use of the OpenAI GPT-4 model in detecting catheter-associated urinary tract infection (CAUTI) cases in small fictitious and curated patient data sets was investigated. Final analysis of 50 patients including 11 CAUTI cases yielded sensitivity, specificity and positive and negative predictive values of 91%, 92%, 83%, and 96%, respectively.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.