ArticleJournal of intensive care medicine2025
Evaluating the Appropriateness, Consistency, and Readability of ChatGPT in Critical Care Recommendations.
Article in Journal of intensive care medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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
15 citing papers in PubMed.
- Guideline-augmented prompting improves comparative preference and response consistency of large language model outputs for orthopaedic anaesthesia questions: A controlled prompting study.Journal of experimental orthopaedics · 2026Article
- Hallucination Rate of Peer-Reviewed Citations Generated by Large Language Models in Neurocritical Care.Critical care explorations · 2026Article
- Unmasking bias in artificial intelligence: sex and racial representation in critical care medicine through text-to-image generators.BJA open · 2026Article
- Retrieval-Augmented Language Models for Clinical Decision Support in the Classification of Inborn Errors of Immunity.Journal of clinical immunology · 2026Article
- Ambiguity Detection in Medical Exams via Large Language Models: Retrospective Cross-Sectional Pilot Study.JMIR medical education · 2026Article
- Generative artificial intelligence-driven chatbots and medical misinformation: an accuracy, referencing and readability audit.BMJ open · 2026Article
- Perception of sex and race diversity in critical care medicine by generative AI: biases, measurement and implications.Critical care (London, England) · 2026Article
- Artificial intelligence-guided nutritional therapy in the ICU.Current opinion in clinical nutrition and metabolic care · 2026Review
- Article
- Large Language Models in Critical Care Medicine: Scoping Review.JMIR medical informatics · 2025Article
- Evaluating the performance of large language models versus human researchers on real world complex medical queries.Scientific reports · 2025Article
- AI assisted prediction of unplanned intensive care admissions using natural language processing in elective neurosurgery.NPJ digital medicine · 2025Article
- Primer on large language models: an educational overview for intensivists.Critical care (London, England) · 2025Review
- A large language model improves clinicians' diagnostic performance in complex critical illness cases.Critical care (London, England) · 2025Article
- Comparative evaluation and performance of large language models on expert level critical care questions: a benchmark study.Critical care (London, England) · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
PubMed holds no abstract for this paper.
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.