ArticleCureus2024
Comparative Analysis of Artificial Intelligence (AI) Languages in Predicting Sequential Organ Failure Assessment (SOFA) Scores.
Article in Cureus, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 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
3 citing papers in PubMed, 1 synthesis or guideline pooled it.
- The applications of ChatGPT and other large language models in anesthesiology and critical care: a systematic review.Canadian journal of anaesthesia = Journal canadien d'anesthesie · 2025Pooled it
- Critical care studies using large language models based on electronic healthcare records: A technical note.Journal of intensive medicine · 2025Review
- The evolution of ChatGPT-generated text in scientific medical publications.Saudi journal of anaesthesiaArticle
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
purposeThe Sequential Organ Failure Assessment (SOFA) score plays a crucial role in intensive care units (ICUs) by providing a reliable measure of a patient's organ function or extent of failure. However, the precise assessment is time-consuming, and daily assessment in clinical practice in the ICU can be challenging.
methodsRealistic scenarios in an ICU setting were created, and the data mining precision of ChatGPT 4.0 Plus, Bard, and Perplexity AI were assessed using Spearman's as well as the intraclass correlation coefficients regarding the accuracy in determining the SOFA score.
resultsThe strongest correlation was observed between the actual SOFA score and the score calculated by ChatGPT 4.0 Plus (
conclusionArtificial intelligence (AI) tools, particularly ChatGPT 4.0 Plus, show significant promise in assisting with automated SOFA score calculations via AI data mining in ICU settings. They offer a pathway to reduce the manual workload and increase the efficiency of continuous patient monitoring and assessment. However, further development and validation are necessary to ensure accuracy and reliability in a critical care environment.
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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.