ArticleScientific reports2025
The impact of prompting on ChatGPT's adherence to status epilepticus treatment guidelines.
Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
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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.
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Who cites it
3 citing papers in PubMed.
- Improving emergency management of status epilepticus: a randomized high-fidelity simulator-based trial.Journal of neurology · 2026Trial
- Modern generative large language models in epilepsy care: a scoping review of current applications, challenges, and future directions.Acta epileptologica · 2026Review
- Large Language Models in Clinical Neurology: A Systematic Review.Research square · 2026Article
Corrections and comments
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
This study assessed ChatGPT's adherence to established management guidelines for status epilepticus (SE) from major neurological societies (NCS, AES, EFNS) and examined how prompt specificity affected the quality of its recommendations. Four prompts varying in detail were each submitted four times, and the generated recommendations were analyzed for consistency with guidelines, along with an assessment of source relevance and accuracy. ChatGPT consistently recommended securing the airway and a breathing check (100% of responses) and always suggested benzodiazepines as first-line treatment. However, it rarely recommended key measures such as side positioning (25%) to prevent potential aspiration and neurological assessments (0-25%). Likewise, alternative administration routes for benzodiazepines were mentioned inconsistently (0-100%). While second- and third-line antiseizure medications were suggested consistently, proper dosage guidance was lacking when unprompted. EEG monitoring was recommended in 50-100%. More specific and detailed prompts increased guideline adherence most markedly regarding vital sign assessment (from 33 to 91%), correct dosages of second-line (from 50 to 100%), third-line drugs (from 0 to 100%), and screening for complications (from 0 to 100%). The findings underscore that Chat-GPT shows promise as a clinical support tool but requires structured prompts for accuracy and should not replace clinical judgment or professional oversight.
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Registered trials
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