Evidence map›Paper›PMID 38279999›Full record

ArticleJournal of neurology2024

ChatGPT fails challenging the recent ESCMID brain abscess guideline.

Susanne Dyckhoff-Shen, Uwe Koedel, Matthijs C Brouwer, Jacob Bodilsen, Matthias Klein

Open access · hybridAbstract read
In one paragraph

Article in Journal of neurology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
1.3field-weighted citation impact, top 19% of its field
1 · What the graph read from 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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed, 11 citations in OpenAlex.

  1. On the future of guidelines.Critical care (London, England) · 2025
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors at 3 institutions in 4 countries.

Susanne Dyckhoff-ShenDepartment of Neurology with Friedrich-Baur-Institute, LMU University Hospital, LMU Munich (en.), Klinikum Grosshadern of the Ludwig Maximilians University of Munich, Marchioninistr. 15, 81377, Munich, Germany. susanne.dyckhoff@med.uni-muenchen.de.ORCID http://orcid.org/0000-0001-9247-4884
Uwe KoedelDepartment of Neurology with Friedrich-Baur-Institute, LMU University Hospital, LMU Munich (en.), Klinikum Grosshadern of the Ludwig Maximilians University of Munich, Marchioninistr. 15, 81377, Munich, Germany.
Matthijs C BrouwerDepartment of Neurology, Amsterdam UMC, University of Amsterdam, Amsterdam Neuroscience, Amsterdam, The Netherlands.
Jacob BodilsenDepartment of Infectious Diseases, Aalborg University Hospital, Aalborg, Denmark.
Matthias KleinDepartment of Neurology with Friedrich-Baur-Institute, LMU University Hospital, LMU Munich (en.), Klinikum Grosshadern of the Ludwig Maximilians University of Munich, Marchioninistr. 15, 81377, Munich, Germany.
LMU Klinikum · DEAalborg University Hospital · DKAmsterdam Neuroscience · NL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundWith artificial intelligence (AI) on the rise, it remains unclear if AI is able to professionally evaluate medical research and give scientifically valid recommendations.

aimThis study aimed to assess the accuracy of ChatGPT's responses to ten key questions on brain abscess diagnostics and treatment in comparison to the guideline recently published by the European Society for Clinical Microbiology and Infectious Diseases (ESCMID).

methodsAll ten PECO (Population, Exposure, Comparator, Outcome) questions which had been developed during the guideline process were presented directly to ChatGPT. Next, ChatGPT was additionally fed with data from studies selected for each PECO question by the ESCMID committee. AI's responses were subsequently compared with the recommendations of the ESCMID guideline.

resultsFor 17 out of 20 challenges, ChatGPT was able to give recommendations on the management of patients with brain abscess, including grade of evidence and strength of recommendation. Without data prompting, 70% of questions were answered very similar to the guideline recommendation. In the answers that differed from the guideline recommendations, no patient hazard was present. Data input slightly improved the clarity of ChatGPT's recommendations, but, however, led to less correct answers including two recommendations that directly contradicted the guideline, being associated with the possibility of a hazard to the patient.

conclusionChatGPT seems to be able to rapidly gather information on brain abscesses and give recommendations on key questions about their management in most cases. Nevertheless, single responses could possibly harm the patients. Thus, the expertise of an expert committee remains inevitable.

Indexed as

Biomedical ResearchBrain AbscessBrain DiseasesCentral Nervous System InfectionsArtificial IntelligenceHumansAIBrain abscessChatGPTGuideline

Identifiers

PMID38279999
PMCPMC10972965
OpenAlexW4391283060

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.