Evidence map›Paper›PMID 41748894›Full record

ArticleActa neurochirurgica2026

Patient perspective on large-language model responses to questions about Moyamoya.

Marcella R Ruppert-Gomez, Joon Hyeok Choi, Steven J Staffa, Katherine Holste, Jordan Xu, Catherine Stratton, Sophia D Kocher, Edward R Smith, Alfred Pokmeng See

Abstract read
In one paragraph

Article in Acta neurochirurgica, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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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.

2 · The registry

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3 · Its place in the literature

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No citing paper in PubMed yet.

4 · The record

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5 · Who and what money

Authors and funding

9 authors.

Marcella R Ruppert-GomezDepartment of Neurosurgery, Boston Children's Hospital, 300 Longwood Avenue, Boston, MA, 02115, USA.
Joon Hyeok ChoiDepartment of Neurosurgery, Boston Children's Hospital, 300 Longwood Avenue, Boston, MA, 02115, USA.
Steven J StaffaDepartment of Anesthesiology, Critical Care and Pain Medicine, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA.
Katherine HolsteDepartment of Neurosurgery, Boston Children's Hospital, 300 Longwood Avenue, Boston, MA, 02115, USA.
Jordan XuDepartment of Neurosurgery, Boston Children's Hospital, 300 Longwood Avenue, Boston, MA, 02115, USA.
Catherine StrattonMoyamoya Foundation Co., Enfiled, CT, USA.
Sophia D KocherMoyamoya Foundation Co., Enfiled, CT, USA.
Edward R SmithDepartment of Neurosurgery, Boston Children's Hospital, 300 Longwood Avenue, Boston, MA, 02115, USA.
Alfred Pokmeng SeeDepartment of Neurosurgery, Boston Children's Hospital, 300 Longwood Avenue, Boston, MA, 02115, USA. pokmeng.see@childrens.harvard.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeLarge Language Models (LLMs) are widely used and accessible. We investigate whether publicly available LLMs provide useful, safe, helpful and accurate information to the non-expert general community seeking answers about moyamoya.

methodsChatGPT-4o and Gemini 1.5 Flash were directly single-shot prompted with ten frequently asked questions about moyamoya. A survey of these responses was posted on the Moyamoya Foundation website for ten weeks. Respondents were randomly assigned to read either ChatGPT or Gemini generated responses. Clinicians treating cerebrovascular disease evaluated the safety and accuracy of all responses.

resultsCommunity respondents evaluated 27 sets of ChatGPT output and 20 sets of Gemini output. Output length was significantly different (p < 0.001). 1.2% and 20.8% of ChatGPT and Gemini answers were reported as "short," respectively. The LLMs failed to address potential risks for procedures and medications it mentioned (ChatGPT 38%, Gemini 28.6%). Responses omitted when these self-care strategies become insufficient and a medical professional should be consulted (ChatGPT 27.2%, Gemini 40.8%). However, community respondents felt LLM answers were of similar quality (ChatGPT 47.8%, Gemini 49%) or somewhat better (ChatGPT 24.4%, Gemini 22.4%) than one received from their physicians. Physicians evaluating the same LLM outputs reported the answers failed to address recent advances and research within the field (ChatGPT 57.5%, Gemini 62.5%) and failed to address urgent symptoms warranting referral to higher levels of care (ChatGPT 70.0%, Gemini 70.0%).

conclusionLLM responses are perceived as being of similar quality to a physician, but limitations remain for safety, omission of data and their impact on patient-physician relationships.

Indexed as

Large Language ModelsMoyamoya DiseaseFemaleHumansSurveys and QuestionnairesArtificial intelligenceLarge language modelsMoyamoyaNeurosurgeryPediatrics

Identifiers

PMID41748894
PMCPMC12948822

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

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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.