AI-Driven Information for Relatives of Patients with Malignant Middle Cerebral Artery Infarction: A Preliminary Validation Study Using GPT-4o

<b>Purpose:</b> This study examines GPT-4o's ability to communicate effectively with relatives of patients undergoing decompressive hemicraniectomy (DHC) after malignant middle cerebral artery infarction (MMCAI). <b>Methods:</b> GPT-4o was asked 25 common questions from patients' relatives about DHC for MMCAI, twice over a 7-day interval. Responses were rated for accuracy, clarity, relevance, completeness, sourcing, and usefulness by board-certified intensivist* (one), neurologists, and neurosurgeons using the Quality Analysis of Medical AI (QAMAI) tool. Interrater reliability and stability were measured using ICC and Pearson's correlation. <b>Results:</b> The total QAMAI scores were 22.32 ± 3.08 for the intensivist, 24.68 ± 2.8 for the neurologist, 23.36 ± 2.86 and 26.32 ± 2.91 for the neurosurgeons, representing moderate-to-high accuracy. The evaluators reported moderate ICC (0.631, 95% CI: 0.321-0.821). The highest subscores were for the categories of accuracy, clarity, and relevance while the poorest were associated with completeness, usefulness, and sourcing. GPT-4o did not systematically provide references for their responses. The stability analysis reported moderate-to-high stability. The readability assessment revealed an FRE score of 7.23, an FKG score of 15.87 and a GF index of 18.15. <b>Conclusions:</b> GPT-4o provides moderate-to-high quality information related to DHC for MMCAI, with strengths in accuracy, clarity, and relevance. However, limitations in completeness, sourcing, and readability may impact its effectiveness in patient or their relatives' education.

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Journal
Brain Sciences
Published
2025-04-11
DOI
https://doi.org/10.3390/brainsci15040391
Primary Topic
Artificial Intelligence in Healthcare and Education
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article
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article

AI-Driven Information for Relatives of Patients with Malignant Middle Cerebral Artery Infarction: A Preliminary Validation Study Using GPT-4o

Ethan Harel, Nathan Torcida, Sami Barrit, Nawfel Ben‐Hamouda et al.
Brain Sciences
Artificial Intelligence in Healthcare and Education
article

AI-Driven Information for Relatives of Patients with Malignant Middle Cerebral Artery Infarction: A Preliminary Validation Study Using GPT-4o

Ethan Harel, Nathan Torcida, Sami Barrit, Nawfel Ben‐Hamouda, Mejdeddine Al Barajraji, Beatrice Pizzarotti, Jerome Rene Lechien, Nicolas Massager
article en

Abstract

<b>Purpose:</b> This study examines GPT-4o's ability to communicate effectively with relatives of patients undergoing decompressive hemicraniectomy (DHC) after malignant middle cerebral artery infarction (MMCAI). <b>Methods:</b> GPT-4o was asked 25 common questions from patients' relatives about DHC for MMCAI, twice over a 7-day interval. Responses were rated for accuracy, clarity, relevance, completeness, sourcing, and usefulness by board-certified intensivist* (one), neurologists, and neurosurgeons using the Quality Analysis of Medical AI (QAMAI) tool. Interrater reliability and stability were measured using ICC and Pearson's correlation. <b>Results:</b> The total QAMAI scores were 22.32 ± 3.08 for the intensivist, 24.68 ± 2.8 for the neurologist, 23.36 ± 2.86 and 26.32 ± 2.91 for the neurosurgeons, representing moderate-to-high accuracy. The evaluators reported moderate ICC (0.631, 95% CI: 0.321-0.821). The highest subscores were for the categories of accuracy, clarity, and relevance while the poorest were associated with completeness, usefulness, and sourcing. GPT-4o did not systematically provide references for their responses. The stability analysis reported moderate-to-high stability. The readability assessment revealed an FRE score of 7.23, an FKG score of 15.87 and a GF index of 18.15. <b>Conclusions:</b> GPT-4o provides moderate-to-high quality information related to DHC for MMCAI, with strengths in accuracy, clarity, and relevance. However, limitations in completeness, sourcing, and readability may impact its effectiveness in patient or their relatives' education.

Brain SciencesVol. 15(4)
University of Mons (BE), Université de Versailles Saint-Quentin-en-Yvelines (FR), Université Paris-Saclay (FR), Centre Hospitalier Universitaire Vaudois (CH), Université de Poitiers (FR), Centre Hospitalier Universitaire de Tivoli (BE), University of Lausanne (CH)
No poverty
Openalex Percentile: Top 95%
Artificial Intelligence in Healthcare and Education
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