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European journal of obstetrics, gynecology, and reproductive biology · 2026

Clinical safety of large language model responses to matched patient-language and clinician-language Turkish obstetric and gynecologic triage prompts: a model-blinded paired-scenario study.

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Ada Onur, Dagli Ugurcan, Bilen Egehan, Bayram Emre, Inan Abdurrahman Hamdi

Аннотация

OBJECTIVE: To determine whether presenting matched obstetric and gynecologic triage scenarios as patient-language prompts rather than clinician-language prompts affects expert-rated clinical confidence and the clinical safety of LLM-generated advice.

METHODS: Thirty obstetric and gynecologic scenarios were presented in matched clinician-language and patient-language Turkish formats to four LLMs. Five specialists independently evaluated 240 responses, generating 1,200 ratings. The primary outcome was the Global Clinical Confidence Score (GCCS; 0-2); five secondary outcomes were rated on 1-5 scales. Associations were examined using ordinal logistic generalized estimating equations adjusted for model and evaluator.

RESULTS: Clinically reliable responses (GCCS = 2) accounted for 89.3% of clinician-language and 91.3% of patient-language ratings. Patient-language phrasing was not significantly associated with overall GCCS (cumulative odds ratio 0.78, 95% confidence interval 0.57-1.06; p = 0.115), and the language-by-model interaction was not significant (p = 0.422). Patient-language prompts were associated with fewer GCCS = 0 ratings in a binary generalized estimating equations analysis (odds ratio 0.66, 95% confidence interval 0.46-0.96; p = 0.031), although the exact paired McNemar test was not significant (p = 0.096). After false-discovery-rate correction, patient-language prompts had higher evaluator-level triage appropriateness and clinical applicability scores (both adjusted p = 0.028).

CONCLUSION: No significant difference in overall expert-rated clinical confidence was detected between patient-language and clinician-language prompts.

ИП Урсолов Владлен Сергеевич

ИНН 500118482352 · ОГРНИП 314500117700049

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