Phlebology · 2026
Artificial intelligence and vascular surgeons in patient communication: A comparative analysis of intelligibility and clinical appropriateness in acute deep vein thrombosis.
СтатьяНазвание и аннотация: Перевод пока не подготовлен
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…
Ошибки и ограничения
История · было → стало
Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.
Gómez Gutiérrez Oliver Antonio, De la Torre Oscar A, Cassagne Gabriela, Flores-Orduña Jorge, Leon Luis, Fabiani Mario Alejandro
Аннотация
ObjectiveEffective patient communication is critical in acute deep vein thrombosis (DVT) management. This study evaluated and compared the intelligibility and clinical appropriateness of patient-directed explanations for acute DVT generated by vascular surgeons versus a diverse panel of large language models (LLMs), using a balanced, unit-matched design.MethodsIn this observational, cross-sectional study, 11 board-certified vascular surgeons and 11 distinct, independently developed LLMs each produced one response to a standardized acute DVT vignette in Spanish. Responses were blinded and scored using an 8-item clinical appropriateness grid (two independent graders, consensus) and five validated Spanish readability indices. Central tendency was assessed with Mann-Whitney U tests; dispersion was assessed descriptively (coefficient of variation, range) and, exploratorily, with Brown-Forsythe tests.ResultsClinical appropriateness did not differ significantly between groups (median 7/8 in both; p = 0.258), dispersion was descriptively far smaller for LLMs (SD 0.40 vs 1.92; coefficient of variation 5.9% vs 32.5%). LLM responses were more readable on three of four content-complexity indices (Fernández-Huerta, Gutiérrez de Polini, Szigriszt-Pazos; all p < 0.02) and required a numerically lower educational grade level (Crawford 5.4 vs 6.1; p = 0.075). Readability dispersion was descriptively far lower for LLMs (Fernández-Huerta range 31 vs 200 points; coefficient of variation 15% vs 181%), driven in the surgeon cohort by a single response that fell far outside the interpretable range; formal variance tests did not reach significance at this sample size. LLM responses were longer (median 903 vs 354 words; p = 0.003) and took longer to read (4.5 vs 1.8 min; p < 0.001). Neither group addressed screening for silent pulmonary embolism. Free-versus-premium comparisons were model-specific rather than uniform.ConclusionCurrent-generation LLMs matched board-certified surgeons in clinical completeness and produced more readable, descriptively far more consistent patient-facing explanations, without the communication failures observed in a minority of human responses. Both cohorts share an important, guideline-adjacent counseling gap.