aceLarge language models in the diagnosis and treatment of immunosuppression-related infections in rheumatic diseases: a comparative, vignette-based study
This study compared the diagnostic accuracy, initial test selection, and initial treatment choices of three current-generation Large Language Models (LLMs) with those of two infectious disease specialists in managing infectious complications in patients with immunosuppressed rheumatic disease. This cross-sectional comparative study utilized 100 standardized Turkish-language clinical vignettes, developed by an expert committee, encompassing ten infection categories: viral, bone/joint, respiratory, central nervous…
On 100 standardized vignettes, three LLMs answered more items correctly than two infectious disease specialists in diagnosis, work-up and initial treatment, suggesting a possible decision-support role for rare or opportunistic infections.
The vignettes were standardized written cases with one prespecified correct answer and only two human comparators, so results reflect a structured written task rather than superiority in clinical care; prospective real-world validation is still needed.
Evidence
- Peer-reviewedRheumatology International2026-10-09
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Truvace Impact Record TRV-2026-1683, v1: “Large language models in the diagnosis and treatment of immunosuppression-related infections in rheumatic diseases: a comparative, vignette-based study.” Truvace, 2026-10-17. /record/TRV-2026-1683 (accessed at citation time). sha256 df1fbf2909e58c2c…
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