Retrospective modeling study of ChatGPT (GPT 4) warfarin dose adjustment in patients with INRs outside the therapeutic range

Abstract

Objective This retrospective, modeled study evaluates the accuracy of ChatGPT (GPT-4)-based warfarin dose adjustments compared to clinician recommendations at the Cardiology Clinic of Konya City Hospital, focusing on patients with international normalized ratio (INR) values outside the therapeutic range (2–3). We hypothesized that ChatGPT could provide reliable, consistent dose guidance. Methods We reviewed the records of warfarin-treated patients from 1 June 2022 through 24 November 2024. Clinical data used by physicians (e.g. baseline INR, warfarin indication, comorbidities, and current dose) were provided to ChatGPT to generate hypothetical weekly dose recommendations. ChatGPT's impact on INR normalization was modeled using standard dose–response assumptions and compared with actual outcomes under physician-guided therapy. Results A total of 180 patients met the inclusion criteria. ChatGPT's recommended doses were within ±1 mg/week of physician prescriptions in 74% of cases and within ±2 mg/week in 84%. The mean physician dose was 28.0 ± 6.1 mg/week versus ChatGPT's 27.5 ± 5.9 mg/week ( p = .12). Seventy-two percent of patients achieved therapeutic INR under physician-managed dosing, while the model suggested a 69% success rate for ChatGPT-guided dosing ( p = .15). Real-world adverse events were infrequent under physician management (1.1% major bleeding, 0.6% thrombotic events). Conclusion In this retrospective, exploratory analysis with modeled outcomes, ChatGPT's weekly dose suggestions showed high concordance with clinician dosing. These findings are hypothesis-generating and do not establish clinical efficacy or safety; prospective, physician-supervised trials—potentially integrated with home INR monitoring—are required for validation.

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