Fabiani, Mario Alejandro

Abstract Introduction Revascularization to prevent limb loss is not feasible or represents a very high risk in a significant proportion of patients with chronic limb-threatening ischaemia (CLTI). No standard definition currently exists to define this population of patients. The aim of this study was to develop a consensus-based, multidomain definition to improve clinical assessment and reporting of studies in people with ‘no option’ (NO) or ‘poor option’ (PO) CLTI. Methods A modified Delphi process was conducted with 164 specialists from 30 countries. Two iterative survey rounds were used to reach consensus, defined as ≥70% agreement with a score of ≥7 on a nine-point scale. Results Some 164 international vascular specialists participated in the study, averaging 19 years of experience. A multidomain framework including arterial disease anatomy, biology, risk, function, and context (ABRFC) achieved 83% consensus. A ‘desert foot’ was defined as the absence of distal arterial revascularization targets on advanced non-invasive imaging, invasive digital subtraction angiography, and at least one failed endovascular revascularization attempt (81.6% agreement). Inadequate autogenous bypass conduit was defined as the lack of usable autologous vein across all four limbs (85% agreement). Patients were classified as NO for revascularization if they present with ‘desert foot’, prohibitive medical risk, a non-functional limb, or in those patients who refused arterial revascularization. PO revascularization patients combined factors such as severe infection, lack of autologous vein, or treatment non-compliance (72.1% agreement). Conclusion This consensus study established a structured, expert-validated definition of no option or poor option for revascularisation of patients with CLTI. The multidomain ABRFC framework provides a foundation for standardized clinical assessment, trial design, and future guideline development.

Background: Peripheral artery disease (PAD) is a global health challenge. Advances in artificial intelligence (AI), such as large language models (LLMs) and chain-of-thought (CoT) reasoning, offer novel approaches for clinical recommendations. This study compared the readability and guideline adherence of responses from physicians and AI for a standardized PAD case. Methods: This cross-sectional study gathered responses from 30 specialized physicians (11 cardiologists, 19 vascular surgeons) across seven Latin American countries and 13 LLM systems (10 standard, three CoT). Both groups addressed diagnosis, treatment, risks, and prognosis; LLMs responded as vascular specialists. Responses were blindly evaluated with five validated Spanish readability indices and compared to the 2024 ACC/AHA multisocietal PAD guideline. Three experts scored guideline adherence; nonparametric tests were applied. Results: Guideline adherence did not differ significantly between physicians (median 5.8 [3.4–7.6]) and LLMs (7.3 [4.7–9.7], p = 0.169), though CoT-LLMs achieved the highest scores (9.7 [8.5–11.0]). LLMs more often recommended supervised exercise (84.6% vs 30.0%, p = 0.002) and revascularization for quality of life (69.2% vs 20.0%, p = 0.004), whereas physicians favored cilostazol (60.0% vs 30.8%, p = 0.104). LLM responses had lower Readability μ values (46.9 vs 51.4, p = 0.012). Inter-rater reliability was highest for CoT-LLMs (intraclass correlation coefficient [ICC] = 0.98) versus physicians (ICC = 0.76). Conclusion: LLM showed comparable guideline adherence to physicians although CoT models achieved the highest scores. The difference in physician and AI treatment preferences suggest the potential of AI as adjunct clinical tools and warrants further study.