Large Language Models in Patient Health Communication for Atherosclerotic Cardiovascular Disease: Pilot Cross-Sectional Comparative Analysis

DeepSeek R1 exhibited promising and consistent performance in generating high-quality, patient-facing ASCVD information across both English and Chinese, highlighting the potential of open-source LLMs in promoting digital health literacy and equitable access to chronic disease information. However, a clinically critical weakness was observed in guideline-sensitive treatment: the models did not reliably provide guideline-concordant standard treatment regimens, suggesting that LLM use should be limited to lower-risk informational subqueries (eg, definitions, diagnosis, and lifestyle education) unless augmented by expert oversight and safety controls.