Comparative Efficacy of ChatGPT and DeepSeek in Addressing Patient Queries on Gonarthrosis and Total Knee Arthroplasty.

BACKGROUND

The advent of artificial intelligence (AI) in healthcare has opened new avenues for patient education and anxiety reduction. This study aims to compare the efficacy of 2 prominent AI platforms, ChatGPT and DeepSeek, in providing accurate and satisfactory responses to patients with gonarthrosis contemplating total knee arthroplasty (TKA).

METHODS

A prospective, comparative trial was conducted involving 100 patients diagnosed with gonarthrosis and indicated for TKA. Each patient posed 5 questions regarding the surgery and postoperative rehabilitation to both ChatGPT and DeepSeek. Responses were evaluated by 2 blinded orthopaedic specialists on a 10-point scale for accuracy and patient satisfaction. Patients also rated their satisfaction with each response on a 10-point scale. The primary outcome measures were the mean accuracy scores from specialists and mean satisfaction scores from patients.

RESULTS

Statistical analysis revealed significant differences between ChatGPT and DeepSeek in both accuracy and patient satisfaction ( < .001). ChatGPT demonstrated superior performance with a mean accuracy score of 8.7 ± 0.9 compared to DeepSeek's 7.4 ± 1.2. Patient satisfaction scores aligned with expert evaluations, with ChatGPT achieving a mean satisfaction score of 8.9 ± 0.8 vs DeepSeek's 7.6 ± 1.1. Notably, ChatGPT excelled in providing comprehensive explanations of surgical procedures (mean score 9.2 ± 0.7) and postoperative care (9.1 ± 0.8), while DeepSeek performed better in offering concise summaries of recovery timelines (8.3 ± 0.9).

CONCLUSIONS

This study demonstrates that ChatGPT offers more accurate and satisfactory responses to patient queries regarding gonarthrosis and TKA compared to DeepSeek. The findings suggest that AI platforms, particularly ChatGPT, can serve as valuable tools in augmenting patient education and potentially reducing preoperative anxiety. Future research should explore the integration of AI-assisted information delivery in clinical practice and its long-term impact on patient outcomes.