Abstract
This retrospective cohort assessed a ChatGPT-based AI model for 1-year KOOS prediction and infection risk in 98 primary total knee replacement (TKR) patients. The model predicted based on preoperative clinical, demographic, and intra-operative data. The model under predicted the mean knee injury and osteoarthritis Outcome Score (KOOS) by 7-8 points compared to surgeon-reported outcomes (p = 0.02) with moderate correlation (r = 0.45).Predicted risk of infection (2.4%) was nominally higher than observed (1.8%), with an ROC-AUC of 0.70. Directionally accurate, the model requires further fine-tuning prior to clinic use.