Abstract
OBJECTIVE: To compare perioperative outcomes and early functional recovery between AI-robotic and conventional total knee arthroplasty (TKA). METHODS: We retrospectively analyzed data from 88 patients who underwent primary unilateral TKA for knee osteoarthritis between April 2024 and December 2024. The AI-robotic group (n = 44) received AI-assisted preoperative planning and robot-assisted TKA, while the traditional group (n = 44) underwent conventional 2D templating and manual TKA. Key metrics included preoperative prosthesis prediction accuracy, intraoperative and postoperative blood loss, osteotomy time, postoperative radiographic alignment, and functional scores. RESULTS: The AI-robotic group showed significantly higher prosthesis prediction accuracy (femoral: 79.5% vs. 52.3%, P = 0.023; tibial: 84.1% vs. 61.4%, P = 0.042), shorter osteotomy time (15.24 ± 4.71 vs. 18.43 ± 4.76 min, P = 0.002), reduced intraoperative blood loss (197.41 ± 78.41 vs. 234.35 ± 74.53 mL, P = 0.026), and lower 72-hour total blood loss (1022.96 ± 226.14 vs. 1118.71 ± 193.30 mL, P = 0.036). Postoperative lateral femoral component (LFC) angles were superior in the AI-robotic group (5.87 ± 2.18° vs. 6.91 ± 2.10°, P = 0.025). At 6 weeks, the AI-robotic group had better VAS pain scores (2.27 ± 1.12 vs. 2.84 ± 1.22, P = 0.029) and HSS scores (61.57 ± 4.40 vs. 59.59 ± 3.80, P = 0.027). CONCLUSION: AI-assisted preoperative planning with robotic TKA improves prosthesis sizing accuracy, reduces perioperative blood loss and 72 h total blood loss, and enhances early functional outcomes compared to conventional methods. These findings support AI-robotic integration as a precision solution for TKA, particularly in complex cases.