Quality Assessment of Computer-Assisted Navigation Knee Arthroplasty Studies

Computer-navigated total knee arthroplasty (TKA) seeks to improve component alignment and reduce postoperative complications versus conventional TKA. However, the quality of studies evaluating outcomes varies. This review systematically assesses the methodological quality of randomized controlled trials (RCTs) comparing computer-navigated to conventional TKA using established quality assessment tools.

A systematic review was conducted by searching PubMed, Ovid (Embase), and MEDLINE in April 2024 using the terms "Computer Navigation and Knee Arthroplasty" or "Computer Assisted and Knee Arthroplasty." A total of 119 RCTs met the inclusion criteria. Trial quality was evaluated using the transformed Detsky index, which assesses reporting completeness, and the modified Cochrane risk-of-bias tool, which evaluates methodological rigor and biases.

Of the 119 RCTs, 6.7% were from North America and 42% were from Asia. Single-center trials comprised 78%. The mean transformed Detsky score was 92%, with 98% of studies classified as high quality, reflecting strong adherence to reporting guidelines. Scores improved over time (P = 0.003) and were higher in multicenter studies (P = 0.034), with no differences by trial location (P = 0.24) or primary outcome (P = 0.19). However, the mean modified Cochrane risk-of-bias score was 6.2, with 27% rated as high quality, indicating deficiencies in allocation concealment, blinding, and bias mitigation. Modified Cochrane risk-of-bias scores improved over time (P = 0.027) and varied by location (P < 0.001), with the Australian trials scoring highest and European trials scoring lowest. There were no differences found between single- and multicenter trials (P = 0.067) or among primary outcomes (P = 0.36).

While RCT-reported standards have improved, methodological weaknesses persist. Future trials should emphasize robust randomization, blinding, and adequate sample sizes to strengthen validity. Multicenter collaborations, standardized reporting, and increased transparency in industry-funded research are essential for improving quality. Addressing these limitations will ensure reliable evidence for TKA decision-making.