Abstract
Background: This study aimed to determine whether the iAssist navigation system (NAV) could improve the accuracy of restoring mechanical axis (MA), component positioning, and clinical outcomes compared to conventional (CON) total knee arthroplasty (TKA). Methods: A total of 301 consecutive patients (NAV: 27, CON: 274) were included. A 1:4 propensity score matching (PSM) was performed between the two groups according to preoperative demographic and clinical parameters. The postoperative MA, femoral coronal angle (FCA), femoral sagittal angle (FSA), tibial coronal angle (TCA) and tibial sagittal angle (TSA) were compared. Absolute deviations of aforementioned angles were calculated as the absolute value of difference between the exact and ideal value and defined as appropriate if within 3°, otherwise regarded as outliers. Additional clinical parameters, including the Knee Society knee and function scores (KSKS and KSFS) and range of motion (ROM), were assessed at the final follow-up (mean follow-up time was 21.88 and 21.56 months respectively for NAV and CON group). Results: A total of 98 patients/102 knees were analyzed after the PSM (NAV: 21 patients/24 knees, CON: 77 patients/78 knees). In the NAV group, the mean MA, FCA and TSA were significantly improved (p = 0.019, 0.006, <0.001, respectively). Proportions of TKAs within a ±3°deviation were significantly improved in all the postoperative radiological variables except for TCA (p = 0.003, 0.021, 0,017, 0.013, respectively for MA, FCA, FSA, and TSA). The absolute deviations of FSA and TSA were also significantly lower in the NAV group (p = 0.016, 0.048, respectively). In particular, no significant differences were found in either mean value, absolute deviation or outlier ratio of TCA between two groups. For the clinical outcomes, there were no significant differences between two groups, although KSKS, KSFS and ROM (p<0.01, respectively) dramatically improved compared to baseline. Conclusions: We suggested that the iAssist system could improve the accuracy and precision of mechanical alignment and component positioning without significant improvement of clinical outcomes. Further long-term high-quality studies are necessary to validate the results.
Portfolio Optimization with a Mean–Absolute Deviation–Entropy Multi-Objective Model
