Background Previous studies have demonstrated that the administration of antibiotics to patients before performing diagnostic testing for periprosthetic joint infection (PJI) can interfere with the accuracy of test results. Although a single-institution study has suggested that alpha-defensin maintains its concentration and sensitivity even after antibiotic treatment, this has not yet been demonstrated in a larger multiinstitutional study. Questions/purposes (1) For the evaluation of PJI, is prior antibiotic administration associated with decreased alpha-defensin levels? (2) When prior antibiotics are given, is alpha-defensin a better screening test for PJI than the traditional tests (erythrocyte sedimentation rate [ESR], C-reactive protein [CRP], fluid white blood cells, fluid polymorphonuclear cells [PMNs], and fluid culture)? Methods This retrospective study included data from 106 hip and knee arthroplasties with Musculoskeletal Infection Society-defined PJI from four centers. Of the 106 patients in this study, 30 (28%) were treated with antibiotics for PJI before diagnostic workup (ABX group), and 76 (72%) were not treated before the diagnostic workup (NO-ABX group). There were no differences in age, sex, joint, culture-negative rate, or bacteriology between groups. The patients in the ABX group had antibiotics initiated by physicians who commenced care before assessment for PJI by the treating surgeon's service. We compared the alpha-defensin levels and sensitivity between the ABX and NO-ABX groups. Additionally, the sensitivity of the alpha-defensin test was compared to that of traditional tests for PJI among patients on antibiotics. Results The administration of antibiotics before performing the alpha-defensin test for PJI was not associated with a decreased median alpha-defensin level (ABX group, median 4.2 [range, 1.79-12.8 S/CO] versus NO-ABX, median 4.9 [range, 0.5-16.8 S/CO], difference of medians: 0.68 S/CO [95% confidence interval {CI}, −0.98 to 1.26], p = 0.451). Furthermore, the alpha-defensin test had a higher sensitivity (100%; 95% CI, 88.4%-100.0%) in diagnosing PJI among patients on antibiotics when compared with the ESR (69.0% [95% CI, 49.17%-84.72%], p = 0.001), the CRP (79.3% [95% CI, 60.3%-92.0%], p = 0.009), the fluid PMN% (79.3% [95% CI, 60.3%-92.0%), p = 0.009), and fluid culture (70.0% [95% CI, 50.6%-85.3%], p = 0.001). Conclusions The alpha-defensin test maintains its concentration and sensitivity for PJI even in the setting of antibiotic administration. Furthermore, among patients with PJI on antibiotics, the alpha-defensin tests demonstrated a higher sensitivity in detecting PJI when compared with the ESR, CRP, fluid PMN%, and fluid culture. The high sensitivity of the alpha-defensin test, even in the setting of prior antibiotic treatment, provides excellent utility as a screening test for PJI. Level of Evidence Level III, diagnostic study.

* Robotic technology used in orthopaedics can be classified on the basis of direct and indirect action and according to the mechanism of cutting, including autonomous, haptic, and boundary control. * Robotics have been used in multiple orthopaedic subspecialties including spine, total joint arthroplasty, trauma, shoulder, and foot and ankle. * Advantages of using robotic technology in orthopaedics include the possibility of improving implant placement (e.g., reducing outliers), accessing certain anatomic areas, reducing complications, decreasing fluoroscopy use, and performing remote surgery. * Disadvantages of using robotics in orthopaedics include increased costs, the need for updated software, the surgeon learning curve and increased operative time, imaging for preoperative templating, potential incorrect placement of implants with poor input of data from the surgeon, and possibly no difference in long-term outcomes.

➤ There is a growing body of evidence implicating psychosocial factors, including anxiety, depression, kinesiophobia, central sensitization, and pain catastrophizing, as negative prognostic factors following total knee arthroplasty (TKA). ➤ Symptoms of anxiety and depression likely represent risk factors for negative outcomes in patients undergoing TKA. However, few studies have assessed the impact of preoperative interventions for these conditions on postoperative outcomes. ➤ The Tampa Scale of Kinesiophobia and the Central Sensitization Inventory have demonstrated value in the diagnosis of kinesiophobia and central sensitization. Higher preoperative indices of kinesiophobia and central sensitization predict worse patient-reported outcomes postoperatively. ➤ Although evidence is limited, cognitive-behavioral therapy for kinesiophobia and duloxetine for central sensitization may help to diminish the negative impact of these preoperative comorbidities. It is important to note, however, that outside the realm of TKA, cognitive-behavioral therapy has been recognized as a more effective treatment for central sensitization than medical treatment. ➤ Awareness of these issues will allow surgeons to better prepare patients regarding postoperative expectations in the setting of a comorbid psychosocial risk factor. Further research into the role of preoperative assessment and possible treatment of these conditions in patients undergoing TKA is warranted.

Background: Implant malalignment may predispose patients to prosthetic failure following total knee arthroplasty (TKA). A more thorough understanding of the surgeon-specific factors that contribute to implant malalignment following TKA may uncover actionable strategies for improving implant survival. The purpose of this study was to determine the impact of surgeon volume and training status on malalignment. Methods: In this retrospective multicenter study, we performed a radiographic analysis of 1,570 primary TKAs performed at 4 private academic and state-funded centers in the U.S. and U.K. Surgeons were categorized as high-volume (≥50 TKAs/year) or low-volume (±3° deviation from the neutral axis; and PSA, 7° of flexion for cruciate-retaining or 5° of flexion for posterior-stabilized TKAs. “Far outliers” were defined as measurements falling >± 2° outside of these ranges. The proportions of outliers were compared between the groups using univariate and multivariate analyses. Results: When comparing the high and low-volume non-trainee groups using univariate analysis, the proportions of knees with outlier measurements for the PTA (5.3% versus 17.4%) and PSA (17.4% versus 28.3%) and the proportion of total outliers (11.8% versus 20.7%) were significantly lower in the high-volume group (all p < 0.001). The proportions of DFA (1.9% versus 6.5%), PTA (1.8% versus 5.7%), PSA (5.5% versus 12.6%), and total far outliers (3.1% versus 8.3%) were also significantly lower in the high-volume non-trainee group (all p < 0.001). Compared with the trainee group, the high-volume non-trainee group had significantly lower proportions of DFA (12.6% versus 21.6%), PTA (5.3% versus 12.0%), PSA (17.4% versus 33.3%), and total outliers (11.8% versus 22.3%) (all p < 0.001) as well as DFA (1.9% versus 3.9%; p = 0.027), PSA (5.5% versus 12.6%; p < 0.001), and total far outliers (3.1% versus 6.4%; p = 0.004). No significant differences were identified when comparing the low-volume non-trainee group and the trainee group, with the exception of PTA outliers (17.4% versus 12.0%; p = 0.041) and PTA far outliers (5.7% versus 2.6%; p = 0.033). Findings from multivariate analysis accounting for the effects of patient age, body mass index, and individual surgeon demonstrated similar results. Conclusions: Low surgical volume and trainee status were risk factors for outlier and far-outlier malalignment in primary TKA, even when accounting for differences in individual surgeon and patient characteristics. Trainee surgeons performed similarly, and certainly not inferiorly, to low-volume non-trainee surgeons. Even among high-volume non-trainees, the best-performing cohort in our study, the proportion of TKA alignment outliers was still high. Level of Evidence: Therapeutic Level III. See Instructions for Authors for a complete description of levels of evidence.

Background: Alignment outcomes and their impact on implant survival following unicompartmental knee arthroplasty (UKA) are unclear. The purpose of this study was to assess the implant survival and radiographic outcomes after UKA as well as the impact of component alignment and overhang on implant survival. Methods: We performed a retrospective analysis of 253 primary fixed-bearing and mobile-bearing medial UKAs from a single academic center. All UKAs were performed by 2 high-volume fellowship-trained arthroplasty surgeons. UKAs comprised ±10° deviation from neutral), FSA (>15° of flexion), TCA (>±5° deviation from neutral), and TSA (>±5° deviation from 7°). “Far outliers” were an additional >±2° of deviation. Outliers for overhang were identified as >3 mm for anterior overhang, >2 mm for posterior overhang, and >2 mm for medial overhang. Results: Among patients with a failed UKA, revision was performed at an average of 3.7 years (range, 0.03 to 8.7 years). The cumulative revision rate was 14.2%. Kaplan-Meier survival analysis demonstrated 5 and 10-year survival rates of 88.0% (95% confidence interval [CI] = 82.0% to 91.0%) and 70.0% (95% CI = 56.0% to 80.0%), respectively. Only 19.0% (48) of the UKAs met target alignment for all 4 alignment measures, and only 72.7% (184) met all 3 targets for overhang. Only 11.9% (30) fell within all alignment and overhang targets. The risk of implant failure was significantly impacted by outliers for FCA (failure rate = 15.4%, p = 0.036), FSA (16.2%, p = 0.028), TCA (17.9%, p = 0.020), and TSA (15.2%, p = 0.034) compared with implants with no alignment or overhang errors (0%); this was also true for far outliers (p < 0.05). Other risk factors for failure were posterior overhang (failure rate = 25.0%, p = 0.006) and medial overhang (38.2%, p < 0.001); anterior overhang was not a significant risk factor (10.0%, p = 0.090). Conclusions: The proportions of UKA revisions and alignment outliers were greater than expected, even among high-volume arthroplasty surgeons performing an average of 14.2 UKAs per year (just below the high-volume UKA threshold of 15). Alignment and overhang outliers were significant risk factors for implant failure. Level of Evidence: Therapeutic Level IV. See Instructions for Authors for a complete description of levels of evidence.