Faculty Bibliography

BACKGROUND:There is a growing number of patients who undergo multiple primary hip and knee joint arthroplasties during their lifetime. Whether patients who have multiple replaced joints are at an increased long-term risk of periprosthetic joint infection (PJI) is not known. The purpose of this study was to compare rates of PJI in patients who have more than one primary arthroplasty. METHODS:We reviewed 36,129 patients who underwent primary total joint arthroplasty at a single institution from 2011 to 2024. Patients were categorized as having one to four primary hip or knee arthroplasties. The PJI incidence was compared using Chi-square testing and binary logistic regressions, and multivariate models adjusted for sex, body mass index, diabetes, renal disease, smoking status, and Charlson Comorbidity Index (CCI). Sub-analyses compared patients who had one versus two, three, and four arthroplasties. RESULTS:When comparing patients who had one, two, three, or four primary joint arthroplasties, there was no significant difference in the rates of PJI between groups (P = 0.112). Multivariate analyses showed no statistically significant association between the number of arthroplasties and PJI (adjusted odds ratio (OR) for two, three, and four arthroplasties versus one: 1.34, 95% confidence interval (CI) 1.02 to 1.74, P = 0.083; 1.98, 95% CI 0.77 to 4.12, P = 0.105; 1.57, 95% CI 0.09 to 7.24, P = 0.657, respectively). Sub-analyses comparing one versus three and one versus four arthroplasties showed no significant differences. CONCLUSION/CONCLUSIONS:In this single-institution cohort, additional primary hip or knee arthroplasties did not appear to substantially increase PJI risk. These findings suggest a potential trend that requires confirmation with larger, prospective, multicenter, or registry-based studies. Nevertheless, these results provide preliminary evidence to inform patient counseling and guide future research on the risks of multiple arthroplasties.

INTRODUCTION/BACKGROUND:The integration of computer-assisted navigation systems (CASs) in total knee arthroplasty (TKA) procedures has gained popularity in recent years. However, additional validation of the accuracy of CAS feedback is necessary. We used short-length and full-length postoperative radiographs to quantify the differences between alignment parameters measured by a novel imageless CAS and alignment outcomes as evidenced on postoperative radiographs. MATERIALS AND METHODS/METHODS:A retrospective analysis was conducted on prospectively collected data from a cohort of patients undergoing navigated primary TKA. Fifty-eight patients had met inclusion criteria, and intraoperative CAS measurements were obtained from device recordings. Alignment parameters were measured digitally and included femorotibial angle on short-length films and hip-knee-ankle axis, mechanical lateral distal femoral angle (mLDFA), and mechanical medial proximal tibial angle (mMPTA) on full-length films. These were compared between CAS and radiograph measurements using a 2-tailed t test. RESULTS:The mean mLDFA measured by the CAS was 0.7° ± 1.1°, compared with 1.3° ± 1.4° as measured on full-body radiographs (P = .1). The mean mMPTA measured by the CAS was 0.2° ± 1.0°, compared with 0.9° ± 1.4° as measured on full-body radiographs (P = .06). On average, radiograph and CAS measurements differed by 0.5° ± 1.5° for mLDFA and 0.7° ± 1.5° for mMPTA. The average postoperative hip-knee-ankle axis was 177.6° ± 2.1°, and the average femorotibial angle was 176.0° ± 9.6° as measured on radiographs. CONCLUSION/CONCLUSIONS:No significant differences in either average or individual measured values for mLDFA or mMPTA were observed between the intraoperative CAS measurements and alignment outcomes postoperatively. Our data highlight the clinical utility of CASs to accurately achieve intended TKA alignment objectives.

Genetics is a burgeoning field within adult reconstructive surgery. Genome-wide sequencing has identified genetic variants found to be associated with not only the development of osteoarthritis but also arthroplasty-related complications, such as aseptic loosening, prosthetic joint infection, arthrofibrosis, and postoperative pain. Examples include newer technology, such as next-generation sequencing, in diagnosing culture-negative prosthetic joint infection. Genetics drives new therapeutic technologies, such as gene therapy, gene-editing, and bacteriophage treatment. Although still rare, a handful of phase 3 clinical trials of gene therapy for osteoarthritis have begun to demonstrate efficacy with low-risk profiles. As the field continues to grow, public and professional buy-in as well as cost present challenges.

BACKGROUND/UNASSIGNED:Technological advancements in total hip arthroplasty (THA), including robotic-assisted (RA-THA) and navigation-assisted (NA-THA) techniques, aim to improve outcomes. However, impact on recovery timing remains unclear. This study examined whether these technologies reduce the time to reach the minimal clinically important difference (MCID) on the Hip Disability and Osteoarthritis Outcome Score for Joint Replacement compared with conventional THA. METHODS/UNASSIGNED:This retrospective study analyzed osteoarthritic THA patients (01/2020-04/2023) who completed preoperative and postoperative Hip Disability and Osteoarthritis Outcome Score for Joint Replacement questionnaires. The exclusion criteria included bilateral procedures or revision within 1 year. MCID was defined using anchor-based (23 points) and distribution-based thresholds (7.6 points). Multivariable interval-censored accelerated failure time models assessed time to MCID. RESULTS/UNASSIGNED:= .140). CONCLUSIONS/UNASSIGNED:Anchor-based MCID demonstrated comparable recovery times across RA, NA, and conventional THA, suggesting no patient-perceived advantage with technology. Distribution-based thresholds indicated RA-THA achieved faster statistically significant improvement, though the relevance remains uncertain.

INTRODUCTION/BACKGROUND:Obtaining an accurate preoperative diagnosis of periprosthetic joint infections (PJI) is challenging, making differentiating between septic and aseptic failures difficult. We sought to identify the value of common serum biomarkers and evaluate the accuracy of three ratios in the diagnosis of PJI after primary total knee arthroplasty (TKA): albumin-globulin ratio (AGR), C-reactive protein-albumin ratio (CAR), and C-reactive protein-AGR ratio (CAGR). METHODS:Patients undergoing PJI and aseptic revisions after TKA between 2011 and 2021 were retrospectively reviewed at a single institution. Only patients who had reported serum white blood cell (WBC), C-reactive protein (CRP), erythrocyte sedimentation rate (ESR), albumin (Alb), and total protein (TP) were included. Areas under the curve (AUCs), which optimize diagnostic performance by balancing sensitivity and specificity at a specific cutoff, were calculated for each individual biomarker and the three ratio groups: AGR = Alb / [TP - Alb], CAR = CRP / Alb, and CAGR = CRP / AGR). Higher AUCs indicate improved identification of PJI while reducing misclassification. RESULTS:Out of the 126 included cases, 89 were confirmed PJIs and 37 were aseptic revisions. Among the single and combination serum biomarkers, the AUCs were as follows: CRP (0.85), ESR (0.76), Alb (0.81), AGR (0.78), CAR (0.87), and CAGR (0.87). The CAR demonstrated excellent accuracy at a cutoff of 2.46, with a sensitivity of 0.74 and specificity of 0.84. CAGR also demonstrated excellent accuracy at a cutoff of 7.09, with a sensitivity of 0.80 and specificity of 0.78. CONCLUSION/CONCLUSIONS:The CRP, CAR, and CAGR showed an excellent diagnostic accuracy as markers for PJI. In patients undergoing revision TKA, common serum biomarkers such as Alb, TP, CRP, and ESR can be obtained, and CAR or CAGR ratios can be calculated to aid in the diagnosis of PJI, especially in cases where synovial analysis is inconclusive, allowing for better clinical decision-making.

BACKGROUND:Patients who undergo primary total knee arthroplasty (TKA) may return to work at variable times following surgery, the timeline for which is partly affected by the physical intensity of their occupation. The purpose of this study was to evaluate patient satisfaction and limitations when returning to work following TKA. METHODS:This retrospective review surveyed patients undergoing primary TKA between June 2011 and January 2022, with at least 1 year of follow up, regarding return to work. Of the 914 respondents, 507 (55.5 %) worked preoperatively and were stratified into high intensity (HI) (i.e., laborer, construction), standard intensity (SI) (i.e., walking, climbing stairs), or low intensity (LI) (i.e., sedentary desk jobs) groups. Baseline characteristics and survey responses were compared across groups. Among those who worked preoperatively, 35 (6.9 %), 213 (42 %), and 259 (51.1 %) were in the HI, SI, and LI groups, respectively. RESULTS:Of the 507 patients who worked prior to TKA, 447 (88.2 %) returned to work after surgery and 60 (11.8 %) did not. The HI group was comprised of more young males and more smokers than the SI and LI groups. In the LI group, 30 % returned within 1 month following surgery and an additional 44 % within 2 months. Similarly in the SI group, 11 % returned to work in less than 1 month with an additional 39 % returning within 2 months. In the HI group, 4 % returned within the first month and additional 42 % returned within 2 months. HI workers were more commonly hindered in their return (HI: 30.8 %, SI: 23.1 %, LI: 7.7 %), 'moderately declined' in their work ability (HI: 23.1 %, SI: 9.7 %, 3.0 %), and 'very unsatisfied' with their return (HI: 11.5 %, SI: 10.8 %, LI: 8.1 %). CONCLUSION/CONCLUSIONS:TKA leads to improvements in work function and satisfaction across all intensity levels, but HI work is associated with longer recovery times and comparatively lower return-to-work satisfaction compared to SI and LI groups.

INTRODUCTION/BACKGROUND:Social support improves outcomes after total hip and knee arthroplasty (THA/TKA), but the demands on informal caregivers, especially as surgeries transition to outpatient care, are understudied. This study strived to assess caregiver burden, predictors, and implications following joint arthroplasty. METHODS:This prospective cohort study enrolled 185 patient-caregiver dyads undergoing primary THA or TKA for osteoarthritis at a tertiary academic center. Caregivers completed assessments at four weeks postoperatively, including the Caregiver Strain Index (CSI) and Appraisal of Caregiving Scale (ACS), which measures perceived benefit, threat, and stress. Demographic, socioeconomic, and caregiving-related variables were collected. Multivariate linear regression identified factors associated with caregiver strain and experiences. Caregivers had a mean age of 64 years (range, 52.3 to 76.3), and 60% were women. Most (72.4%) were spouses, and 46.5% were retired. RESULTS:The CSI scores showed considerable strain, especially among women caregivers (β = 1.29, P = 0.001), those who had higher daily time commitment postoperatively, and those who had lower preoperative preparedness. Regarding employment status, 7% worked part-time, and 3.2% were homemakers. Among ACS subscales, non-White race (β = 0.31, P = 0.035) and homemaker status (β = 0.65, P = 0.049) were positively associated with perceived benefit, while lower preparedness predicted higher perceived threat. Caregiver age (β = 0.0217, P = 0.004), higher initial social support (β = 0.013, P = 0.001), and preparedness (β = 0.19, P = 0.016) predicted higher stress appraisals. Part-time employment was associated with lower stress (β = -0.47, P = 0.042). CONCLUSION/CONCLUSIONS:Caregiver burden after joint arthroplasty is substantial and influenced by sex, age, race, employment, social support, and preparedness. Targeted interventions addressing these factors are needed to mitigate strain in at-risk caregivers and improve surgical recovery for patients.