Faculty Bibliography

The rise in solid organ transplantations (SOTs) has led to increased long-term survival and also a higher incidence of joint degenerative diseases, necessitating more total joint arthroplasties (TJAs). SOT recipients face unique challenges, including immunosuppression, infection risks, and altered bone metabolism, requiring meticulous perioperative management. Despite higher complication rates, TJAs in SOT patients provide significant pain relief and functional improvement. Preoperative evaluation, tailored antibiotic prophylaxis, and careful implant selection are crucial. Multidisciplinary collaboration is essential to optimize outcomes, reduce complications, and improve quality of life for this high-risk population.

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.

PURPOSE/OBJECTIVE:To investigate the incidence and risk factors for dressing-induced allergic contact dermatitis (DIACD) following total hip and knee arthroplasty (THA and TKA, respectively) across different dressings and sealants. METHODS:A retrospective review was conducted of patients who underwent primary, elective THA or TKA between 2019 and 2024 with ≥ 90 days of follow-up. Incidences of DIACD were identified by reviewing medical records for "allergy" diagnoses and use of antihistamines or corticosteroids within 30 days postoperatively. Patient characteristics, prior exposure, treatment, dressing type, and allergy history were analyzed. RESULTS:A total of 61 (0.3%) of the 23,396 investigated patients developed a DIACD on average 12.2 ± 7.3 days postoperatively. Overall, 41% had a preoperative allergy (excluding seasonal), and 55.7% were treated with topical or low-dose oral antihistamines and corticosteroids. The majority (41%) of the DIACD involved mesh-adhesive dressings, and a liquid skin adhesive (2-octyl cyanoacrylate) was also used in 41% of cases, often in combination with the primary dressing. Of the 61 DIACD patients, 24 (39.3%) had previously undergone THA or TKA, and nearly half of these (n = 11, 45.8%) had been exposed to the same dressing without prior occurrence of DIACD. DIACD patients were significantly more likely to have undergone TKA (73.8 vs. 58.3%, p = 0.015) and to have never smoked (75.4 vs. 58.4%, p = 0.014). The effect sizes of these findings were negligible (Cramer's V = 0.016 and 0.019, respectively). CONCLUSIONS:The incidence of DIACD following joint arthroplasty is low (0.3%) but remains a frustrating complication, primarily occurring two weeks postoperatively, with mesh-adhesive dressings most frequently implicated. Patients with prior exposure to dressings, those undergoing TKA, and non-smokers are at higher risk. Identifying at-risk patients can guide dressing selection and application.

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.

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.

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/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.