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.

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.

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.

INTRODUCTION/BACKGROUND:There is increased awareness of socioeconomic disparities among total hip arthroplasty (THA) patients. Most studies contain small sample sizes and few control for confounding variables. This study aims to evaluate postoperative outcomes and survivorship after THA in patients of different races/ethnicities. METHODS:Patients who underwent a primary THA were identified in the New York Statewide Planning and Research Cooperative System (SPARCS) database. Patients were stratified into 4 groups: White, Black, Hispanic, or Asian. Categorical variables and continuous variables were compared, and revision free survival was calculated using Kaplan Meier survival analysis. Multivariate Cox proportional hazard regression was used to calculate revision hazard ratios. RESULTS: = 0.021). There were no significant differences in the cumulative revision event rate up to 10 years postoperatively. CONCLUSIONS:Non-White patients are significantly more likely to have worse short-term outcomes and complications. However, overall rates of revision at 1 year are similar across these groups, with a slightly lower rate of revision in Black patients after controlling for confounding factors.

INTRODUCTION/BACKGROUND:While the number of absolute and relative contraindications to total joint arthroplasty (TJA) has gradually decreased, active cancer patients have traditionally been challenging surgical candidates. We sought to compare perioperative and two-year postoperative clinical outcomes of patients with and without active cancer. METHODS:Patients over 18 years with active cancer undergoing primary, unilateral TJA from 2017 to 2023 at a single urban academic center were reviewed for a minimum two-year follow-up. Cancer status, type, and stage were confirmed manually. 68 cancer patients were propensity-matched 3:1 to 204 non-cancer patients from a pool of 9,382 based on age, sex, BMI, smoking status, race, and ASA class. Demographic, perioperative, and clinical data were analyzed using t-tests, Chi-square, and ANOVA. Subgroup analyses compared cancer patients receiving active therapy versus those not on treatment. RESULTS:There were no significant demographic differences between groups, except Charlson Comorbidity Index (P < 0.001). The most common cancers were breast (22%) and prostate (20%). There were no differences in discharge disposition (P = 0.20), operative time (P = 0.87), or length of stay (P = 0.29). The all-cause revision rate (including infection) was higher in patients with active cancer (7.4% vs. 2.5%), though not statistically significant (P = 0.15; Power = 46.5%). Of the various causes for revision, infection was significantly more likely in cancer patients than other causes compared (4.4% vs. 0%, P = 0.003). When analyzing only the active cancer group, those receiving cancer therapy had higher revision rates, though this was not statistically significant (11.1% vs. 6.0%, P = 0.487). DISCUSSION/CONCLUSION/CONCLUSIONS:Despite often being excluded from arthroplasty studies, active cancer patients demonstrated comparable overall outcomes after primary TJA. Although infection-related revisions were more common, they were effectively treated. With proper preoperative optimization and multidisciplinary care, TJA can be safely performed in selected active cancer patients.

BACKGROUND:Obesity is a known risk factor for complications after total hip arthroplasty (THA), with societal guidelines recommending surgical delay for patients above body mass index (BMI) targets. Consequently, patients are motivated to reach BMI targets before the office visit, discussing surgical booking. Our study investigates BMI fluctuations between surgical booking and the surgery date and whether these fluctuations have implications for peri- and postoperative outcomes. METHODS:We retrospectively reviewed our institutional database for elective, primary, unilateral THA from 2015 to 2024 with a minimum 90-day follow-up. The cohort was stratified into three groups by percent BMI change from booking date to THA date: Group 1, decrease in BMI; Group 2, 0 to 5% increase in BMI; and Group 3, > 5% increase in BMI. Baseline demographic factors, as well as peri- and postoperative outcomes, were compared. A multivariate regression analysis evaluated risk factors for interval change in BMI. We reviewed 10,400 THA patients who had an average 62-day delay between booking and surgery dates, where 44.2, 42.2, and 13.6% were allocated to Groups 1, 2, and 3, respectively. RESULTS:Operative time, length of stay, and discharge to a rehab facility were significantly higher in Group 3 compared to the others. There were no significant differences seen in 90-day outcomes, including emergency department (ED) visits, readmissions, or revision rates. Multivariate regression analyses identified that elevated BMI at the time of surgery predicted increased septic revision incidence (OR [odds ratio]: 1.1, P < 0.001). Surgical delay and BMI change between booking and surgery did not influence all-cause and septic revision rates. CONCLUSION/CONCLUSIONS:Our study is the first to evaluate preoperative BMI fluctuations between the booking date and surgery date. We found that most patients (55.8%) gained weight, with 13.6% increasing > 5% BMI. Importantly, these weight changes do not impact short-term complications or revision rates, comforting THA surgeons who see interval weight gain on the day of surgery.

BACKGROUND:Return to sports is a concern for many patients undergoing total hip arthroplasty (THA). As younger, active patients increasingly undergo THA, identifying factors that influence athletic recovery is critical. Although prior work has reported favorable outcomes, large-scale studies comparing return rates across both surgical approaches and sport types remain limited. METHODS:We retrospectively analyzed 1,115 athletically participant THA patients and compared rates of returning to sports up to one year postoperatively. Survey data captured sport type, participation at four time points, frequency, exertion, and perceived recovery. Patients were stratified by surgical approach: posterior (PA) (n = 519), anterior (AA) (n = 556), and lateral (LA) (n = 50). RESULTS:Preoperatively, 45.2% of patients were active in at least one sport versus 43.7% at one year postoperatively; 73.2% of preoperative athletes returned, and 23.3% of those previously inactive took up sports. Return-to-sport rates were 68.1, 77.0, and 81.8% for PA, AA, and LA, respectively (Chi-square = 3.42, P = 0.181). There were no significant differences between AA and PA, and the lateral approach was not statistically comparable due to a smaller sample size. Low-impact sports had significantly higher return rates than high-impact sports (72.4 versus 50.0%; P < 0.001). At survey completion (> one year postoperatively), satisfaction rates were high across all sports, and activity restrictions were reported by about one in five patients, regardless of approach. Sport-specific outcomes showed that most patients maintained or improved performance. CONCLUSION/CONCLUSIONS:Patients undergoing THA can expect high return rates and satisfaction with athletic endeavors. Surgical approach generally does not affect return-to-sport outcomes after THA. Most patients, regardless of approach, resumed or exceeded preoperative activity. In addition to high return rates among previously active patients, many previously inactive patients participated in sports after THA, highlighting the role of THA in enabling sport resumption and participation.