Faculty Bibliography

INTRODUCTION/BACKGROUND:Preoperative planning of total hip arthroplasty (THA) using two-dimensional low-dose (2DLD) full-body imaging has gained popularity in recent years. The low-dose imaging system is said to produce a calibrated image with constant 1:1 magnification. However, the planning software used in conjunction with those images may introduce variations in the degree of magnification in 2DLD imaging, and this has not yet been investigated. The purpose of the present study was to quantify any variation in 2DLD image to assess the need for image calibration when using conventional planning software. METHODS:Postoperative 2DLD images from 137 patients were retrospectively evaluated. Only patients who underwent THA for primary osteoarthritis were included in the study cohort. The femoral head diameter was measured by two independent observers using both Orthoview™ and TraumaCad™ planning software programs. Actual sizes of the femoral head implants were extracted from surgical reports to calculate image magnification. Magnification measurement reliability was calculated with the intra-class correlation coefficient (ICC) index. RESULTS:Image magnification varied among cases (mean 133%, range 129-135%). There was no statistical difference in mean image magnification among the various implant sizes (p = 0.8). Mean observer and inter-observer reliability was rated excellent. CONCLUSION/CONCLUSIONS:THA planning with 2DLD imaging is subject to variation in magnification as analyzed with conventional planning software in this series. This finding is of paramount importance for surgeons using 2DLD imaging in preparation for THA since errors in magnification could affect the accuracy of preoperative planning and ultimately the clinical outcome.

BACKGROUND:The lower morbidity and mortality rate associated with increased surgeon and hospital volume may also correlate with improved patient-reported outcome measures. The goal of this study was to determine the relationship between surgeon and hospital volume and patient-reported outcome measures after total knee arthroplasty (TKA) using American Joint Replacement Registry data. METHODS:Using American Joint Replacement Registry data from 2012 to 2020, 8,193 primary, elective TKAs with both preoperative and 1-year postoperative The Knee Injury and Osteoarthritis Outcome Score, Joint Replacement (KOOS-JR) scores were analyzed. This study was powered to detect the minimally clinical important difference (MCID). The main exposure variables were median annual surgeon and hospital volume. Tertiles were formed based on the median annual number of TKAs performed: low-volume surgeons (1 to 52), medium-volume (53 to 114), and high-volume (≥115); low-volume hospitals (1 to 283), medium-volume (284 to 602), and high-volume (≥603). The mean preoperative and 1-year postoperative KOOS-JR were compared. Multivariable logistic regression models were used to determine the effect of surgeon and hospital volume and demographics on achieving the MCID for KOOS-JR. RESULTS:The mean preoperative and 1-year postoperative KOOS-JR score for low-volume surgeons was 47.78 ± 13.50 and 77.75 ± 16.65, respectively, and 47.32 ± 13.73 and 76.86 ± 16.38 for low-volume hospitals. The mean preoperative and 1-year postoperative KOOS-JR score for medium-volume surgeons was 47.20 ± 13.46 and 76.70 ± 16.98, and 48.93 ± 12.50 and 77.15 ± 16.36 for medium-volume hospitals. The mean preoperative and 1-year postoperative KOOS-JR scores for high-volume surgeons were 49.08 ± 13.04 and 78.23 ± 16.72, and 48.11 ± 13.47 and 78.23 ± 17.22 for high-volume hospitals. No notable difference was observed in reaching MCID for KOOS-JR after adjustment for potential confounders. CONCLUSION/CONCLUSIONS:An increased number of TKA cases performed by a given surgeon or at a given hospital did not have an effect on achieving MCID for KOOS-JR outcomes.

BACKGROUND:Supervised machine learning techniques have been increasingly applied to predict patient outcomes after hip and knee arthroplasty procedures. The purpose of this study was to systematically review the applications of supervised machine learning techniques to predict patient outcomes after primary total hip and knee arthroplasty. METHODS:A comprehensive literature search using the electronic databases MEDLINE, EMBASE, Cochrane Central Register of Controlled Trials, and Cochrane Database of Systematic Reviews was conducted in July of 2021. The inclusion criteria were studies that utilized supervised machine learning techniques to predict patient outcomes after primary total hip or knee arthroplasty. RESULTS:Search criteria yielded n = 30 relevant studies. Topics of study included patient complications (n = 6), readmissions (n = 1), revision (n = 2), patient-reported outcome measures (n = 4), patient satisfaction (n = 4), inpatient status and length of stay (LOS) (n = 9), opioid usage (n = 3), and patient function (n = 1). Studies involved TKA (n = 12), THA (n = 11), or a combination (n = 7). Less than 35% of predictive outcomes had an area under the receiver operating characteristic curve (AUC) in the excellent or outstanding range. Additionally, only 9 of the studies found improvement over logistic regression, and only 9 studies were externally validated. CONCLUSION/CONCLUSIONS:Supervised machine learning algorithms are powerful tools that have been increasingly applied to predict patient outcomes after total hip and knee arthroplasty. However, these algorithms should be evaluated in the context of prognostic accuracy, comparison to traditional statistical techniques for outcome prediction, and application to populations outside the training set. While machine learning algorithms have been received with considerable interest, they should be critically assessed and validated prior to clinical adoption.

INTRODUCTION/BACKGROUND:Operating room air quality can be affected by several factors including temperature, humidity, and airborne particle burden. Our study examines the role of operating room (OR) size on air quality and airborne particle (ABP) count in primary total knee arthroplasty (TKA). MATERIALS AND METHODS/METHODS:We analyzed all primary, elective TKAs performed within two ORs measuring 278 sq ft. (small) and 501 sq ft. (large) at a single academic institution in the United States from April 2019 to June 2020. Intraoperative measurements of temperature, humidity, and ABP count were recorded. p values were calculated using t test for continuous variables and chi-square for categorical values. RESULTS:91 primary TKA cases were included in the study, with 21 (23.1%) in the small OR and 70 (76.9%) in the large OR. Between-groups comparisons revealed significant differences in relative humidity (small OR 38.5% ± 7.24% vs. large OR 44.4% ± 8.01%, p = 0.002). Significant percent decreases in ABP rates for particles measuring 2.5 μm (- 43.9%, p = 0.007) and 5.0 μm (- 69.0%, p = 0.0024) were found in the large OR. Total time spent in the OR was not significantly different between the two groups (small OR 153.09 ± 22.3 vs. large OR 173 ± 44.6, p = 0.05). CONCLUSIONS:Although total time spent in the room did not differ between the large and small OR, there were significant differences in humidity and ABP rates for particles measuring 2.5 μm and 5.0 μm, suggesting the filtration system encounters less particle burden in larger rooms. Larger studies are required to determine the impact this may have on OR sterility and infection rates.

BACKGROUND:Chronic prosthetic joint infection (PJI) is most frequently treated with 2-stage revision in conjunction with antibiotic treatment. The aims of this study were 1) to investigate the characteristics of patients who have recurrent infection following 2-stage revision for PJI and 2) to identify risk factors associated with treatment failure. METHODS:A multicenter retrospective review of 90 total knee arthroplasty (TKA) patients who underwent 2-stage revision for treatment of PJI from March 1, 2003 to July 31, 2019, and had recurrent PJI was conducted. The minimum follow-up was 12 months (median follow up of 2.4 years). Microorganisms, subsequent revision, PJI control status, and final joint status were collected. The infection-free survival after initial 2-stage revision was plotted utilizing the Kaplan-Meier method. RESULTS:Mean survival time to reinfection was 21.3 months (range, 0.3 to 160.5). There were 14 recurrent infections that were acute PJIs treated with debridement, antibiotics, and implant retention (DAIR), while 76 were chronic and treated with repeat 2-stage revision. The most common pathogen identified for both index and recurrent PJI was coagulase-negative Staphylococci. Pathogen persistence was observed in 14 (22.2%) of recurrent PJIs. In total, 61 (67.8%) patients possessed a prosthetic reimplantation at their most recent follow-up, and 29 (35.6%) patients required intervention following repeat 2-stage. CONCLUSION/CONCLUSIONS:Overall, 31.1% of the patients obtained infection control after treatment of a failed 2-stage revision due to PJI. The high rate of pathogen persistence and the relatively low survival time to recurrence suggests a need to more closely monitor PJIs cases within 2 years.

PURPOSE/OBJECTIVE:Soft tissue balancing is an important step in a total knee procedure, carried out manually, or using an indicator. The purpose of this study was to evaluate our design of 3D printed Balancer, and demonstrate how it could be used at surgery. PROCEDURES/METHODS:When inserted between the femur and tibia, the Balancer displayed the forces acting across the lateral and medial compartments, indicated by pointers at the end of the handle. A loading rig was used to measure the pointer deflections for different forces applied at different locations on the condyle surfaces. Repeatability and reproducibilty were evaluated. The Balancer was tested in six fresh knee specimens using a surgical simulation rig. MAIN FINDINGS/RESULTS:Pointer deflections of up to 12 millimeters occurred for less than 1 mm displacements at the condyle surfaces. Reproducibility tests showed a standard deviation of 14% at lower loads, reducing to only 4% at higher loads. Mean pointer deflections were within 8% for forces applied at ±10 mm AP, and +5/-3 mm in an ML direction, relative to the neutral contact point. In specimens, most lateral to medial force differences could be corrected by a 2° change in frontal plane angle of the tibial resection. Effects of ligament releases were also demonstrated. PRINCIPAL CONCLUSIONS/CONCLUSIONS:The 3D printed Balancer was easy to use, and provided the surgeon with lateral and medial force data over a full range of flexion, enabling possible corrective procedures to be specified.

BACKGROUND/UNASSIGNED:Total knee arthroplasty (TKA) procedures are expected to grow exponentially in the upcoming years, highlighting the importance of identifying preoperative risk factors that predispose patients to poor outcomes. The present study sought to determine if preoperative healthcare events (PHEs) influenced outcomes following TKA. METHODS/UNASSIGNED:This was a retrospective review of all patients who underwent TKA at a single institution from June 2011 to April 2022. Patients who had a PHE within 90 days of surgery, defined as an emergency department visit or hospital admission, were compared to patients with no history of PHE. Patients who underwent revision, nonelective, and/or bilateral TKA were excluded. Chi-squared analysis and independent sample t-tests were used to determine significant differences between demographic variables. All significant covariates were included in binary logistic regressions used to predict discharge disposition, 90-day readmission, and 1-year revision. RESULTS/UNASSIGNED: = .004) compared to patients without a PHE. CONCLUSIONS/UNASSIGNED:Our results demonstrate that PHEs put patients at significantly greater risk of facility discharge, 90-day readmission, and 1-year revision. Moving forward, consideration of elective surgery scheduling in the context of a recent PHE may lead to improved postoperative outcomes. LEVEL III EVIDENCE/UNASSIGNED:Retrospective Cohort Study.

BACKGROUND:Many studies have demonstrated that in patients whose primary language is not English, outcomes after orthopaedic surgery are worse compared to primary English speakers. The goal of this study was to compare perioperative outcomes in patients undergoing total knee arthroplasty (TKA) who prefer English as their first language versus those who prefer a different language. METHODS:We retrospectively reviewed all patients who underwent primary TKA from May 2012 to July 2021. Patients were separated into two groups based on whether English was their preferred primary language (PPL). Of the 13,447 patients who underwent primary TKA, 11,290 reported English as their PPL and 2,157 preferred a language other than English. Patients whose PPL was not English were further stratified based on whether they requested interpreter services. Multiple regression analyses were performed to determine the significance of perioperative outcomes while controlling for demographic differences. RESULTS:Our analysis found that non-English PPL patients had significantly lower rates of readmission (p=0.040), overall revision (p=0.028), and manipulation under anesthesia (MUA; p=0.025) within 90 days postoperatively. Sub analyses of the non-English PPL group showed that those who requested interpreter services had significantly lower one year revision (p<0.001) and overall MUA (p=0.049) rates. CONCLUSION/CONCLUSIONS:Our results demonstrate that TKA patients who communicated in English without an interpreter were significantly more likely to undergo revision, readmission, and MUA. These findings may suggest that language barriers may make it more difficult to identify postoperative problems or concerns in non-English speakers, which may limit appropriate postoperative care.

INTRODUCTION/BACKGROUND:Reduced bone mineral density (BMD) and disruption of normal bony architecture are the characteristics of osteopenia and osteoporosis and in patients undergoing total hip arthroplasty (THA) may cause failure of trabecular ingrowth. The purpose of this study is to evaluate the impact of reduced BMD on outcomes following primary elective THA. METHODS:A retrospective chart review of 650 elective THAs with a DEXA scan in their electronic health record (EHR) from 2011 to 2020 was conducted at an urban, academic center and a regional, health center. Patients were separated into three cohorts based on their t-score and the World Health Organizations definitions: normal (t-score ≥ - 1), osteopenia (t-score < - 1.0 and > - 2.5), and osteoporosis (t-score ≤ - 2.5). Demographic and outcome data were assessed. Subsidence was assessed for patients with non-cemented THAs. Regression models were used to account for demographic differences. RESULTS:650 elective THAs, of which only 11 were cemented, were included in the study. Patients with osteopenia and osteoporosis were significantly older than those without (p = 0.002 and p < 0.0001, respectively) and had a lower BMI (p < 0.0001 and p < 0.0001, respectively). PFx was significantly greater in patients with osteoporosis when compared to those with normal BMD (6.5% vs. 1.0%; p = 0.04). No such difference was found between osteoporotic and osteopenic patients. The revision rate was significantly higher for osteoporotic patients than osteopenic patients (7.5% vs. 1.5%; p = 0.04). No such difference was found between the other comparison groups. CONCLUSION/CONCLUSIONS:Patients with osteoporosis were older with reduced BMI and had increased PFx after non-cemented elective THA. Understanding this can help surgeons formulate an appropriate preoperative plan for the treatment of patients with osteoporotic bone undergoing elective THA.