The Microbiome of Osteoarthritic Hip and Knee Joints: A Prospective Multicenter Investigation.

BACKGROUND: Recent advances in high-throughput DNA sequencing technologies have made it possible to characterize the microbial profile in anatomical sites previously assumed to be sterile. We used this approach to explore the microbial composition within joints of osteoarthritic patients. METHODS: This prospective multicenter study recruited 113 patients undergoing hip or knee arthroplasty between 2017 and 2019. Demographics and prior intra-articular injections were noted. Matched synovial fluid, tissue, and swab specimens were obtained and shipped to a centralized laboratory for testing. Following DNA extraction, microbial 16S-rRNA sequencing was performed. RESULTS: Comparisons of paired specimens indicated that each was a comparable measure for microbiological sampling of the joint. Swab specimens were modestly different in bacterial composition from synovial fluid and tissue. The 5 most abundant genera were Escherichia, Cutibacterium, Staphylococcus, Acinetobacter, and Pseudomonas. Although sample size varied, the hospital of origin explained a significant portion (18.5%) of the variance in the microbial composition of the joint, and corticosteroid injection within 6 months before arthroplasty was associated with elevated abundance of several lineages. CONCLUSIONS: The findings revealed that prior intra-articular injection and the operative hospital environment may influence the microbial composition of the joint. Furthermore, the most common species observed in this study were not among the most common in previous skin microbiome studies, suggesting that the microbial profiles detected are not likely explained solely by skin contamination. Further research is needed to determine the relationship between the hospital and a "closed" microbiome environment. These findings contribute to establishing the baseline microbial signal and identifying contributing variables in the osteoarthritic joint, which will be valuable as a comparator in the contexts of infection and long-term arthroplasty success. LEVEL OF EVIDENCE: Diagnostic Level II. See Instructions for Authors for a complete description of levels of evidence.

Kinematic Alignment of Failed Mechanically Aligned Total Knee Arthroplasty Restored Constitutional Limb Alignment and Improved Clinical Outcomes: A Case Report of 7 Patients.

Background: Stiffness and mid-flexion instability (MFI) is a recognized complication of mechanically aligned (MA) total knee arthroplasty (TKA). Kinematic alignment (KA) has been proposed as a means by which to restore normal joint motion following TKA and potentially avoid stiffness and MFI. Several studies have documented improved function with KA when compared to MA. The aim of this study was to determine if revising MA TKAs failed for either MFI or stiffness into KA resolves MFI, achieves better range of motion, and improves clinical outcomes. Methods: A retrospective, single surgeon review was performed. All consecutive TKAs revised from MA into KA for MFI (def: >5 mm opening between 10° and 45° of flexion) or stiffness (def: flexion ≤90°) between January 2017 and May 2021 were included. The constitutional limb alignment of the operated knee was "reverse engineered" by measuring the coronal alignment of the contralateral healthy knee or pre-operative x-rays. Femoral Rotation was set at 3 degrees internal to the trans epicondylar axis. All coronal and sagittal angles were digitally measured on pre- and post-operative long leg and maximum flexion radiographs (minimum 12 month follow-up). The Knee Society Score (KSS) and range of motion assessments were collected preoperatively and at final follow-up. Comparisons between groups were done with a paired T test. Significance was set at p < 0.05. Results: Seven patients were included. Two were male, the mean age was 70.1 years (±9.3), mean follow-up was 32 months (±26). Three patients were revised for MFI and 4 for stiffness. Constitutional limb alignment was restored within 2 degrees for all patients. The mean total KSS gain was 65.9 (±18.1). The total KSS was significantly improved in all patients (p < 0.001). The mean maximum flexion gain was 30 deg (±23°) (p = 0.01). MFI was absent in all patients. Conclusion: In a limited series of patients, revision of stiff or unstable TKA from MA to KA resulted in improved range of motion by 30° on averages, resolved instability without the use of constrained liners, improved clinical outcomes with a mean gain of 75 points on the KSS, and restored constitutional limb alignment within 2 degrees in all patients. As these short term results are promising, further study is warranted.

An Enhanced Understanding of Culture-Negative Periprosthetic Joint Infection with Next-Generation Sequencing: A Multicenter Study.

BACKGROUND: The challenges of culture-negative periprosthetic joint infection (PJI) have led to the emergence of molecular methods of pathogen identification, including next-generation sequencing (NGS). While its increased sensitivity compared with traditional culture techniques is well documented, it is not fully known which organisms could be expected to be detected with use of NGS. The aim of this study was to describe the NGS profile of culture-negative PJI. METHODS: Patients undergoing revision hip or knee arthroplasty from June 2016 to August 2020 at 14 institutions were prospectively recruited. Patients meeting International Consensus Meeting (ICM) criteria for PJI were included in this study. Intraoperative samples were obtained and concurrently sent for both routine culture and NGS. Patients for whom NGS was positive and standard culture was negative were included in our analysis. RESULTS: The overall cohort included 301 patients who met the ICM criteria for PJI. Of these patients, 85 (28.2%) were culture-negative. A pathogen could be identified by NGS in 56 (65.9%) of these culture-negative patients. Seventeen species were identified as common based on a study-wide incidence threshold of 5%. NGS revealed a polymicrobial infection in 91.1% of culture-negative PJI cases, with the set of common species contributing to 82.4% of polymicrobial profiles. Escherichia coli, Cutibacterium acnes, Staphylococcus epidermidis, and Staphylococcus aureus ranked highest in terms of incidence and study-wide mean relative abundance and were most frequently the dominant organism when occurring in polymicrobial infections. CONCLUSIONS: NGS provides a more comprehensive picture of the microbial profile of infection that is often missed by traditional culture. Examining the profile of PJI in a multicenter cohort using NGS, this study demonstrated that approximately two-thirds of culture-negative PJIs had identifiable opportunistically pathogenic organisms, and furthermore, the majority of infections were polymicrobial. LEVEL OF EVIDENCE: Diagnostic Level II . See Instructions for Authors for a complete description of levels of evidence.

Impact of fatty degeneration on the functional outcomes of 38 patients undergoing surgical repair of gluteal tendon tears.

BACKGROUND: Gluteal tendon tears (GTT) can cause pain and weakness of the hip. We analyze the impact of gluteal muscle fatty degeneration, atrophy and tear morphology on clinical outcomes of surgical repair. METHODS: All sequential patients receiving surgical repair of GTTs via anchor sutures between 1/2015 and 11/2018 were retrospectively identified. MRIs were reviewed by a radiologist for tendon retraction, muscle atrophy and tear size. The Goutallier-Fuchs Classification (GFC) was used to quantify fatty degeneration as < 2° or ≥ 2°. Demographic and clinical variables were abstracted from the electronic records. The surveys HHS Section 1 and HOOS Jr. were obtained at last follow-up. The Pearson correlation and one-way ANOVA tests served for statistical analysis of clinical variance. RESULTS: 38 patients were identified, 29 (76.3%) were female. The average age was 67. Of the 11 (28.9%) patients with a prior hip arthroplasty 87.5% of primary THAs had a direct lateral approach. 29 (76.3%) patients were treated open and 9 (23.7%) arthroscopically. At an average follow-up of 20.9 months, patients reported a significant improvement in pain (97%), analgesic use (85.7%), limp (52.6%) and abduction strength (54.2%) (all: P ≤ 0.01). GFC ≥ 2° were associated with significantly worse outcomes in terms of limp (0.19/3 vs. 1.2/3, P = 0.05), HHS-S1 (58.19 vs. 71.68, P = 0.04) and complication rates (37.5% vs. 0%, P = 0.02). There was a strong correlation between tear retraction (P = 0.005), tear size (P = 0.009) and muscle atrophy (P = 0.001) with GFC ≥ 2° but not with clinical outcomes. GFC ≥ 2° was strongly related to lateral THA exposures (P < 0.001). Surgical approach had no impact on clinical outcomes. CONCLUSION: While fatty degeneration can negatively impact functional outcomes, pain relief is reliably achieved. Tear morphology and muscle atrophy did not correlate with outcomes in this patient cohort. Patients should be counseled to expect a residual limp after surgery if they have GFC ≥ 2° on MRI.

Neurologic Dysfunction Associated With Mechanically Assisted Crevice Corrosion and Elevated Cobalt Ion Levels After Total Hip Arthroplasty.

Adverse local tissue reactions secondary to mechanically assisted crevice corrosion (MACC) at the trunnion is a complication of total hip arthroplasty known to cause local soft-tissue damage. However, what is not as well appreciated is that MACC in metal-on-polyethylene (MOP) articulations can lead to cobalt ion serum elevations with associated neurological dysfunction just as in metal-on-metal articulations. We report a compelling case for the association of neurologic dysfunction tied to metal ion elevations secondary to MACC at two distinct MOP tapers in a 58-year-old intensive care unit nurse with two hips implanted 3 years apart. This report further raises awareness about the potential of MACC-generated elevated ion levels to produce neurological symptoms that might otherwise be overlooked in patients with MOP articulations.

Tibial Mechanical Axis Is Nonorthogonal to the Floor in Varus Knee Alignment.

BACKGROUND: Classical models of the knee assume the joint line is parallel to the floor and the tibial mechanical axis (TMA) is orthogonal to the floor. Our study characterizes the angle subtended by the TMA and floor during bipedal stance, called the tibial axis orientation angle (TAOA), and tests the assumption that the TMA should be orthogonal to the floor. METHODS: We reviewed the nonoperative knee on full-length, standing radiographs in patients undergoing total knee arthroplasty between 2013 and 2017. Radiographic measurements were obtained for hip-knee-ankle axis, medial proximal tibial angle (MPTA), joint line orientation angle, and TAOA and correlated by regression analysis. The cohort was stratified by hip-knee-ankle axis alignment to determine statistical differences in knee angle values. Demographic data were collected to assess associations with knee angles. RESULTS: Our cohort included 68 patients, with 56% female and average age of 62.3 years. Varus knees comprised 56% of the cohort, with 7% neutral and 37% valgus. The cohort demonstrated an MPTA of 3.06°, TAOA of 2.67°, and joint line orientation angle of 0.36°. Varus knees had a higher MPTA (4.26°) and TAOA (4.74°) than valgus knees (P < .001). MPTA and TAOA were correlated on regression analysis (r2 = 0.465), and all angles were statistically different between sexes. CONCLUSION: The angle between the TMA and floor, called TAOA, is not orthogonal in normal knees, contrary to assumptions in classical biomechanics. Knee angles vary significantly between varus and valgus cohorts, and the distinction between these cohorts should be noted when evaluating normal joint line angles.

The Effect of the COVID-19 Pandemic on Hip and Knee Arthroplasty Patients in the United States: A Multicenter Update to the Previous Survey.

BACKGROUND: In March 2020, elective total hip and knee arthroplasty (THA and TKA) were suspended across the United States in response to the COVID-19 pandemic. We had previously published the results of a survey to the affected patients from 6 institutions. We now present the results of a larger distribution of this survey, through May and June 2020, to electively scheduled patients representing different regions of the United States. METHODS: Fifteen centers identified through the American Association of Hip and Knee Surgeons Research Committee participated in a survey study of THA and TKA patients. Patients scheduled for primary elective THA or TKA but canceled due to the COVID-19 elective surgery stoppage (3/2020-5/2020) were included in the study. Descriptive statistics along with subgroup analysis with Wilcoxon rank were performed. RESULTS: In total, surveys were distributed to 2135 patients and completed by 848 patients (40%) from 15 institutions. Most patients (728/848, 86%) had their surgery postponed or canceled by the surgeon or hospital. Unknown length of surgical delay remained the highest source of anxiety among survey participants. Male patients were more likely to be willing to proceed with surgery in spite of COVID-19. There were minimal regional differences in responses. Only 61 patients (7%) stated they will continue to delay surgery for fear of contracting COVID-19 while in the hospital. CONCLUSION: Similar to the previous study, the most anxiety-provoking thought was the uncertainty, over if and when the canceled joint replacement surgery could be rescheduled. Patients suffering from the daily pain of hip and knee arthritis who have been scheduled for elective arthroplasty remain eager to have their operation as soon as elective surgery is allowed to resume.

Risk Adjustment in the California Joint Replacement Registry: Is Patient Complexity Accurately Assessed in Academic Versus Nonacademic Hospitals?

BACKGROUND: We sought to report on the differences in observed versus expected arthroplasty outcomes between academic and nonacademic hospitals in a large joint registry. We utilized the California Joint Replacement Registry's data and risk adjustment model. METHODS: Observed versus expected hip and knee arthroplasty complications were utilized to assess hospital and surgeon risk-adjusted complication rates (RACRs). Based on a hospital and surgeon RACR, each was assigned a performance rating ("worse," "expected," "better"). Associations between academic status and performance ratings, rates of individual complications, prevalence of risk factors associated with increased complication rates, and differences in complication rates were calculated. RESULTS: A higher percentage of academic providers had "worse" than expected ratings, whereas a higher percentage of nonacademic providers had "expected" and "better" than expected ratings (P = .011) based on the observed versus expected complication rates. There was a higher incidence of patients with congestive heart failure and an elevated American Society of Anesthesiologists classification in academic institutions (P = .0001). The complication rate was higher in academic institutions for all total knee arthroplasties (P < .0016). CONCLUSIONS: We identified disparities in RACRs between nonacademic and academic institutions. This may reflect the difficulty of fully adjusting for medical risk and surgical complexity in a large arthroplasty database.

Risk-Adjusted Cost Performance for 90-Day Total Hip Arthroplasty Episodes: Comparing US Hospitals Nationwide Before CJR.

BACKGROUND: We characterize variation in total hip arthroplasty (THA) episode payments in the United States. Medicare population immediately preceding implementation of the comprehensive care for joint replacement (CJR) bundled care model and propose a model for ongoing evaluation of hospital performance. METHODS: We identified THA episodes in Medicare part A 2014-2016 (n = 366,380) and compared 90-day episode payments across years and geographic regions. We fit hierarchical models that regressed episode payments on patient-level fixed and region-level and hospital-level random effects. Random effects estimates were used to characterize risk-adjusted hospital cost performance. We ranked hospitals (n = 3218) in each region by their cost performance estimate and constructed 95% confidence intervals to visualize high-performing and low-performing hospitals. RESULTS: Mean part A episode payments declined from 2014 to 2016 throughout the United States ($19,925-$17,775; P < .001), primarily attributable to decreased postacute care payments. Ninety-day readmission rates fell by a percentage point (from 7.9% to 6.8%; P < .001). We found significant variation in risk-adjusted episode payments, postacute care utilization, and readmission rates across regions, and ever greater variation at the hospital level. CONCLUSION: Medicare part A payments decreased for THA episodes between 2014 and 2016. The time frame for this decrease is notable for preceding full implementation of CJR, thus suggesting a more universal embrace of value-based care principles before the start date of CJR. These decreases were primarily because of decreased postacute care utilization and possibly related to falling readmission rates. Yet, significant variation in hospital cost performance remains, even after risk adjustment.

Incremental inputs improve the automated detection of implant loosening using machine-learning algorithms.

AIMS: The aim of this study was to evaluate the ability of a machine-learning algorithm to diagnose prosthetic loosening from preoperative radiographs and to investigate the inputs that might improve its performance. METHODS: A group of 697 patients underwent a first-time revision of a total hip (THA) or total knee arthroplasty (TKA) at our institution between 2012 and 2018. Preoperative anteroposterior (AP) and lateral radiographs, and historical and comorbidity information were collected from their electronic records. Each patient was defined as having loose or fixed components based on the operation notes. We trained a series of convolutional neural network (CNN) models to predict a diagnosis of loosening at the time of surgery from the preoperative radiographs. We then added historical data about the patients to the best performing model to create a final model and tested it on an independent dataset. RESULTS: The convolutional neural network we built performed well when detecting loosening from radiographs alone. The first model built de novo with only the radiological image as input had an accuracy of 70%. The final model, which was built by fine-tuning a publicly available model named DenseNet, combining the AP and lateral radiographs, and incorporating information from the patient's history, had an accuracy, sensitivity, and specificity of 88.3%, 70.2%, and 95.6% on the independent test dataset. It performed better for cases of revision THA with an accuracy of 90.1%, than for cases of revision TKA with an accuracy of 85.8%. CONCLUSION: This study showed that machine learning can detect prosthetic loosening from radiographs. Its accuracy is enhanced when using highly trained public algorithms, and when adding clinical data to the algorithm. While this algorithm may not be sufficient in its present state of development as a standalone metric of loosening, it is currently a useful augment for clinical decision making. Cite this article: Bone Joint J 2020;102-B(6 Supple A):101-106.

Digital Orthopaedics: A Glimpse Into the Future in the Midst of a Pandemic.

BACKGROUND: The response to COVID-19 catalyzed the adoption and integration of digital health tools into the health care delivery model for musculoskeletal patients. The change, suspension, or relaxation of Medicare and federal guidelines enabled the rapid implementation of these technologies. The expansion of payment models for virtual care facilitated its rapid adoption. The authors aim to provide several examples of digital health solutions utilized to manage orthopedic patients during the pandemic and discuss what features of these technologies are likely to continue to provide value to patients and clinicians following its resolution. CONCLUSION: The widespread adoption of new technologies enabling providers to care for patients remotely has the potential to permanently change the expectations of all stakeholders about the way care is provided in orthopedics. The new era of Digital Orthopaedics will see a gradual and nondisruptive integration of technologies that support the patient's journey through the successful management of their musculoskeletal disease.

Equivalent Mid-Term Results of Open vs Endoscopic Gluteal Tendon Tear Repair Using Suture Anchors in Forty-Five Patients.

BACKGROUND: Little is known about the relative efficacy of open (OGR) vs endoscopic (EGR) gluteal tendon repair of gluteal tendon tears in minimizing pain and restoring function. Our aim is to compare these 2 surgical techniques and quantify their impact on clinical outcomes. METHODS: All patients undergoing gluteal tendon tear repair at our institution between 2015 and 2018 were retrospectively reviewed. Pain scores, limp, hip abduction strength, and the use of analgesics were recorded preoperatively and at last follow-up. The Hip disability and Osteoarthritis Outcome Score Junior and Harris Hip Score Section1 were obtained at last follow-up. Fatty degeneration was quantified using the Goutallier-Fuchs Classification (GFC). Statistical analysis was conducted using one-way analysis of variance and t-tests. RESULTS: Forty-five patients (mean age 66, 87% females) met inclusion criteria. Average follow-up was 20.3 months. None of the 10 patients (22%) undergoing EGR had prior surgery. Of 35 patients (78%) undergoing OGR, 12 (27%) had prior hip replacement (75% via lateral approach). The OGRs had more patients with GFC ≥2 (50% vs 11%, P = .02) and used more anchors (P = .03). Both groups showed statistical improvement (P ≤ .01) for all outcomes measured. GFC >2 was independently associated with a worst limp and Harris Hip Score Section 1 score (P = .05). EGR had a statistically higher opioid use reduction (P < .05) than OGR. Other comparisons between EGR and OGR did not reach statistical significance. CONCLUSION: In this series, open vs endoscopic operative approach did not impact clinical outcomes. More complex tears were treated open and with more anchors. Fatty degeneration adversely impacted outcomes. Although further evaluation of the efficacy of EGR in complex tears is indicated, both approaches can be used successfully.

Wearable activity sensors and early pain after total joint arthroplasty.

A prospective observational cohort of 20 primary total hip arthroplasty (n = 12) and total knee arthroplasty (n = 8) patients (mean age: 63 ± 6 years) was passively monitored with a consumer-level wearable activity sensor before and 6 weeks after surgery. Patients were clustered by minimal change or decreased activity using sensor data. Decreased postoperative activity was associated with greater pain reduction (-5.5 vs -2.0, P = .03). All patients surpassed minimal clinical benefit thresholds of total joint arthroplasty (TJA) (Hip Disability and Osteoarthritis Score Junior 30.5 vs 20.8, P = .23; Knee Injury and Osteoarthritis Outcome Score Junior 23.3 vs 18.2, P = .77) within 6 weeks. Patients who objectively "take it easy" after TJA may experience less pain with no difference in early subjective outcome. Remote, passive analysis of outpatient wearable sensor data may permit real-time detection of early problems after TJA.

Machine Learning Algorithms Can Use Wearable Sensor Data to Accurately Predict Six-Week Patient-Reported Outcome Scores Following Joint Replacement in a Prospective Trial.

BACKGROUND: Tracking patient-generated health data (PGHD) following total joint arthroplasty (TJA) may enable data-driven early intervention to improve clinical results. We aim to demonstrate the feasibility of combining machine learning (ML) with PGHD in TJA to predict patient-reported outcome measures (PROMs). METHODS: Twenty-two TJA patients were recruited for this pilot study. Three activity trackers collected 35 features from 4 weeks before to 6 weeks following surgery. PROMs were collected at both endpoints (Hip and Knee Disability and Osteoarthritis Outcome Score, Knee Osteoarthritis Outcome Score, and Veterans RAND 12-Item Health Survey Physical Component Score). We used ML to identify features with the highest correlation with PROMs. The algorithm trained on a subset of patients and used 3 feature sets (A, B, and C) to group the rest into one of the 3 PROM clusters. RESULTS: Fifteen patients completed the study and collected 3 million data points. Three sets of features with the highest R2 values relative to PROMs were selected (A, B and C). Data collected through the 11th day had the highest predictive value. The ML algorithm grouped patients into 3 clusters predictive of 6-week PROM results, yielding total sum of squares values ranging from 3.86 (A) to 1.86 (C). CONCLUSION: This small but critical proof-of-concept study demonstrates that ML can be used in combination with PGHD to predict 6-week PROM data as early as 11 days following TJA surgery. Further study is needed to confirm these findings and their clinical value.

Optimal Sampling Frequency for Wearable Sensor Data in Arthroplasty Outcomes Research. A Prospective Observational Cohort Trial.

BACKGROUND: Wearable sensors can track patient activity after surgery. The optimal data sampling frequency to identify an association between patient-reported outcome measures (PROMs) and sensor data is unknown. Most commercial grade sensors report 24-hour average data. We hypothesize that increasing the frequency of data collection may improve the correlation with PROM data. METHODS: Twenty-two total joint arthroplasty (TJA) patients were prospectively recruited and provided wearable sensors. Second-by-second (Raw) and 24-hour average data (24Hr) were collected on 7 gait metrics on the 1st, 7th, 14th, 21st, and 42nd days postoperatively. The average for each metric as well as the slope of a linear regression for 24Hr data (24HrLR) was calculated. The R2 associations were calculated using machine learning algorithms against individual PROM results at 6 weeks. The resulting R2 values were defined having a mild, moderate, or strong fit (R2 ≥ 0.2, ≥0.3, and ≥0.6, respectively) with PROM results. The difference in frequency of fit was analyzed with the McNemar's test. RESULTS: The frequency of at least a mild fit (R2 ≥ 0.2) for any data point at any time frame relative to either of the PROMs measured was higher for Raw data (42%) than 24Hr data (32%; P = .041). There was no difference in frequency of fit for 24hrLR data (32%) and 24Hr data values (32%; P > .05). Longer data collection improved frequency of fit. CONCLUSION: In this prospective trial, increasing sampling frequency above the standard 24Hr average provided by consumer grade activity sensors improves the ability of machine learning algorithms to predict 6-week PROMs in our total joint arthroplasty cohort.

Variation in the Thickness of Knee Cartilage. The Use of a Novel Machine Learning Algorithm for Cartilage Segmentation of Magnetic Resonance Images.

BACKGROUND: The variation in articular cartilage thickness (ACT) in healthy knees is difficult to quantify and therefore poorly documented. Our aims are to (1) define how machine learning (ML) algorithms can automate the segmentation and measurement of ACT on magnetic resonance imaging (MRI) (2) use ML to provide reference data on ACT in healthy knees, and (3) identify whether demographic variables impact these results. METHODS: Patients recruited into the Osteoarthritis Initiative with a radiographic Kellgren-Lawrence grade of 0 or 1 with 3D double-echo steady-state MRIs were included and their gender, age, and body mass index were collected. Using a validated ML algorithm, 2 orthogonal points on each femoral condyle were identified (distal and posterior) and ACT was measured on each MRI. Site-specific ACT was compared using paired t-tests, and multivariate regression was used to investigate the risk-adjusted effect of each demographic variable on ACT. RESULTS: A total of 3910 MRI were included. The average femoral ACT was 2.34 mm (standard deviation, 0.71; 95% confidence interval, 0.95-3.73). In multivariate analysis, distal-medial (-0.17 mm) and distal-lateral cartilage (-0.32 mm) were found to be thinner than posterior-lateral cartilage, while posterior-medial cartilage was found to be thicker (0.21 mm). In addition, female sex was found to negatively impact cartilage thickness (OR, -0.36; all values: P < .001). CONCLUSION: ML was effectively used to automate the segmentation and measurement of cartilage thickness on a large number of MRIs of healthy knees to provide normative data on the variation in ACT in this population. We further report patient variables that can influence ACT. Further validation will determine whether this technique represents a powerful new tool for tracking the impact of medical intervention on the progression of articular cartilage degeneration.

Implementing a perioperative efficiency initiative for orthopedic surgery instrumentation at an academic center: A comparative before-and-after study.

Optimizing surgical instrumentation may contribute to value-based care, particularly in commonly performed procedures. We report our experience in implementing a perioperative efficiency program in 2 types of orthopedic surgery (primary total-knee arthroplasty, TKA, and total-hip arthroplasty, THA).A comparative before-and-after study with 2 participating surgeons, each performing both THA and TKA, was conducted. Our objective was to evaluate the effect of surgical tray optimization on operating and processing time, cost, and waste associated with preparation, delivery, and staging of sterile surgical instruments. The study was designed as a prospective quality improvement initiative with pre- and postimplementation operational measures and a provider satisfaction survey.A total of 96 procedures (38 preimplementation and 58 postimplementation) were assessed using time-stamped performance endpoints. The number and weight of trays and instruments processed were reduced substantially after the optimization intervention, particularly for TKA. Setup time was reduced by 23% (6 minutes, P = .01) for TKA procedures but did not differ for THA. The number of survey respondents was small, but satisfaction was high overall among personnel involved in implementation.Optimizing instrumentation trays for orthopedic procedures yielded reduction in processing time and cost. Future research should evaluate patient outcomes and incremental/additive impact on institutional quality measures.