Isolated Osteochondral Autograft Versus Allograft Transplantation for the Treatment of Symptomatic Cartilage Lesions of the Knee: A Systematic Review and Meta-analysis.

BACKGROUND: Focal cartilage lesions of the knee remain a difficult entity to treat. Current treatment options include arthroscopic debridement, microfracture, autograft or allograft osteochondral transplantation, and cell-based therapies such as autologous chondrocyte transplantation. Osteochondral transplantation techniques restore the normal topography of the condyles and provide mature hyaline cartilage in a single-stage procedure. However, clinical outcomes comparing autograft versus allograft techniques are scarce. PURPOSE: To perform a comprehensive systematic review and meta-analysis of high-quality studies to evaluate the results of osteochondral autograft and allograft transplantation for the treatment of symptomatic cartilage defects of the knee. STUDY DESIGN: Systematic review and meta-analysis; Level of evidence, 2. METHODS: A comprehensive search of the literature was conducted using various databases. Inclusion criteria were level 1 or 2 original studies, studies with patients reporting knee cartilage injuries and chondral defects, mean follow-up ≥2 years, and studies focusing on osteochondral transplant techniques. Exclusion criteria were studies with nonknee chondral defects, studies reporting clinical outcomes of osteochondral autograft or allograft combined with other procedures, animal studies, cadaveric studies, non-English language studies, case reports, and reviews or editorials. Primary outcomes included patient-reported outcomes and failure rates associated with both techniques, and factors such as lesion size, age, sex, and the number of plugs transplanted were assessed. Metaregression using a mixed-effects model was utilized for meta-analyses. RESULTS: The search resulted in 20 included studies with 364 cases of osteochondral autograft and 272 cases of osteochondral allograft. Mean postoperative survival was 88.2% in the osteochondral autograft cohort as compared with 87.2% in the osteochondral allograft cohort at 5.4 and 5.2 years, respectively (P = .6605). Patient-reported outcomes improved by an average of 65.1% and 81.1% after osteochondral autograft and allograft, respectively (P = .0001). However, meta-analysis revealed no significant difference in patient-reported outcome percentage change between osteochondral autograft and allograft (P = .97) and a coefficient of 0.033 (95% CI, -1.91 to 1.98). Meta-analysis of the relative risk of graft failure after osteochondral autograft versus allograft showed no significant differences (P = .66) and a coefficient of 0.114 (95% CI, -0.46 to 0.69). Furthermore, the regression did not find other predictors (mean age, percentage of female patients, lesion size, number of plugs/grafts used, and treatment location) that may have significantly affected patient-reported outcome percentage change or postoperative failure between osteochondral autograft versus allograft. CONCLUSION: Osteochondral autograft and allograft result in favorable patient-reported outcomes and graft survival rates at medium-term follow-up. While predictors for outcomes such as mean age, percentage of female patients, lesion size, number of plugs/grafts used, and treatment location did not affect the comparison of the 2 cohorts, proper patient selection for either procedure remains paramount to the success and potentially long-term viability of the graft.

Machine Learning Can Accurately Predict Overnight Stay, Readmission, and 30-Day Complications Following Anterior Cruciate Ligament Reconstruction.

PURPOSE: This study aimed to develop machine learning (ML) models to predict hospital admission (overnight stay) as well as short-term complications and readmission rates following anterior cruciate ligament reconstruction (ACLR). Furthermore, we sought to compare the ML models with logistic regression models in predicting ACLR outcomes. METHODS: The American College of Surgeons National Surgical Quality Improvement Program database was queried for patients who underwent elective ACLR from 2012 to 2018. Artificial neural network ML and logistic regression models were developed to predict overnight stay, 30-day postoperative complications, and ACL-related readmission, and model performance was compared using the area under the receiver operating characteristic curve. Regression analyses were used to identify variables that were significantly associated with the predicted outcomes. RESULTS: A total of 21,636 elective ACLR cases met inclusion criteria. Variables associated with hospital admission included White race, obesity, hypertension, and American Society of Anesthesiologists classification 3 and greater, anesthesia other than general, prolonged operative time, and inpatient setting. The incidence of hospital admission (overnight stay) was 10.2%, 30-day complications was 1.3%, and 30-day readmission for ACLR-related causes was 0.9%. Compared with logistic regression models, artificial neural network models reported superior area under the receiver operating characteristic curve values in predicting overnight stay (0.835 vs 0.589), 30-day complications (0.742 vs 0.590), reoperation (0.842 vs 0.601), ACLR-related readmission (0.872 vs 0.606), deep-vein thrombosis (0.804 vs 0.608), and surgical-site infection (0.818 vs 0.596). CONCLUSIONS: The ML models developed in this study demonstrate an application of ML in which data from a national surgical patient registry was used to predict hospital admission and 30-day postoperative complications after elective ACLR. ML models developed performed well, outperforming regression models in predicting hospital admission and short-term complications following elective ACLR. ML models performed best when predicting ACLR-related readmissions and reoperations, followed by overnight stay. LEVEL OF EVIDENCE: IV, retrospective comparative prognostic trial.

Mortality Rate Increase in Elderly Patients With Hip Fractures Presenting During the COVID-19 Pandemic to a Hospital in the United States Epicenter: Minimum 30-day Follow Up Comparative Study.

The purpose of this study was to compare mortality and complication rates among geriatric patients who sustained a hip fracture before the coronavirus disease (COVID-19) pandemic began to those who presented during the peak of the pandemic. Patients greater than or equal to 50 years of age who presented with a diagnosis of hip fracture from March 16, 2020 to May 1, 2020 were compared with a historical control group who presented between December 1, 2019 and January 16, 2020. Minimum follow up was 30 days. The primary outcome was a 30-day mortality rate. Thirty-day mortality was significantly different between groups, with no deaths of 24 patients in the pre-COVID-19 cohort versus six deaths of 23 patients (26.1%) in the COVID-19 cohort (chi-squared test, p-value = 0.02). The study concluded that the COVID-19 pandemic increased mortality risk for geriatric hip fracture patients. (Journal of Surgical Orthopaedic Advances 32(4):232-237, 2023).

Incidental Pulmonary Nodules Found on Shoulder Arthroplasty Preoperative CT Scans.

With current emphasis on preoperative templating of anatomical and reverse shoulder arthroplasty (aTSA and rTSA, respectively), patients often receive thin slice (<1.0 mm) computerized tomography (CT) scans of the operative shoulder, which includes about two-thirds of the ipsilateral lung. The purpose of this study is to evaluate the prevalence and management of incidentally detected pulmonary nodules on preoperative CT scans for shoulder arthroplasty. In this single-center retrospective study, we queried records of aTSA and rTSA patients from 2015 to 2020 who received preoperative CT imaging of the shoulder. Compared to patients with negative CT findings, there were significantly more females (63.8% vs. 46.4%; P = .011), COPD (13.0% vs. 4.7%; P = .015), and asthma (18.8% vs. 6.9%; P = .003) among the patients with incidental nodules on CT. Binary logistic regression confirmed that female sex (odds ratio = 2.00; 95% CI = 1.04 to 3.88; P = .037), COPD history (OR = 3.02; 95% CI = 1.05 to 8.65; P = .040), and asthma history (OR = 3.17; 95% CI = 1.30 to 7.77; P = .011) were significantly associated with an incidental nodule finding. Incidental pulmonary nodules found on shoulder arthroplasty preoperative CT scans are often low risk in size with low risk of malignancy, and do not require further workup. This study may provide guidance to orthopedic surgeons on how to manage patients with incidental pulmonary nodules to increase chances of early cancer detection, avoid unnecessary referrals, reduce potentially harmful radiation exposure of serial CT scans, and improve cost efficiency.

Artificial Learning and Machine Learning Applications in Spine Surgery: A Systematic Review.

OBJECTIVES: This current systematic review sought to identify and evaluate all current research-based spine surgery applications of AI/ML in optimizing preoperative patient selection, as well as predicting and managing postoperative outcomes and complications. METHODS: A comprehensive search of publications was conducted through the EMBASE, Medline, and PubMed databases using relevant keywords to maximize the sensitivity of the search. No limits were placed on level of evidence or timing of the study. Findings were reported according to the PRISMA guidelines. RESULTS: After application of inclusion and exclusion criteria, 41 studies were included in this review. Bayesian networks had the highest average AUC (.80), and neural networks had the best accuracy (83.0%), sensitivity (81.5%), and specificity (71.8%). Preoperative planning/cost prediction models (.89,82.2%) and discharge/length of stay models (.80,78.0%) each reported significantly higher average AUC and accuracy compared to readmissions/reoperation prediction models (.67,70.2%) (P < .001, P = .005, respectively). Model performance also significantly varied across postoperative management applications for average AUC and accuracy values (P < .001, P < .027, respectively). CONCLUSIONS: Generally, authors of the reviewed studies concluded that AI/ML offers a potentially beneficial tool for providers to optimize patient care and improve cost-efficiency. More specifically, AI/ML models performed best, on average, when optimizing preoperative patient selection and planning and predicting costs, hospital discharge, and length of stay. However, models were not as accurate in predicting postoperative complications, adverse events, and readmissions and reoperations. An understanding of AI/ML-based applications is becoming increasingly important, particularly in spine surgery, as the volume of reported literature, technology accessibility, and clinical applications continue to rapidly expand.

Recent Trends in Private Equity Acquisition of Orthopaedic Practices in the United States.

BACKGROUND: Private equity acquisition of medical specialty practices has increased in recent years. With the projected increase in the volume of elective, ambulatory orthopaedic procedures, especially in the outpatient setting, private equity firms are increasingly investing in orthopaedic practices. The purpose of this cross-sectional study was to report recent trends and variations in acquisitions of US orthopaedic practices by private equity firms and other institutional investors (venture capital firms, trusts, and large investment companies). METHODS: Acquisition data through January 1, 2020, were collected and analyzed using various financial databases, supplemented with publicly available information from financial news outlets, press releases, and financial analyst and industry reports. Disclosed financing data were also included, in addition to pertinent geographic information (state, city, and zip code) of the target practices. RESULTS: Between 2004 and 2019, 41 orthopaedic practices and surgeon groups across 22 states were acquired by 34 private equity and other investment firms. A significant increase was observed in the number of acquisitions between 2017 and 2019, consisting of 70.7% of total transactions during the study period, with a statistically significant upward yearly trend (P = 0.002). The compound annual growth rate in acquisition volume was 29.2% during the study period. A disproportionate share of private equity acquisitions took place in the South, where more than half (51.2%) of the total transactions took place. Firms were markedly more likely to acquire or invest in practices located in major metropolitan areas (population more than 1 million) compared with those in mid-sized or rural areas (70.7%, 17.1%, 12.2%, respectively; P < 0.001). CONCLUSIONS: Private equity acquisition of orthopaedic surgery practices has increased markedly in recent years. The effect of private equity acquisition on physician independence, practice management, and procedure reimbursement remains unclear and may be important to explore as practice management evolves. LEVEL OF EVIDENCE: Prognostic Level III.

Machine Learning Model Developed to Aid in Patient Selection for Outpatient Total Joint Arthroplasty.

BACKGROUND: Patient selection for outpatient total joint arthroplasty (TJA) is important for optimizing patient outcomes. This study develops machine learning models that may aid in patient selection for outpatient TJA based on medical comorbidities and demographic factors. METHODS: This study queried elective total knee arthroplasty (TKA) and total hip arthroplasty (THA) cases during 2010-2018 in the American College of Surgeons National Surgical Quality Improvement Program. Artificial neural network models predicted same-day discharge and length of stay (LOS) fewer than 2 days (short LOS). Multiple linear and logistic regression analyses were used to identify variables significantly associated with predicted outcomes. RESULTS: A total of 284,731 TKA cases and 153,053 THA cases met inclusion criteria. For TKA, prediction of short LOS had an area under the receiver operating characteristic curve (AUC) of 0.767 and accuracy of 84.1%; prediction of same-day discharge had an AUC of 0.802 and accuracy of 89.2%. For THA, prediction of short LOS had an AUC of 0.757 and accuracy of 70.6%; prediction of same-day discharge had an AUC of 0.814 and accuracy of 78.8%. CONCLUSION: This study developed machine learning models for aiding patient selection for outpatient TJA, through accurately predicting short LOS or outpatient vs inpatient cases. As outpatient TJA expands, it will be important to optimize preoperative patient selection and effectively screen surgical candidates from a broader patient population. Incorporating models such as these into electronic medical records could aid in decision-making and resource planning in real time.

Artificial Learning and Machine Learning Decision Guidance Applications in Total Hip and Knee Arthroplasty: A Systematic Review.

BACKGROUND: Artificial intelligence (AI) and machine learning (ML) modeling in hip and knee arthroplasty (total joint arthroplasty [TJA]) is becoming more commonplace. This systematic review aims to quantify the accuracy of current AI- and ML-based application for cognitive support and decision-making in TJA. METHODS: A comprehensive search of publications was conducted through the EMBASE, Medline, and PubMed databases using relevant keywords to maximize the sensitivity of the search. No limits were placed on level of evidence or timing of the study. Findings were reported according to the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. Analysis of variance testing with post-hoc Tukey test was applied to compare the area under the curve (AUC) of the models. RESULTS: After application of inclusion and exclusion criteria, 49 studies were included in this review. The application of AI/ML-based models and average AUC is as follows: cost prediction-0.77, LOS and discharges-0.78, readmissions and reoperations-0.66, preoperative patient selection/planning-0.79, adverse events and other postoperative complications-0.84, postoperative pain-0.83, postoperative patient-reported outcomes measures and functional outcome-0.81. Significant variability in model AUC across the different decision support applications was found (P < .001) with the AUC for readmission and reoperation models being significantly lower than that of the other decision support categories. CONCLUSIONS: AI/ML-based applications in TJA continue to expand and have the potential to optimize patient selection and accurately predict postoperative outcomes, complications, and associated costs. On average, the AI/ML models performed best in predicting postoperative complications, pain, and patient-reported outcomes and were less accurate in predicting hospital readmissions and reoperations.

A Systematic Review of the Orthopaedic Literature on Truncal and Lower Extremity Injuries in Major League Baseball Players.

BACKGROUND: Orthopaedic injuries in Major League Baseball (MLB) players can have a tremendous impact on player health, longevity, salaries, and time lost from play. PURPOSE: To summarize all data published between January 1980 and August 2019 on truncal and lower extremity orthopaedic injuries sustained by MLB players. METHODS: A literature review of studies examining injuries in MLB was performed using the PubMed and Embase databases. Included studies focused on truncal and lower extremity injuries in professional baseball players. Studies pertaining to nonorthopaedic injuries, and case reports, were excluded. RESULTS: A total of 41 articles met the inclusion criteria and were selected for the final analysis. Articles were divided based on anatomic region of injury: hip and pelvis (16%), thigh (15%), truncal (14%), knee (13%), and ankle (11%). Most studies (83.7%) were level 3 evidence. Most studies obtained data using publicly available internet resources (29.8%) compared with the MLB Health and Injury Tracking System (22.1%). CONCLUSION: This review provides physicians with a single source of the most current literature regarding truncal and lower extremity orthopaedic injuries in MLB players. Most research was published on hip and pelvic, truncal, and thigh injuries and consisted of level III evidence.

Using machine learning methods to predict nonhome discharge after elective total shoulder arthroplasty.

BACKGROUND: Machine learning has shown potential in accurately predicting outcomes after orthopedic surgery, thereby allowing for improved patient selection, risk stratification, and preoperative planning. This study sought to develop machine learning models to predict nonhome discharge after total shoulder arthroplasty (TSA). METHODS: The American College of Surgeons National Surgical Quality Improvement Program database was queried for patients who underwent elective TSA from 2012 to 2018. Boosted decision tree and artificial neural networks (ANN) machine learning models were developed to predict non-home discharge and 30-day postoperative complications. Model performance was measured using the area under the receiver operating characteristic curve (AUC) and overall accuracy (%). Multivariate binary logistic regression analyses were used to identify variables that were significantly associated with the predicted outcomes. RESULTS: There were 21,544 elective TSA cases identified in the National Surgical Quality Improvement Program registry from 2012 to 2018 that met inclusion criteria. Multivariate logistic regression identified several variables associated with increased risk of nonhome discharge including female sex (odds ratio [OR] = 2.83; 95% confidence interval [CI] = 2.53-3.17; P < .001), age older than 70 years (OR = 3.19; 95% CI = 2.86-3.57; P < .001), American Society of Anesthesiologists classification 3 or greater (OR = 2.70; 95% CI = 2.41-2.03; P < .001), prolonged operative time (OR = 1.38; 95% CI = 1.20-1.58; P < .001), as well as history of diabetes (OR = 1.56; 95% CI = 1.38-1.75; P < .001), chronic obstructive pulmonary disease (OR = 1.71; 95% CI = 1.46-2.01; P < .001), congestive heart failure (OR = 2.65; 95% CI = 1.72-4.01; P < .001), hypertension (OR = 1.35; 95% CI = 1.20-1.52; P = .004), dialysis (OR = 3.58; 95% CI = 2.01-6.39; P = .002), wound infection (OR = 5.67; 95% CI = 3.46-9.29; P < .001), steroid use (OR = 1.43; 95% CI = 1.18-1.74; P = .010), and bleeding disorder (OR = 1.84; 95% CI = 1.45-2.34; P < .001). The boosted decision tree model for predicting nonhome discharge had an AUC of 0.788 and an overall accuracy of 90.3%. The ANN model for predicting nonhome discharge had an AUC of 0.851 and an overall accuracy of 89.9%. For predicting the occurrence of 1 or more postoperative complications, the boosted decision tree model had an AUC of 0.795 and an overall accuracy of 95.5%. The ANN model yielded an AUC of 0.788 and an overall accuracy of 92.5%. CONCLUSIONS: Both the boosted decision tree and ANN models performed well in predicting nonhome discharge with similar overall accuracy, but the ANN had higher discriminative ability. Based on the findings of this study, machine learning has the potential to accurately predict nonhome discharge after elective TSA. Surgeons can use such tools to guide patient expectations and to improve preoperative discharge planning, with the ultimate goal of decreasing hospital length of stay and improving cost-efficiency.

Number of screws in the articular segment of distal humerus AO/OTA C-type fractures treated with open reduction internal fixation is associated with complication rate.

INTRODUCTION: Surgical treatment of distal humerus fractures can lead to numerous complications. Data suggest that the number of screws in the distal (articular) segment may be associated with complication rate. The purpose of this study is to evaluate the association between a number of screws in the distal segment and complication rate for surgical treatment of distal humerus fractures. We hypothesize that the number of screws in the articular segment of distal humerus AO/OTA C-type fractures treated with open reduction internal fixation (ORIF) will be inversely proportional to the complication rate. METHODS: We performed a single-center retrospective cohort study of 27 patients who underwent ORIF of distal humerus fractures C-type with at least six months of radiographic and clinical follow-up. Clinical outcomes including a range of motion, pain, revision surgery for stiffness and/or heterotopic ossification (HO), nonunion, and persistent ulnar nerve symptoms requiring revision neurolysis were recorded. RESULTS: In C-type fractures, the use of three or fewer articular screws was significantly associated with nonunion or loss of fixation (RR 17, p = 0.006). Nineteen of 36 (53%) patients experienced at least one complication. The surgical approach, plate configuration, age, and ulnar nerve treatment (none, in situ release, transposition) were not associated with the need for revision surgery. Men had a higher risk of requiring surgical contracture release due to improving post-operative stiffness (RR 12, p = 0.02). CONCLUSION: In this retrospective study, the use of three or fewer screws to fix articular fragments in AO type C fractures was a significant risk for nonunion or loss of fixation. Plate configuration and surgical approach did not correlate with outcomes. Men had higher rates of complications and required more frequent revision surgery compared to women.

Recent Trends in Medicare Utilization and Reimbursement for Orthopaedic Procedures Performed at Ambulatory Surgery Centers.

BACKGROUND: As part of a market-driven response to the increasing costs of hospital-based surgical care, an increasing volume of orthopaedic procedures are being performed in ambulatory surgery centers (ASCs). The purpose of the present study was to identify recent trends in orthopaedic ASC procedure volume, utilization, and reimbursements in the Medicare system between 2012 and 2017. METHODS: This cross-sectional, national study tracked annual Medicare claims and payments and aggregated data at the county level. Descriptive statistics and multivariate regression models were used to evaluate trends in procedure volume, utilization rates, and reimbursement rates, and to identify demographic predictors of ASC utilization. RESULTS: A total of 1,914,905 orthopaedic procedures were performed at ASCs in the Medicare population between 2012 and 2017, with an 8.8% increase in annual procedure volume and a 10.5% increase in average reimbursements per case. ASC orthopaedic procedure utilization, including utilization across all subspecialties, is strongly associated with metropolitan areas compared with rural areas. In addition, orthopaedic procedure utilization, including for sports and hand procedures, was found to be significantly higher in wealthier counties (measured by average household income) and in counties located in the South. CONCLUSIONS: This study demonstrated increasing orthopaedic ASC procedure volume in recent years, driven by increases in hand procedure volume. Medicare reimbursements per case have steadily risen and outpaced the rate of inflation over the study period. However, as orthopaedic practice overhead continues to increase, other Medicare expenditures such as hospital payments and operational and implant costs also must be evaluated. These findings may provide a source of information that can be used by orthopaedic surgeons, policy makers, investors, and other stakeholders to make informed decisions regarding the costs and benefits of the use of ASCs for orthopaedic procedures.

State Medical Cannabis Laws Associated With Reduction in Opioid Prescriptions by Orthopaedic Surgeons in Medicare Part D Cohort.

INTRODUCTION: Opioid prescriptions and abuse remain a significant national concern. Cannabinoids offer a potentially attractive nonopioid analgesic option for orthopaedic patients, and 32 US states have passed medical cannabis laws (MCLs), legalizing patient access to cannabinoids. We examine the association between implementation of state cannabis laws and prescribing patterns for opioids by orthopaedic surgeons in Medicare Part D patients between 2013 and 2017. METHODS: Using the Medicare Part D Prescription Drug Event database, we measured annual aggregate daily doses of all opioid medications (excluding buprenorphine) prescribed by orthopaedic surgeons in each US state (and DC), in addition to total daily doses of opioid medications by generic name (hydrocodone, oxycodone, fentanyl, morphine, methadone, and "other opioids"). We used adjusted linear regression models to examine associations between state-specific cannabis regulations (state MCL, MCL type-dispensary or home cultivation, and recreational cannabis legalization) and annual total daily doses of opioid medications (all opioids and opioid types, separately). RESULTS: State MCLs were associated with a statistically significant reduction in aggregate opioid prescribing of 144,000 daily doses (19.7% reduction) annually (95% confidence interval [CI], -0.535 to -0.024 million; P < 0.01). States with MCLs allowing access to in-state dispensaries had a statistically significant reduction in total opioid prescriptions of 96,000 daily doses (13.1%) annually (95% CI, -0.165 to -0.026 million; P < 0.01). Specifically, MCLs were associated with a statistically significant reduction of 72,000 daily doses of hydrocodone annually (95% CI, -0.164 to -0.019 million; P < 0.01). No significant association between recreational marijuana legalization and opioid prescribing was found. CONCLUSION: Orthopaedic surgeons are among the highest prescribers of opioids, highlighting the importance of providing nonopioid analgesic alternatives in efforts to reduce opioid use in the patient cohort. This study is the first to examine the association between implementation of state cannabis laws and prescribing patterns for opioids by orthopaedic surgeons in Medicare Part D patients. LEVEL OF EVIDENCE: Population-based ecological study.

Recent trends in Medicare utilization and surgeon reimbursement for shoulder arthroplasty.

BACKGROUND: Recent efforts to contain health care costs and move toward value-based health care have intensified, with a continued focus on Medicare expenditures, especially for high-volume procedures. As total shoulder arthroplasty (TSA) volume continues to increase, especially within the Medicare population, it is important for orthopedic surgeons to understand recent trends in the allocation of health care expenditures and potential effects on reimbursements. The purpose of this study was to evaluate trends in annual Medicare utilization and provider reimbursement rates for shoulder arthroplasty procedures between 2012 and 2017. METHODS: This study tracked annual Medicare claims and payments to shoulder arthroplasty surgeons via publicly available databases and aggregated data at the county level. Descriptive statistics were used to evaluate trends in procedure volume, utilization rate (per 10,000 Medicare beneficiaries), and reimbursement rate. We used adjusted multiple linear regression models to examine associations between county-specific variables (ie, urban or rural, average household income, poverty rate, percentage Medicare population, and race and ethnicity demographics) and procedure volume, utilization rate, and reimbursement rate. RESULTS: Between 2012 and 2017, there was an 81.3% increase in primary TSA volume and 55.5% increase in primary TSA utilization. The Midwest and South had higher utilization rates than the Northeast and West (P < .001). TSA utilization rates in metropolitan areas were significantly higher than in rural areas (P < .001). Utilization rates for primary TSA procedures also had a significant negative association with poverty rate (P < .001). Regarding reimbursements, the Medicare payment per TSA case decreased from 2012 to 2017, with overall inflation-adjusted decreases of 7.1% and 11.8% for primary and revision cases, respectively. TSAs performed in metropolitan areas received significantly higher reimbursements per case than TSAs performed in rural areas ($1108.05 and $1066.40, respectively; P = .002). Furthermore, reimbursements per case were on average higher in the Northeast and West than in the South and Midwest (P < .001). CONCLUSIONS: Our study confirms that although TSA volume and per capita utilization have increased dramatically since 2012, Medicare Part B reimbursements to surgeons have continued to fall even after the adoption of bundled-payment models for orthopedic procedures. Cost-containment efforts continue to focus on Medicare reimbursements to surgeons, although other expenditures such as hospital payments and operational and implant costs must also be evaluated as part of an overall transition to value-based health care.

Three-Dimensional Printing for Preoperative Planning and Pedicle Screw Placement in Adult Spinal Deformity: A Systematic Review.

STUDY DESIGN: Systematic review. OBJECTIVES: This current systematic review seeks to identify current applications and surgical outcomes for 3-dimensional printing (3DP) in the treatment of adult spinal deformity. METHODS: A comprehensive search of publications was conducted through literature databases using relevant keywords. Inclusion criteria consisted of original studies, studies with patients with adult spinal deformities, and studies focusing on the feasibility and/or utility of 3DP technologies in the planning or treatment of scoliosis and other spinal deformities. Exclusion criteria included studies with patients without adult spinal deformity, animal subjects, pediatric patients, reviews, and editorials. RESULTS: Studies evaluating the effect of 3DP drill guide templates found higher screw placement accuracy in the 3DP cohort (96.9%), compared with non-3DP cohorts (81.5%, P < .001). Operative duration was significant decreased in 3DP cases (378 patients, 258 minutes) relative to non-3DP cases (301 patients,272 minutes, P < .05). The average deformity correction rate was 72.5% in 3DP cases (245 patients). There was no significant difference in perioperative blood loss between 3DP (924.6 mL, 252 patients) and non-3DP cases (935.6 mL, 177 patients, P = .058). CONCLUSIONS: Three-dimensional printing is currently used for presurgical planning, patient and trainee communication and education, pre- and intraoperative guides, and screw drill guides in the treatment of scoliosis and other adult spinal deformities. In adult spinal deformity, the usage of 3DP guides is associated with increased screw accuracy and favorable deformity correction outcomes; however, average costs and production lead time are highly variable between studies.

Association between shoulder coracoacromial arch morphology and anterior instability of the shoulder.

BACKGROUND: Glenohumeral instability is a common condition of the shoulder. Glenoid bone loss and humeral head bone loss are well recognized as risk factors for recurrent instability. There are few studies in the literature that examine the role of coracoacromial arch anatomy in the pathogenesis of glenohumeral instability. Previous reports found an association between posterior acromial coverage (PAC) and posterior instability. We hypothesize that coracoacromial arch anatomy is related to anterior shoulder instability. METHODS: In this retrospective cohort study, 50 patients with unidirectional anterior shoulder instability were matched to a control group of 50 glenohumeral arthritis patients without any history of shoulder instability. Radiographic measurements of the coracoacromial arch anatomy were made: shoulder arch angle, scapular Y angle, anterior coracoid tilt (ACT), posterior acromial tilt, anterior acromial coverage angle, PAC angle, coracoid height, posterior acromial height, and critical shoulder angle were determined using standard lateral scapular and anteroposterior radiographs. RESULTS: Logistic regression analyses found a significant association between the presence of anterior instability and flatter coracoacromial arch angles (mean, 124.1°) vs. the arthritis control group (mean, 120.6°) (odds ratios [OR] = 1.113; 95% confidence interval [CI] = 1.039-1.191; P = .002). There was a significant association between anterior instability and ACT (OR = 1.144; 95% CI = 1.053-1.243; P = .001), whereas a negative association was found between anterior instability and PAC (OR = 0.909; 95% CI = 0.853-0.969; P = .004) and posterior acromial tilt (OR = 0.878; 95% CI = 0.773-0.998; P = .046). Lower critical shoulder angle values were associated with the arthritis group (28.2° vs. 33.9°) (OR = 1.555; 95% CI = 1.202-2.012; P = .001). CONCLUSIONS: Shoulder coracoacromial arch morphology may play a role in the stability of the shoulder joint and development of recurrent anterior instability. Shoulders with a decreased shoulder arch angle, a less contained and flatter coracoacromial arch and larger ACT, were associated with anterior instability. This study identifies the shoulder coracoacromial arch angle and anterior coracoid tile angles as risk factors for anterior shoulder instability. Our findings suggest that measuring these angles may help orthopedic surgeons understand the risk of anterior instability and analyze risk factors to improve clinical decision making.

A Systematic Review of the Orthopedic Literature Involving National Hockey League Players.

BACKGROUND: Orthopedic injuries of National Hockey League (NHL) players are common and may significantly affect players' health and careers. Evidence-based injury management is important in guiding players' timely return to sport and their ability to play at their pre-injury levels of competition. PURPOSE: To summarize all data published between January 1980 and March 2020 on orthopedic injuries experienced by professional ice hockey players competing in the NHL. STUDY DESIGN: Systematic review. METHODS: A literature review of studies examining orthopedic injuries in the NHL was performed using the Embase, PubMed, and CINAHL databases. The review included studies focusing on NHL players and players attending the NHL Combine and preseason NHL team camps. Studies pertaining to non-orthopedic injuries and case reports were excluded. RESULTS: A total of 39 articles met the inclusion criteria and were analyzed. The articles were divided by anatomic site of injury for further analysis: hip and pelvis (24%), general/other (14%), ankle (10%), knee (10%), foot (7%), shoulder (7%), thigh (7%), trunk (7%), spine (6%), elbow (4%), and hand and wrist (4%). The majority of articles were Level IV Evidence (51.3%), followed by Level III Evidence (38.5%). Most studies obtained data from publicly available internet resources (24.7%), player medical records (19.5%) or surveys of team physicians and athletic trainers (15.5%). A much smaller number of studies utilized the NHL Injury Surveillance System (NHLISS) (6.5%) or the Athlete Health Management System (AHMS) (2.6%). CONCLUSION: This systematic review provides NHL team physicians with a single source of the current literature regarding orthopedic injuries in NHL players. Most research was published on hip and pelvis (24%) injuries, did not utilize the NHLISS and consisted of Level IV Evidence.

Medicare Utilization and Reimbursement for Vertebroplasty and Kyphoplasty: A National Analysis From 2012-2017.

STUDY DESIGN: Retrospective cohort study OBJECTIVE.: This study seeks to identify recent trends in utilization and reimbursements of these procedures between 2012and 2017, a period which experienced a change in national guideline recommendations for these procedures. SUMMARY OF BACKGROUND DATA: Minimally invasive vertebral augmentation procedures, including vertebroplasty and kyphoplasty, have been typically reserved for fractures associated with refractory pain, deformity, or progressive neurological symptoms. However, controversy exists regarding the safety and effectiveness of these procedures, in particular vertebroplasty. METHODS: Annual Medicare claims and payments to surgeons were aggregated at the county level to assess regional trends. Descriptive statistics and multivariate regression models were used to evaluate trends in procedure volume, utilization rates, and reimbursement rates, and to examine associations between county-specific variables and outcome variables. RESULTS: A total of 24,316 vertebroplasties and 138,778 kyphoplasties were performed in the Medicare population between 2012 and 2017. Annual vertebroplasty volume fell by 48.0% from 5744 procedures in 2012 to 2987 in 2017, with a compound annual growth rate (CAGR) of -12.3%. Annual kyphoplasty volume also declined by 12.7% (CAGR -2.7%), from 24,986 in 2012 to 21,681 in 2017. Surgeon reimbursements for vertebral augmentation procedures increased by a weighted average of 93.7% (inflation-adjusted increase of 78.2%) between 2012 and 2017, which was primarily driven by a dramatic 113.3% (inflation-adjusted increase of 96.2%) increase in mean reimbursements for kyphoplasty procedures from an average of $895 to $1764, between 2012 and 2017, respectively. CONCLUSION: This large national Medicare database study found that vertebroplasty and kyphoplasty procedure volume and utilization of both procedures have declined significantly. Although average reimbursements to surgeons for vertebroplasties have significantly declined, payments for kyphoplasty procedures have risen significantly. Although vertebroplasty volume has significantly decreased, it is still being performed and being reimbursed for, in spite of its controversial role in its treatment of vertebral fractures. LEVEL OF EVIDENCE: 3.

Hospital and Surgeon Medicare Reimbursement Trends for Total Joint Arthroplasty.

BACKGROUND: Over 1 million total joint arthroplasties (TJAs) are performed every year in the United States, creating Medicare cost concerns for policy makers. The purpose of this study is to evaluate recent trends in Medicare utilization and reimbursements to hospitals/surgeons for TJAs between 2012 and 2017. METHODS: We tracked annual Medicare claims and payments to TJA surgeons using publicly available Medicare databases and aggregated data at the county level. Descriptive statistics and multivariate regression models were used to evaluate trends in procedure volume, utilization (per 10,000 Medicare beneficiaries), and reimbursement rates and to examine associations between county-specific variables and TJA utilization and reimbursements. RESULTS: Between 2012 and 2017, there was an 18.9% increase in annual primary TJA volume (357,500 cases in 2012 to 425,028 cases in 2017) and a 2.0% increase in annual primary TJA per capita utilization (73.4 cases per 10,000 Medicare beneficiaries in 2012 to 74.8 in 2017). The Midwest and the South had higher utilization rates compared with the Northeast and West (P < .001). Utilization rates for primary TJA procedures also had a significant negative association with the poverty rate (P < .001). Medicare Part B payments to surgeons fell by 7.5%, equivalent to a 14.9% inflation-adjusted decline, whereas hospital reimbursements and charges increased by 0.3% and 18.6%, respectively, during the study period. CONCLUSIONS: Despite increasing TJA volume and utilization, surgeon reimbursements have continued to decline, whereas hospital payments and hospital charges have increased significantly more than surgeon charges. Cost containment efforts will need to address other expenditures such as hospital costs and implant costs to better align financial risks and incentives for TJA surgeons.

Recent trends in medicare utilization and reimbursement for anterior cervical discectomy and fusion.

BACKGROUND CONTEXT: Anterior cervical discectomy and fusion (ACDF) has been considered the gold standard for treating various cervical spine pathologies stemming from cervical degenerative disorders. While cervical artificial disc replacement has emerged as an alternative in select cases, ACDF still remains a commonly performed procedure. PURPOSE: This study seeks to define the costs of ACDF and identify trends and variations in ACDF volume, utilization, and surgeon and hospital reimbursement rates. STUDY DESIGN/SETTING: Retrospective analysis of patients undergoing ACDF PATIENT SAMPLE: Medicare patients undergoing ACDF between 2012 and 2017 OUTCOME MEASURES: ACDF volume, utilization rates, and surgeon/hospital reimbursement rates METHODS: This study tracked annual Medicare claims and payments to ACDF surgeons using publicly-available databases and aggregated data at the county level. Descriptive statistics and multivariate regression models were used to evaluate trends in procedure volume, utilization rates (per 10,000 Medicare beneficiaries), and reimbursement rates, and to examine associations between county-specific variables (ie, urban or rural, average household income, poverty rate, percent Medicare population, race/ethnicity demographics), and ACDF utilization and reimbursement rates. RESULTS: A total of 264,673 ACDF surgeries were performed in the Medicare population from 2012 to 2017, with a 24.2% increase in annual procedure volume. Utilization also increased by 6.5% from 8.0 surgeries per 10,000 Medicare beneficiaries in 2012 to 8.5 in 2017. Hospital reimbursements for cervical spine fusion surgeries without complications or co-morbidities experienced nominal and inflation-adjusted increases of 9.5% and 0.7%, respectively, from $12,030.11 in 2012 to $13,167.64 in 2017. Surgeon reimbursements for single-level and multilevel ACDF each nominally decreased from $958.11 and $1,173.01, respectively, in 2012 to $950.34 and $1,138.41 in 2017 (a 0.8% and 2.9% decrease, respectively), but after adjusting for inflation, reimbursements per case fell by an average of 8.7% and 10.7%, respectively. In contrast, mean reimbursements per case for hospitals rose by 7.1% (1.5% inflation-adjusted decrease). A significant upward yearly trend in ambulatory surgical centers volume, resulted in a net increase of 184.5% between 2015 and 2017 (p<.001). CONCLUSIONS: While ACDF volume and utilization has continued to increase since 2012, Medicare payments to hospitals and surgeons have struggled to keep up with inflation. Our study confirms that Medicare reimbursement per case continues to decrease at a disproportionate rate for surgeons, compared to hospitals. The increasing trend in procedures performed at ambulatory surgical centers shows promise for a future model of cost-efficient and value-based care.