Evaluating the Need for Preoperative MRI Before Primary Hip Arthroscopy in Patients 40 Years and Younger With Femoroacetabular Impingement Syndrome: A Multicenter Comparative Analysis

BACKGROUND: Routine hip magnetic resonance imaging (MRI) before arthroscopy for patients with femoroacetabular impingement syndrome (FAIS) offers questionable clinical benefit, delays surgery, and wastes resources. PURPOSE: To assess the clinical utility of preoperative hip MRI for patients aged ≤40 years who were undergoing primary hip arthroscopy and who had a history, physical examination findings, and radiographs concordant with FAIS. STUDY DESIGN: Cohort study; Level of evidence, 3. METHODS: Included were 1391 patients (mean age, 25.8 years; 63% female; mean body mass index, 25.6) who underwent hip arthroscopy between August 2015 and December 2021 by 1 of 4 fellowship-trained hip surgeons from 4 referral centers. Inclusion criteria were FAIS, primary surgery, and age ≤40 years. Exclusion criteria were MRI contraindication, reattempt of nonoperative management, and concomitant periacetabular osteotomy. Patients were stratified into those who were evaluated with preoperative MRI versus those without MRI. Those without MRI received an MRI before surgery without deviation from the established surgical plan. All preoperative MRI scans were compared with the office evaluation and intraoperative findings to assess agreement. Time from office to arthroscopy and/or MRI was recorded. MRI costs were calculated. RESULTS: Of the study patients, 322 were not evaluated with MRI and 1069 were. MRI did not alter surgical or interoperative plans. Both groups had MRI findings demonstrating anterosuperior labral tears treated intraoperatively (99.8% repair, 0.2% debridement, and 0% reconstruction). Compared with patients who were evaluated with MRI and waited 63.0 ± 34.6 days, patients who were not evaluated with MRI underwent surgery 6.5 ± 18.7 days after preoperative MRI. MRI delayed surgery by 24.0 ± 5.3 days and cost a mean $2262 per patient. CONCLUSION: Preoperative MRI did not alter indications for primary hip arthroscopy in patients aged ≤40 years with a history, physical examination findings, and radiographs concordant with FAIS. Rather, MRI delayed surgery and wasted resources. Routine hip MRI acquisition for the younger population with primary FAIS with a typical presentation should be challenged

Impact of COVID-19 on cardiovascular testing in the United States versus the rest of the world

Objectives: This study sought to quantify and compare the decline in volumes of cardiovascular procedures between the United States and non-US institutions during the early phase of the coronavirus disease-2019 (COVID-19) pandemic. Background: The COVID-19 pandemic has disrupted the care of many non-COVID-19 illnesses. Reductions in diagnostic cardiovascular testing around the world have led to concerns over the implications of reduced testing for cardiovascular disease (CVD) morbidity and mortality. Methods: Data were submitted to the INCAPS-COVID (International Atomic Energy Agency Non-Invasive Cardiology Protocols Study of COVID-19), a multinational registry comprising 909 institutions in 108 countries (including 155 facilities in 40 U.S. states), assessing the impact of the COVID-19 pandemic on volumes of diagnostic cardiovascular procedures. Data were obtained for April 2020 and compared with volumes of baseline procedures from March 2019. We compared laboratory characteristics, practices, and procedure volumes between U.S. and non-U.S. facilities and between U.S. geographic regions and identified factors associated with volume reduction in the United States. Results: Reductions in the volumes of procedures in the United States were similar to those in non-U.S. facilities (68% vs. 63%, respectively; p = 0.237), although U.S. facilities reported greater reductions in invasive coronary angiography (69% vs. 53%, respectively; p < 0.001). Significantly more U.S. facilities reported increased use of telehealth and patient screening measures than non-U.S. facilities, such as temperature checks, symptom screenings, and COVID-19 testing. Reductions in volumes of procedures differed between U.S. regions, with larger declines observed in the Northeast (76%) and Midwest (74%) than in the South (62%) and West (44%). Prevalence of COVID-19, staff redeployments, outpatient centers, and urban centers were associated with greater reductions in volume in U.S. facilities in a multivariable analysis. Conclusions: We observed marked reductions in U.S. cardiovascular testing in the early phase of the pandemic and significant variability between U.S. regions. The association between reductions of volumes and COVID-19 prevalence in the United States highlighted the need for proactive efforts to maintain access to cardiovascular testing in areas most affected by outbreaks of COVID-19 infection

Approach to the Patient With Failed Hip Arthroscopy for Labral Tears and Femoroacetabular Impingement

There has been an exponential increase in the diagnosis and treatment of patients with femoroacetabular impingement, leading to a rise in the number of hip arthroscopies done annually. Despite reliable pain relief and functional improvements after hip arthroscopy in properly indicated patients, and due to these increased numbers, there is a growing number of patients who have persistent pain after surgery. The etiology of these continued symptoms is multifactorial, and clinicians must have a fundamental understanding of these causes to properly diagnose and manage these patients. Factors contributing to failure after surgery include those related to the patient, the surgeon, and the postoperative physical therapy. This review highlights common causes of failure, including those related to residual bony deformity as well as capsular deficiency, and provides a framework for diagnosis and treatment of these patients

Time-Driven Activity-based Costing for Anterior Cruciate Ligament Reconstruction: A Comparison to Traditional Accounting Methods

Purpose: The primary purpose of this study was to compare the cost of care of one of the most common sports medicine surgical procedures, anterior cruciate ligament reconstruction (ACLR), using the time-driven activity-based costing (TDABC) method to traditional accounting methods such as activity-based costing (ABC). Our secondary purpose was to identify the main drivers of the cost of ACLR using both of these techniques. Methods: A process map of ACLR was constructed through direct observation in the clinical setting according to established techniques to identify drivers of fixed, direct variable, and indirect costs. An episode of care consisted of each step in the surgical process from admission to discharge. Personnel costs were combined with the process map to determine the cost drivers and overall cost of the procedure. The cost generated from the TDABC method was compared with the cost from our institution\u27s internal accounting system, which used an ABC method. Results: The total cost of ACLR was $5,242.25 when using TDABC versus$10,318 when using the traditional ABC method. The largest difference between the 2 methods was within the domain of direct variable costs. Conclusions: When compared with TDABC, the hospital\u27s traditional cost-accounting estimate for ACLR is nearly twice as costly. These findings highlight the variability of cost calculation for the same clinical episode between the 2 accounting methods. For the traditional accounting method, the direct variable cost was the main cost driver, whereas for the TDABC method, the direct fixed cost was the main cost driver. Clinical Relevance: This study is important because it elucidates important cost drivers for one of the most common sports medicine orthopaedic surgical procedures and attempts to identify the true overall cost of the procedure

Advancements in Artificial Intelligence for Foot and Ankle Surgery: A Systematic Review

BACKGROUND: There has been a rapid increase in research applying artificial intelligence (AI) to various subspecialties of orthopaedic surgery, including foot and ankle surgery. The purpose of this systematic review is to (1) characterize the topics and objectives of studies using AI in foot and ankle surgery, (2) evaluate the performance of their models, and (3) evaluate their validity (internal or external validation). METHODS: A systematic literature review was conducted using PubMed/MEDLINE and Embase databases in December 2022. All studies that used AI or its subsets machine learning (ML) and deep learning (DL) in the setting of foot and ankle surgery relevant to orthopaedic surgeons were included. Studies were evaluated for their demographics, subject area, outcomes of interest, model(s) tested, model(s)\u27 performance, and validity (internal or external). RESULTS: A total of 31 studies met inclusion criteria: 14 studies investigated AI for image interpretation, 13 studies investigated AI for clinical predictions, and 4 studies were grouped as other. Studies commonly explored AI for ankle fractures, calcaneus fractures, hallux valgus, Achilles tendon pathologies, plantar fasciitis, and sports injuries. For studies reporting the area under the receiver operating characteristic curve (AUC), AUCs ranged from 0.64 (poor) to 0.99 (excellent). Two studies (6.45%) reported external validation. CONCLUSION: Applications of AI in the field of foot and ankle surgery are expanding, particularly for image interpretation and clinical predictions. Current model performances range from poor to excellent, and most studies lack external validation, demonstrating a need for further research prior to deploying AI-based clinical applications. LEVEL OF EVIDENCE: Level III, retrospective cohort study

Hip resurfacing arthroplasty as an alternative to total hip arthroplasty in patients aged under 40 years: a retrospective analysis of 267 hips

Aims: The aims of the study were to report for a cohort aged younger than 40 years: 1) indications for HRA; 2) patient-reported outcomes in terms of the modified Harris Hip Score (HHS); 3) dislocation rate; and 4) revision rate. Methods: This retrospective analysis identified 267 hips from 224 patients who underwent an hip resurfacing arthroplasty (HRA) from a single fellowship-trained surgeon using the direct lateral approach between 2007 and 2019. Inclusion criteria was minimum two-year follow-up, and age younger than 40 years. Patients were followed using a prospectively maintained institutional database. Results: A total of 217 hips (81%) were included for follow-up analysis at a mean of 3.8 years. Of the 23 females who underwent HRA, none were revised, and the median head size was 46 mm (compared to 50 mm for males). The most common indication for HRA was femoroacetabular impingement syndrome (n = 133), and avascular necrosis ( (n = 53). Mean postoperative HHS was 100 at two and five years. No dislocations occurred. A total of four hips (1.8%) required reoperation for resection of heterotopic ossification, removal of components for infection, and subsidence with loosening. The overall revision rate was 0.9%. Conclusion: For younger patients with higher functional expectations and increased lifetime risk for revision, HRA is an excellent bone preserving intervention carrying low complication rates, revision rates, and excellent patient outcomes without lifetime restrictions allowing these patients to return to activity and sport. Thus, in younger male patients with end-stage hip disease and higher demands, referral to a high-volume HRA surgeon should be considered. Cite this article: Bone Jt Open 2023;4(6):408–415

Artificial intelligence-based applications in shoulder surgery leaves much to be desired: a systematic review

Background: Artificial intelligence (AI) aims to simulate human intelligence using automated computer algorithms. There has been a rapid increase in research applying AI to various subspecialties of orthopedic surgery, including shoulder surgery. The purpose of this review is to assess the scope and validity of current clinical AI applications in shoulder surgery literature. Methods: A systematic literature review was conducted using PubMed for all articles published between January 1, 2010 and June 10, 2022. The search query used the terms as follows: (artificial intelligence OR machine learning OR deep learning) AND (shoulder OR shoulder surgery OR rotator cuff). All studies that examined AI application models in shoulder surgery were included and evaluated for model performance and validation (internal, external, or both). Results: A total of 45 studies were included in the final analysis. Eighteen studies involved shoulder arthroplasty, 13 rotator cuff, and 14 other areas. Studies applying AI to shoulder surgery primarily involved (1) automated imaging analysis including identifying rotator cuff tears and shoulder implants (2) risk prediction analyses including perioperative complications, functional outcomes, and patient satisfaction. Highest model performance area under the curve ranged from 0.681 (poor) to 1.00 (perfect). Only 2 studies reported external validation. Conclusion: Applications of AI in the field of shoulder surgery are expanding rapidly and offer patient-specific risk stratification for shared decision-making and process automation for resource preservation. However, model performance is modest and external validation remains to be demonstrated, suggesting increased scientific rigor is warranted prior to deploying AI-based clinical applications

Machine Learning Outperforms Logistic Regression Analysis to Predict Next-Season NHL Player Injury: An Analysis of 2322 Players From 2007 to 2017

© The Author(s) 2020. Background: The opportunity to quantitatively predict next-season injury risk in the National Hockey League (NHL) has become a reality with the advent of advanced computational processors and machine learning (ML) architecture. Unlike static regression analyses that provide a momentary prediction, ML algorithms are dynamic in that they are readily capable of imbibing historical data to build a framework that improves with additive data. Purpose: To (1) characterize the epidemiology of publicly reported NHL injuries from 2007 to 2017, (2) determine the validity of a machine learning model in predicting next-season injury risk for both goalies and position players, and (3) compare the performance of modern ML algorithms versus logistic regression (LR) analyses. Study Design: Descriptive epidemiology study. Methods: Professional NHL player data were compiled for the years 2007 to 2017 from 2 publicly reported databases in the absence of an official NHL-approved database. Attributes acquired from each NHL player from each professional year included age, 85 performance metrics, and injury history. A total of 5 ML algorithms were created for both position player and goalie data: random forest, K Nearest Neighbors, Naïve Bayes, XGBoost, and Top 3 Ensemble. LR was also performed for both position player and goalie data. Area under the receiver operating characteristic curve (AUC) primarily determined validation. Results: Player data were generated from 2109 position players and 213 goalies. For models predicting next-season injury risk for position players, XGBoost performed the best with an AUC of 0.948, compared with an AUC of 0.937 for LR (P \u3c.0001). For models predicting next-season injury risk for goalies, XGBoost had the highest AUC with 0.956, compared with an AUC of 0.947 for LR (P \u3c.0001). Conclusion: Advanced ML models such as XGBoost outperformed LR and demonstrated good to excellent capability of predicting whether a publicly reportable injury is likely to occur the next season

Interobserver and Intraobserver Reliability of an MRI-Based Classification System for Injuries to the Ulnar Collateral Ligament.

BACKGROUND: Despite improvements in understanding biomechanics and surgical options for ulnar collateral ligament (UCL) tears, there remains a need for a reliable classification of UCL tears that has the potential to guide clinical decision making. PURPOSE: To assess the intra- and interobserver reliability of the newly proposed magnetic resonance imaging (MRI)-based classification for UCL tears. Secondary objectives included assessing the effect of additional views, discrimination between distal and nondistal tears, and correlation of imaging reads with intraoperative findings of the UCL. STUDY DESIGN: Cohort study (diagnosis); Level of evidence, 2. METHODS: Nine fellowship-trained specialists from 7 institutions independently completed 4 surveys consisting of 60 elbow MRI scans with UCL tears using a newly proposed 6-stage classification system. The first and third surveys contained 60 coronal images, while the second and fourth contained the same images with coronal and axial views presented in a random order to assess intraobserver variability via the weighted kappa value and the effect of additional imaging views. Weighted kappa values were also calculated for each of the 4 surveys to acquire interobserver reliability. Reliability analysis was repeated through a 2-group classification analysis for distal and nondistal tears. Observer readings were compared with intraoperative UCL findings. RESULTS: For the newly proposed 6-stage MRI-based classification, intra- and interobserver reliability demonstrated near perfect and substantial agreement, respectively. These values increased only when substratified into the 2-group distal and nondistal tear classification ( P \u3c .05). The additional axial view did not statistically improve the agreement within and among readers. When compared with intraoperative findings from 30 elbows, observer readings were accurate for tear grade (partial and complete), proximal location, and distal location but not midsubstance tears. CONCLUSION: The newly proposed 6-stage MRI-based classification utilizing grade and location of the injury had substantial to near perfect agreement among and within fellowship-trained observers