Are our actions matching our words? A review of trainee ethnic and gender diversity in orthopaedic surgery

Background

There is a lack of physician ethnic and gender diversity amongst surgical specialties. This study analyzes the literature that promotes diversity amongst surgical trainees. Specifically, this study sought to answer (i) how the number of publications regarding diversity in orthopaedic surgery compares to other surgical specialties, (ii) how the number of publications amongst all surgical subspecialties trends over time and (iii) which specific topics regarding diversity are discussed in the surgical literature.

Methods

The Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines were used to query articles from PubMed, Web of Science, Embase and the Cumulative Index to Nursing and Allied Health Literature. Broad inclusion criteria for both ethnic and gender diversity of any surgical specialty were utilized.

Results

Our query resulted 1429 publications, of which 408 duplicates were removed, and 701 were excluded on title and abstract screening, leaving 320 to be included. The highest number of related publications was in orthopaedic surgery (n = 73) followed by general surgery (n = 56). Out of 320 total articles, 260 (81.3 %) were published after 2015, and 56 of 73 (76.7 %) orthopaedic-specific articles were published after 2015.

Conclusion

Orthopaedic surgery published the most about ethnic and gender diversity, however, still remains one of the least diverse surgical specialties. With the recent increase in publications on diversity in surgical training, close attention should be paid to ethnic and gender diversity amongst surgical trainees over the coming years. Should diversity remain stagnant, diversification efforts may need to be restructured to achieve a diverse surgeon workforce.

Key message

Orthopaedic surgery is the surgical subspecialty that publishes the most about trainee ethnic and gender diversity followed by general surgery. With most of this literature being published over the last eight years, it is imperative to pay close attention to the ethnic and gender landscape of the surgeon workforce over the coming years.

Characteristics and Outcomes of US Veterans With Immunocompromised Conditions at High Risk of SARS-CoV-2 Infection With or Without Receipt of Oral Antiviral Agents

OBJECTIVES

Molnupiravir and nirmatrelvir-ritonavir were the first oral antiviral agents to demonstrate reduced hospitalization or death in patients with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), but patients with immunocompromised conditions were not well-represented. The objective of this study was to characterize and compare the clinical outcomes of US veterans with immunocompromised conditions prescribed oral antivirals with those who did not receive oral antivirals for mild-to-moderate SARS-CoV-2 active infection.

METHODS

This was a retrospective, observational, nationwide propensity-matched analysis of US veterans with immunocompromised conditions who developed documented SARS-CoV-2 infection. The primary outcome was the composite of any hospitalization or death within 30 days of diagnosis. Secondary outcomes included 30-day comparative rates of (1) any hospitalization, (2) death, (3) intensive care requirement, and (4) subset analyses of outcomes by oral antiviral used and vaccination status.

RESULTS

The composite primary outcome was significantly lower in patients receiving oral antiviral therapy compared with those who did not (23/390 [5.9%] vs 57/390 [14.6%]; odds ratio, 0.37; 95% confidence interval, .22-.61). This difference was driven largely by fewer deaths in the oral antiviral group (1/390 [0.3%] vs 19/390 [4.9%]; odds ratio, 0.05; 95% confidence interval, .007-.38). There was no significant difference in rate of intensive care requirement. The composite outcome was improved in vaccinated patients (completing the first series or first booster dose) who received oral antiviral agents compared with those who did not receive oral antiviral agents. Compared with those prescribed nirmatrelvir-ritonavir, patients given molnupiravir were older, had a higher incidence of cautions/contraindications, greater prevalence of tobacco use, and more cardiovascular complications.

CONCLUSIONS

Use of molnupiravir or nirmatrelvir-ritonavir was associated with lower incidences of hospitalization or death within 30 days of diagnosis in US veterans with immunocompromised conditions, regardless of vaccination status. These findings support the use of either oral antiviral in this patient population.

Rotator cuff tears

Rotator cuff tears are the most common upper extremity condition seen by primary care and orthopaedic surgeons, with a spectrum ranging from tendinopathy to full-thickness tears with arthritic change. Some tears are traumatic, but most rotator cuff problems are degenerative. Not all tears are symptomatic and not all progress, and many patients in whom tears become more extensive do not experience symptom worsening. Hence, a standard algorithm for managing patients is challenging. The pathophysiology of rotator cuff tears is complex and encompasses an interplay between the tendon, bone and muscle. Rotator cuff tears begin as degenerative changes within the tendon, with matrix disorganization and inflammatory changes. Subsequently, tears progress to partial-thickness and then full-thickness tears. Muscle quality, as evidenced by the overall size of the muscle and intramuscular fatty infiltration, also influences symptoms, tear progression and the outcomes of surgery. Treatment depends primarily on symptoms, with non-operative management sufficient for most patients with rotator cuff problems. Modern arthroscopic repair techniques have improved recovery, but outcomes are still limited by a lack of understanding of how to improve tendon to bone healing in many patients.

Development and validation of a multivariable prediction model in pediatric liver transplant patients for predicting intensive care unit length of stay

BACKGROUND

Liver transplantation is the life-saving treatment for many end-stage pediatric liver diseases. The perioperative course, including surgical and anesthetic factors, have an important influence on the trajectory of this high-risk population. Given the complexity and variability of the immediate postoperative course, there would be utility in identifying risk factors that allow prediction of adverse outcomes and intensive care unit trajectories.

AIMS

The aim of this study was to develop and validate a risk prediction model of prolonged intensive care unit length of stay in the pediatric liver transplant population.

METHODS

This is a retrospective analysis of consecutive pediatric isolated liver transplant recipients at a single institution between April 1, 2013 and April 30, 2020. All patients under the age of 18 years receiving a liver transplant were included in the study (n = 186). The primary outcome was intensive care unit length of stay greater than 7 days.

RESULTS

Recipient and donor characteristics were used to develop a multivariable logistic regression model. A total of 186 patients were included in the study. Using multivariable logistic regression, we found that age < 12 months (odds ratio 4.02, 95% confidence interval 1.20-13.51, p = .024), metabolic or cholestatic disease (odds ratio 2.66, 95% confidence interval 1.01-7.07, p = .049), 30-day pretransplant hospital admission (odds ratio 8.59, 95% confidence interval 2.27-32.54, p = .002), intraoperative red blood cells transfusion >40 mL/kg (odds ratio 3.32, 95% confidence interval 1.12-9.81, p = .030), posttransplant return to the operating room (odds ratio 11.45, 95% confidence interval 3.04-43.16, p = .004), and major postoperative respiratory event (odds ratio 32.14, 95% confidence interval 3.00-343.90, p < .001) were associated with prolonged intensive care unit length of stay. The model demonstrates a good discriminative ability with an area under the receiver operative curve of 0.888 (95% confidence interval, 0.824-0.951).

CONCLUSIONS

We develop and validate a model to predict prolonged intensive care unit length of stay in pediatric liver transplant patients using risk factors from all phases of the perioperative period.

Injury prevention strategies at the 2019 FIFA Women's World Cup display a multifactorial approach and highlight subjective wellness measurements

OBJECTIVE

To report the injury prevention programs utilised by top-level female footballers competing internationally.

METHODS

An online survey was administered to physicians of the 24 competing national teams at the 2019 Federation Internationale de Football Association (FIFA) Women's World Cup. The survey included 4 sections regarding perceptions and practices concerning non-contact injuries: (1) risk factors, (2) screening tests and monitoring tools, (3) preventative strategies, and (4) reflection on their World Cup experience.

RESULTS

Following responses from 54% of teams, the most common injuries encountered included muscle strains, ankle sprains, and anterior cruciate ligament ruptures. The study also revealed the most important injury risk factors during the FIFA 2019 World Cup. Intrinsic risk factors include accumulated fatigue, previous injury, and strength endurance. Extrinsic risk factors include reduced recovery time between matches, congested match schedule, and the number of club team matches played. The 5 most used tests for risk factors were flexibility, joint mobility, fitness, balance, and strength. Monitoring tools commonly used were subjective wellness, heart rate, minutes/matches played, and daily medical screening. Specific strategies to limit the risk of an anterior cruciate ligament injury included the FIFA 11+ program and proprioception training.

CONCLUSION

The present study revealed multifactorial approaches to injury prevention strategies for women's national football teams at the FIFA 2019 World Cup. Challenges to injury prevention program implementation reflect time limitations, schedule uncertainties, and varying club team recommendations.

LEVEL OF EVIDENCE

IV.

Integration of population-level data sources into an individual-level clinical prediction model for dengue virus test positivity

The differentiation of dengue virus (DENV) infection, a major cause of acute febrile illness in tropical regions, from other etiologies, may help prioritize laboratory testing and limit the inappropriate use of antibiotics. While traditional clinical prediction models focus on individual patient-level parameters, we hypothesize that for infectious diseases, population-level data sources may improve predictive ability. To create a clinical prediction model that integrates patient-extrinsic data for identifying DENV among febrile patients presenting to a hospital in Thailand, we fit random forest classifiers combining clinical data with climate and population-level epidemiologic data. In cross validation, compared to a parsimonious model with the top clinical predictors, a model with the addition of climate data, reconstructed susceptibility estimates, force of infection estimates, and a recent case clustering metric, significantly improved model performance.

National Patterns in Utilization of Knee and Hip Arthroscopy: An Analysis of Racial, Ethnic, and Geographic Disparities in the United States

Background

Racial and ethnic disparities in the field of orthopaedic surgery have been reported extensively across many subspecialties. However, these data remain relatively sparse in orthopaedic sports medicine, especially with respect to commonly performed procedures including knee and hip arthroscopy.

Purpose

To assess (1) differences in utilization of knee and hip arthroscopy between White, Black, Hispanic, and Asian or Pacific Islander patients in the United States (US) and (2) how these differences vary by geographical region.

Study Design

Descriptive epidemiology study.

Methods

The study sample was acquired from the 2019 National Ambulatory Surgery Sample database. Racial and ethnic differences in age-standardized utilization rates of hip and knee arthroscopy were calculated using survey weights and population estimates from US census data. Poisson regression was used to model age-standardized utilization rates for hip and knee arthroscopy while controlling for several demographic and clinical variables.

Results

During the study period, rates of knee arthroscopy utilization among White patients were significantly higher than those of Black, Hispanic, and Asian or Pacific Islander patients (ie, per 100,000, White: 180.5, Black: 113.2, Hispanic: 122.2, and Asian: 58.6). Disparities were even more pronounced among patients undergoing hip arthroscopy, with White patients receiving the procedure at almost 4 to 5 times higher rates (ie, per 100,000, White: 12.6, Black: 3.2, Hispanic: 2.3, Asian or Pacific Islander: 1.8). Disparities in knee and hip arthroscopy utilization between White and non-White patients varied significantly by region, with gaps in knee arthroscopy being most pronounced in the Midwest (adjusted rate ratio, 2.0 [95% CI, 1.9-2.1]) and those in hip arthroscopy being greatest in the West (adjusted rate ratio, 5.3 [95% CI, 4.9-5.6]).

Conclusion

Racial and ethnic disparities in the use of knee and hip arthroscopy were found across the US, with decreased rates among Black, Hispanic, and Asian or Pacific Islander patients compared with White patients. Disparities were most pronounced in the Midwest and South and greater for hip than knee arthroscopy, possibly demonstrating emerging inequality in a rapidly growing and evolving procedure across the country.

Risk Factors for Graft Failure After Meniscal Allograft Transplantation: A Systematic Review and Meta-analysis

Background

Graft failure after meniscal allograft transplantation (MAT) may necessitate revision surgery or conversion to arthroplasty. A comprehensive understanding of the risk factors for failure after MAT of the knee may facilitate more informed shared decision-making discussions before surgery and help determine whether MAT should be performed based on patient risk.

Purpose

To perform a systematic review and meta-analysis of risk factors associated with graft failure after MAT of the knee.

Study Design

Systematic review; Level of evidence, 4.

Methods

The PubMed, OVID/Medline, and Cochrane databases were queried in October 2021. Data pertaining to study characteristics and risk factors associated with failure after MAT were recorded. DerSimonian-Laird binary random-effects models were constructed to quantitatively evaluate the association between risk factors and MAT graft failure by generating effect estimates in the form of odds ratios (ORs) with 95% CIs. Qualitative analysis was performed to describe risk factors that were variably reported.

Results

In total, 17 studies including 2184 patients were included. The overall pooled prevalence of failure at the latest follow-up was 17.8% (range, 3.3%-81.0%). In 10 studies reporting 5-year failure rates, the pooled prevalence of failure was 10.9% (range, 4.7%-23%). In 4 studies reporting 10-year failure rates, the pooled prevalence was 22.7% (range, 8.1%-55.0%). A total of 39 risk factors were identified, although raw data presented in a manner amenable to meta-analysis only allowed for 3 to be explored quantitatively. There was strong evidence to support that an International Cartilage Regeneration & Joint Preservation Society grade >3a (OR, 5.32; 95% CI, 2.75-10.31; P < .001) was a significant risk factor for failure after MAT. There was no statistically significant evidence to incontrovertibly support that patient sex (OR, 2.16; 95% CI, 0.83-5.64; P = .12) or MAT laterality (OR, 1.11; 95% CI, 0.38-3.28; P = .85) was associated with increased risk of failure after MAT.

Conclusion

Based on the studies reviewed, there was strong evidence to suggest that degree of cartilage damage at the time of MAT is associated with graft failure; however, the evidence was inconclusive on whether laterality or patient sex is associated with graft failure.

A guide to appropriately planning and conducting meta-analyses: part 3. Special considerations-the network meta-analysis

The meta-analysis has become one of the predominant studies designs in orthopaedic literature. Within recent years, the network meta-analysis has been implicated as a powerful approach to comparing multiple treatments for an outcome of interest when conducting a meta-analysis (as opposed to two competing treatments which is typical of a traditional meta-analysis). With the increasing use of the network meta-analysis, it is imperative for readers to possess the ability to independently and critically evaluate these types of studies. The purpose of this article is to provide the necessary foundation of knowledge to both properly conduct and interpret the results of a network meta-analysis.

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.

Lower donor site morbidity with hamstring and quadriceps tendon autograft compared with bone-patellar tendon-bone autograft after anterior cruciate ligament reconstruction: a systematic review and network meta-analysis of randomized controlled trials

PURPOSE

To perform a meta-analysis of RCTs evaluating donor site morbidity after bone-patellar tendon-bone (BTB), hamstring tendon (HT) and quadriceps tendon (QT) autograft harvest for anterior cruciate ligament reconstruction (ACLR).

METHODS

PubMed, OVID/Medline and Cochrane databases were queried in July 2022. All level one articles reporting the frequency of specific donor-site morbidity were included. Frequentist model network meta-analyses with P-scores were conducted to compare the prevalence of donor-site morbidity, complications, all-cause reoperations and revision ACLR among the three treatment groups.

RESULTS

Twenty-one RCTs comprising the outcomes of 1726 patients were included. The overall pooled rate of donor-site morbidity (defined as anterior knee pain, difficulty/impossibility kneeling, or combination) was 47.3% (range, 3.8-86.7%). A 69% (95% confidence interval [95% CI]: 0.18-0.56) and 88% (95% CI: 0.04-0.33) lower odds of incurring donor-site morbidity was observed with HT and QT autografts, respectively (p < 0.0001, both), when compared to BTB autograft. QT autograft was associated with a non-statistically significant reduction in donor-site morbidity compared with HT autograft (OR: 0.37, 95% CI: 0.14-1.03, n.s.). Treatment rankings (ordered from best-to-worst autograft choice with respect to donor-site morbidity) were as follows: (1) QT (P-score = 0.99), (2) HT (P-score = 0.51) and (3) BTB (P-score = 0.00). No statistically significant associations were observed between autograft and complications (n.s.), reoperations (n.s.) or revision ACLR (n.s.).

CONCLUSION

ACLR using HT and QT autograft tissue was associated with a significant reduction in donor-site morbidity compared to BTB autograft. Autograft selection was not associated with complications, all-cause reoperations, or revision ACLR. Based on the current data, there is sufficient evidence to recommend that autograft selection should be personalized through considering differential rates of donor-site morbidity in the context of patient expectations and activity level without concern for a clinically important change in the rate of adverse events.

LEVEL OF EVIDENCE

Level I.

A guide to appropriately planning and conducting meta-analyses: part 2-effect size estimation, heterogeneity and analytic approaches

Meta-analyses by definition are a subtype of systematic review intended to quantitatively assess the strength of evidence present on an intervention or treatment. Such analyses may use individual-level data or aggregate data to produce a point estimate of an effect, also known as the combined effect, and measure precision of the calculated estimate. The current article will review several important considerations during the analytic phase of a meta-analysis, including selection of effect estimators, heterogeneity and various sub-types of meta-analytic approaches.

Survival analyses and their applications in orthopaedics

Survival analyses are a powerful statistical tool used to analyse data when the outcome of interest involves the time until an event. There is an array of models fit for this goal; however, there are subtle differences in assumptions, as well as a number of pitfalls, that can lead to biased results if researchers are unaware of the subtleties. As larger amounts of data become available, and more survival analyses are published every year, it is important that healthcare professionals understand how to evaluate these models and apply them into their practice. Therefore, the purpose of this study was to present an overview of survival analyses, including required assumptions and important pitfalls, as well as examples of their use within orthopaedic surgery.

Characteristics and outcomes of US Veterans at least 65 years of age at high risk of severe SARS-CoV-2 infection with or without receipt of oral antiviral agents

OBJECTIVES

Molnupiravir and nirmatrelvir/ritonavir each became available in the United States (US) through the Food and Drug Administration (FDA) emergency use authorization (EUA) in December 2021 after their respective initial prospective randomized controlled trials demonstrated efficacy for patients with mild-to-moderate SARS-CoV-2 active infection considered to be at high risk for progression of disease and hospitalization. Although sufficiently powered for this wide group, the mean age for patients in these studies was only 43 and 46 years of age, respectively. We sought to compare outcomes of US Veterans 65 years and older who received either of these oral antivirals to those who did not receive oral antivirals for mild-to-moderate SARS-CoV-2 active infection.

METHODS

The current project was a retrospective, observational, nationwide propensity-matched analysis comparing outcomes of US Veterans 65 years and older who received either of these oral antivirals to US Veterans 65 years and older who did not receive oral antivirals for mild-to-moderate SARS-CoV-2 active infection.

RESULTS

The composite primary outcome of admission or death within 30 days of diagnosis was reached less often in those receiving either molnupiravir or nirmatrelvir/ritonavir versus those that received no antiviral (65/1370 [4.75%] vs. 139/1370 [10.2%]; odds ratio 0.44, 95% confidence interval 0.32-0.60, p<0.0001). Baseline differences between Veterans selected for molnupiravir vs. nirmatrelvir/ritonavir therapy were noted, particularly in the number of concomitant medications with cautions or contraindications with nirmatrelvir/ritonavir.

CONCLUSIONS

Our findings support the use of molnupiravir or nirmatrelvir/ritonavir in patients 65 years of age and older. Patients with higher medication caution and contraindication burdens to nirmatrelvir/ritonavir are selected for molnupiravir therapy, which in the absence of a prospective head-to-head trial, may limit any efforts to compare the effectiveness of the two drugs.

Editorial Commentary: Machine Learning Is Just a Statistical Technique, Not a Mystical Methodology or Peer Review Panacea

Orthopaedic and sports medicine research surrounding artificial intelligence (AI) has dramatically risen over the last 4 years. Meaningful application and methodologic rigor in the scientific literature are critical to ensure appropriate use of AI. Common but critical errors for those engaging in AI-related research include failure to 1) ensure the question is important and previously unknown or unanswered; 2) establish that AI is necessary to answer the question; and 3) recognize model performance is more commonly a reflection of the data than the AI itself. We must take care to ensure we are not repackaging and internally validating registry data. Instead, we should be critically appraising our data-not the AI-based statistical technique. Without appropriate guardrails surrounding the use of artificial intelligence in Orthopaedic research, there is a risk of repackaging registry data and low-quality research in a recursive peer-reviewed loop.

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)' 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.

Propensity-matched analysis of the protective effect of ticagrelor versus clopidogrel on the risk of developing Staphylococcus aureus bacteremia

OBJECTIVE

Recent data indicate that ticagrelor, used in acute coronary syndromes (ACS), has antibacterial effects against Staphylococcus sp. and other effects that may help management of infection. The primary objective of this study was to evaluate the protective effect of ticagrelor in patients who have had an ACS event and the risk of developing Staphylococcus aureus bacteremia (SAB) compared to a propensity-matched cohort receiving clopidogrel.

METHODS

This study was a retrospective, nationwide analysis of all patients presenting to any percutaneous coronary intervention-performing Veterans Affairs Medical Center with an ACS episode and resultant prescription for clopidogrel or ticagrelor. The primary outcome was the comparative rate of SAB in patients receiving ticagrelor vs. clopidogrel.

RESULTS

Analysis involved 24 456 patients on ticagrelor and 277 277 patients on clopidogrel. There was a statistically significant difference in the number of patients developing SAB between the propensity-matched groups (32 [0.13%] of 24 456 for ticagrelor vs. 71 [0.29%] of 24 456 for clopidogrel; odds ratio (OR), 0.43; 95% confidence interval (CI), 0.28-0.65; P<0.0001). Multivariate logistic regression showed that receipt of clopidogrel, comorbid dermatologic condition, comorbid hematologic condition, and baseline anemia were independently associated with the development of SAB.

CONCLUSIONS

The study findings align with recent reports that ticagrelor may have a beneficial role in the prevention of SAB.

Staphylococcus aureus bacteraemia treatment outcomes in patients receiving ticagrelor vs a propensity-matched cohort receiving clopidogrel

OBJECTIVES

Ticagrelor may improve the outcomes in Staphylococcus aureus bacteraemia (SAB). However, treatment outcome data for these patients remain limited. The primary objective of this study was to characterize the outcomes of patients with SAB who received ticagrelor compared with a cohort who received clopidogrel.

METHODS

This was a retrospective, nationwide propensity-matched analysis of patients with SAB who were prescribed ticagrelor or clopidogrel concomitantly with antistaphylococcal therapy. The primary outcome was the comparative all-cause 30-day mortality rate between propensity-matched groups.

RESULTS

In total, 1509 patients were prescribed concomitantly with ticagrelor or clopidogrel during treatment of S. aureus bacteraemia; of these, 194 patients were excluded from this study due to an inadequate number of antiplatelet doses within the first week of therapy (n=171) or non-admission to hospital (n=23). Of the remaining 1315 patients, 74 patients received ticagrelor and 1241 patients received clopidogrel. There was no significant difference in all-cause 30-day mortality between the groups [6/74 (8.1%) in the ticagrelor group vs 10/74 (13.5%) in the clopidogrel group; P=0.29]. Multi-variate logistic regression demonstrated that elevated aspartate aminotransferase, systolic blood pressure <90 mmHg, elevated serum creatinine and neurological comorbidity were independently associated with all-cause 30-day mortality.

CONCLUSIONS

This study found no difference in all-cause 30-day mortality between the two groups, although overall mortality appeared to be lower compared with other reports. Randomized controlled trials of P2Y12 inhibitors as adjunctive agents to antibiotic therapy for the treatment of serious S. aureus infections are warranted.

Unsupervised machine learning methods and emerging applications in healthcare

Unsupervised machine learning methods are important analytical tools that can facilitate the analysis and interpretation of high-dimensional data. Unsupervised machine learning methods identify latent patterns and hidden structures in high-dimensional data and can help simplify complex datasets. This article provides an overview of key unsupervised machine learning techniques including K-means clustering, hierarchical clustering, principal component analysis, and factor analysis. With a deeper understanding of these analytical tools, unsupervised machine learning methods can be incorporated into health sciences research to identify novel risk factors, improve prevention strategies, and facilitate delivery of personalized therapies and targeted patient care.Level of evidence: I.

A practical guide to the development and deployment of deep learning models for the Orthopedic surgeon: part I

Deep learning has a profound impact on daily life. As Orthopedics makes use of this rapid escalation in technology, Orthopedic surgeons will need to take leadership roles on deep learning projects. Moreover, surgeons must possess an understanding of what is necessary to design and implement deep learning-based project pipelines. This review provides a practical guide for the Orthopedic surgeon to understand the steps needed to design, develop, and deploy a deep learning pipeline for clinical applications. A detailed description of the processes involved in defining the problem, building the team, acquiring and curating the data, labeling the data, establishing the ground truth, pre-processing and augmenting the data, and selecting the required hardware is provided. In addition, an overview of unique considerations involved in the training and evaluation of deep learning models is provided. This review strives to provide surgeons with the groundwork needed to identify gaps in the clinical landscape that deep learning models may be able to fill and equips them with the knowledge needed to lead an interdisciplinary team through the process of creating novel deep-learning-based solutions to fill those gaps.

Choosing the appropriate measure of central tendency: mean, median, or mode?

Mean, median, and mode are among the most basic and consistently used measures of central tendency in statistical analysis and are crucial for simplifying data sets to a single value. However, there is a lack of understanding of when to use each metric and how various factors can impact these values. The aim of this article is to clarify some of the confusion related to each measure and explain how to select the appropriate metric for a given data set. The authors present this work as an educational resource, ensuring that these common statistical concepts are better understood throughout the Orthopedic research community.

Multivariable regression: understanding one of medicine's most fundamental statistical tools

Multivariable regression is a fundamental tool that drives observational research in orthopaedic surgery. However, regression analyses are not always implemented correctly. This study presents a basic overview of regression analyses and reviews frequent points of confusion. Topics include linear, logistic, and time-to-event regressions, causal inference, confounders, overfitting, missing data, multicollinearity, interactions, and key differences between multivariable versus multivariate regression. The goal is to provide clarity regarding the use and interpretation of multivariable analyses for those attempting to increase their statistical literacy in orthopaedic research.

Development of SARS-CoV-2 infection in patients with rheumatic conditions on hydroxychloroquine monotherapy vs. patients without rheumatic conditions: A retrospective, propensity-matched cohort study

BACKGROUND

The primary purpose of the current study was to examine whether patients with rheumatologic conditions receiving only chronic hydroxychloroquine therapy for their disease are at less risk of developing SARS-CoV-2 infection than a comparative group of patients without rheumatologic conditions.

METHODS

A retrospective, observational, nationwide stratified propensity analysis was conducted comparing patients only on chronic treatment with hydroxychloroquine for their rheumatologic condition to a random sample of patients without rheumatologic conditions and not receiving hydroxychloroquine, utilizing a Veterans Health Administration nationwide clinical administrative database.

RESULTS

The 1-to-1 stratified propensity analysis was undertaken using a random sample of patients without rheumatoid conditions and not receiving hydroxychloroquine (n  33,081) and patients with rheumatoid conditions receiving hydroxychloroquine as the lone medication for their condition (n  6047). A total of 5,474 patients in each group were successfully matched. The incidence of documented SARS-CoV-2 infections during the study period did not differ between patients receiving hydroxychloroquine and patients not receiving hydroxychloroquine (41/5,474 [0.749%] vs. 36/5,474 [0.658%], respectively, p = 0.57; Odds ratio [OR] 1.14, 95% confidence interval [CI] 0.73-1.79). There were no statistically-significant differences in secondary outcomes between the two groups in patients who developed active SARS-CoV-2 infection. Multivariate logistic regression to determine independent variables associated with the development of active SARS-CoV-2 infection failed to include receipt of hydroxychloroquine (OR 0.99, 95% CI 0.62-1.56).

CONCLUSIONS

Hydroxychloroquine failed to demonstrate a preventative effect against SARS-CoV-2 infection in a large group of patients with rheumatologic conditions compared to patients without rheumatologic conditions.

Quadriceps Weakness is Associated with Neuroplastic Changes Within Specific Corticospinal Pathways and Brain Areas After Anterior Cruciate Ligament Reconstruction: Theoretical Utility of Motor Imagery-Based Brain-Computer Interface Technology for Rehabilitation

Persistent quadriceps weakness is a problematic sequela of anterior cruciate ligament reconstruction (ACLR). The purposes of this review are to summarize neuroplastic changes after ACL reconstruction; provide an overview of a promising interventions, motor imagery (MI), and its utility in muscle activation; and propose a framework using a brain-computer interface (BCI) to augment quadriceps activation. A literature review of neuroplastic changes, MI training, and BCI-MI technology in postoperative neuromuscular rehabilitation was conducted in PubMed, Embase, and Scopus. Combinations of the following search terms were used to identify articles: "quadriceps muscle," "neurofeedback," "biofeedback," "muscle activation," "motor learning," "anterior cruciate ligament," and "cortical plasticity." We found that ACLR disrupts sensory input from the quadriceps, which results in reduced sensitivity to electrochemical neuronal signals, an increase in central inhibition of neurons regulating quadriceps control and dampening of reflexive motor activity. MI training consists of visualizing an action, without physically engaging in muscle activity. Imagined motor output during MI training increases the sensitivity and conductivity of corticospinal tracts emerging from the primary motor cortex, which helps "exercise" the connections between the brain and target muscle tissues. Motor rehabilitation studies using BCI-MI technology have demonstrated increased excitability of the motor cortex, corticospinal tract, spinal motor neurons, and disinhibition of inhibitory interneurons. This technology has been validated and successfully applied in the recovery of atrophied neuromuscular pathways in stroke patients but has yet to be investigated in peripheral neuromuscular insults, such as ACL injury and reconstruction. Well-designed clinical studies may assess the impact of BCI on clinical outcomes and recovery time. Quadriceps weakness is associated with neuroplastic changes within specific corticospinal pathways and brain areas. BCI-MI shows strong potential for facilitating recovery of atrophied neuromuscular pathways after ACLR and may offer an innovative, multidisciplinary approach to orthopaedic care.

Level of Evidence

V, expert opinion.

Natural language processing: using artificial intelligence to understand human language in orthopedics

Natural language processing (NLP) describes the broad field of artificial intelligence by which computers are trained to understand and generate human language. Within healthcare research, NLP is commonly used for variable extraction and classification/cohort identification tasks. While these tools are becoming increasingly popular and available as both open-source and commercial products, there is a paucity of the literature within the orthopedic space describing the key tasks within these powerful pipelines. Curation and navigation of the electronic medical record are becoming increasingly onerous, and it is important for physicians and other healthcare professionals to understand potential methods of harnessing this large data resource. The purpose of this study is to provide an overview of the tasks required to develop an NLP pipeline for orthopedic research and present recent examples of successful implementations.

Supervised machine learning and associated algorithms: applications in orthopedic surgery

Supervised learning is the most common form of machine learning utilized in medical research. It is used to predict outcomes of interest or classify positive and/or negative cases with a known ground truth. Supervised learning describes a spectrum of techniques, ranging from traditional regression modeling to more complex tree boosting, which are becoming increasingly prevalent as the focus on "big data" develops. While these tools are becoming increasingly popular and powerful, there is a paucity of literature available that describe the strengths and limitations of these different modeling techniques. Typically, there is no formal training for health care professionals in the use of machine learning models. As machine learning applications throughout medicine increase, it is important that physicians and other health care professionals better understand the processes underlying application of these techniques. The purpose of this study is to provide an overview of commonly used supervised learning techniques with recent case examples within the orthopedic literature. An additional goal is to address disparities in the understanding of these methods to improve communication within and between research teams.

High variability and lack of standardization in the evaluation of return to sport after ACL reconstruction: a systematic review

PURPOSE

Return to sport (RTS) after ACL reconstruction (ACLR) has been recognized as an important outcome, which is associated with success of the surgery. This study aimed to assess the methods used to determine return to sport after ACLR in the published literature, report on variability of methods and evaluate their strength in establishing accurate RTS data.

METHODS

Electronic databases (PubMed, Cochrane Library and Embase) were searched via a defined search strategy with no limits, to identify relevant studies from January 2008 to December 2020 for inclusion in the review. Defined eligibility criteria included studies specifically measuring and reporting on return to sport after ACLR with a clear methodology. Each included study was assessed for the definition of successful RTS, successful return to pre-injury level of sport and for methods used to determine RTS.

RESULTS

One hundred and seventy-one studies were included. Of the included studies, six studies (4%) were level of evidence 1 and seventy-two studies (42%) were level of evidence 4. Forty-one studies (24%) reported on return to a specific sport and 130 studies (76%) reported on return to multiple sports or general sport. Sixteen studies (9%) reported on RTS in the pediatric population, 36 (21%) in the adult population and 119 (70%) reported on a mixed-aged population. The most commonly used definition of successful RTS was return to the same sport (44 of 125 studies, 35%). The most common method used to determine RTS was a non-validated study-specific questionnaire (73 studies, 43%), which was administered in various ways to the patients. Time of RTS assessment was variable and ranged between 6 months and 27 years post-surgery.

CONCLUSION

This review demonstrates high variability in defining, evaluating and reporting RTS following ACLR. The findings of this study reveal low reliability and unproven validity of methods used to evaluate RTS and highlight the challenges in interpreting and using RTS data reported in literature.

LEVEL OF EVIDENCE

IV.

Sports Medicine and Artificial Intelligence: A Primer

Artificial intelligence (AI) represents the fourth industrial revolution and the next frontier in medicine poised to transform the field of orthopaedics and sports medicine, though widespread understanding of the fundamental principles and adoption of applications remain nascent. Recent research efforts into implementation of AI in the field of orthopaedic surgery and sports medicine have demonstrated great promise in predicting athlete injury risk, interpreting advanced imaging, evaluating patient-reported outcomes, reporting value-based metrics, and augmenting the patient experience. Not unlike the recent emphasis thrust upon physicians to understand the business of medicine, the future practice of sports medicine specialists will require a fundamental working knowledge of the strengths, limitations, and applications of AI-based tools. With appreciation, caution, and experience applying AI to sports medicine, the potential to automate tasks and improve data-driven insights may be realized to fundamentally improve patient care. In this Current Concepts review, we discuss the definitions, strengths, limitations, and applications of AI from the current literature as it relates to orthopaedic sports medicine.

Risk Factors for Failure After Osteochondral Allograft Transplantation of the Knee: A Systematic Review and Exploratory Meta-analysis

BACKGROUND

Graft failure after osteochondral allograft transplantation (OCA) of the knee is a devastating outcome, often necessitating subsequent interventions. A comprehensive understanding of the risk factors for failure after OCA of the knee may provide enhanced prognostic data for the knee surgeon and facilitate more informed shared decision-making discussions before surgery.

PURPOSE

To perform a systematic review and meta-analysis of risk factors associated with graft failure after OCA of the knee.

STUDY DESIGN

Systematic review and meta-analysis; Level of evidence, 4.

METHODS

The PubMed, Ovid/MEDLINE, and Cochrane databases were queried in April 2021. Data pertaining to study characteristics and risk factors associated with failure after OCA were recorded. DerSimonian-Laird binary random-effects models were constructed to quantitatively evaluate the association between risk factors and graft failure by generating effect estimates in the form of odds ratios (ORs) with 95% CIs, while mean differences (MDs) were calculated for continuous data. Qualitative analysis was performed to describe risk factors that were variably reported.

RESULTS

A total of 16 studies consisting of 1401 patients were included. The overall pooled prevalence of failure was 18.9% (range, 10%-46%). There were 44 risk factors identified, of which 9 were explored quantitatively. There was strong evidence to support that the presence of bipolar chondral defects (OR, 4.20 [95% CI, 1.17-15.08]; P = .028) and male sex (OR, 2.04 [95% CI, 1.17-3.55]; P = .012) were significant risk factors for failure after OCA. Older age (MD, 5.06 years [95% CI, 1.44-8.70]; P = .006) and greater body mass index (MD, 1.75 kg/m² [95% CI, 0.48-3.03]; P = .007) at the time of surgery were also significant risk factors for failure after OCA. There was no statistically significant evidence to incontrovertibly support that concomitant procedures, chondral defect size, and defect location were associated with an increased risk of failure after OCA.

CONCLUSION

Bipolar chondral defects, male sex, older age, and greater body mass index were significantly associated with an increased failure rate after OCA of the knee. No statistically significant evidence presently exists to support that chondral defect size and location or concomitant procedures are associated with an increased graft failure rate after OCA of the knee. Additional studies are needed to evaluate these associations.

Design and Implementation of a novel Weekend Elective Paediatric Surgery Program to Reduce COVID-19 Related Backlog: Operating Room Ramp-Up After COVID-19 Lockdown Ends - Extra Lists (ORRACLE-Xtra)

Background

The COVID-19 pandemic caused by the SARS-COV-2 virus has resulted in unprecedented challenges for the health care system. A decrease of surgical services led to substantial backlogs for time-sensitive scheduled pediatric patients. We designed and implemented a novel pilot weekend surgical quality improvement project called Operating Room Ramp-Up After COVID Lockdown Ends—Extra Lists (ORRACLE-Xtra).

Objective

Our overall goals are to increase patient access to surgery (and reduce the wait list), improve operating room efficiencies, and optimize parent and staff experience.

Methods

Using the DMAIC (define, measure, analyze, improve, control) framework, we implemented ORRACLE-Xtra in a tertiary care academic pediatric hospital during a quiescent period of the COVID-19 pandemic. We defined process and outcome measures based on provincial targets of out-of-window cases. Parental and staff satisfaction was tracked by surveys.

Results

ORRACLE-Xtra led to 247 patients receiving surgery during the pilot period, resulting in a 5% decrease in the total number of patients on our wait list with Paediatric Canadian Access Targets for Surgery IV (147/247, 59.5%), with 38.1% (94/247) out-of-window of provincial targets. Most of the process and outcome measures were met or exceeded. Overall parental satisfaction was at 95.8% (110/121), with 79% (64/81) of staff reporting satisfaction with working weekends.

Conclusions

Through the ORRACLE-Xtra pilot program, we have shown that hospitals impacted by COVID-19 can reduce the surgical backlog using innovative models of service delivery in a Canadian context. Sustained funding is critical to achieving more meaningful reductions in wait times for scheduled surgeries over the longer term and needs to be balanced with staff well-being.

Differences in the Demographics and Preferred Management of Knee Cartilage Injuries in Soccer Players Across FIFA Centers of Excellence

OBJECTIVE

We sought to report on the demographics and epidemiology of knee cartilage injuries and preferred management in soccer players, across FIFA Medical Centers of Excellence (FMCE).

DESIGN

A descriptive questionnaire focusing on characteristics of knee cartilage injuries and their management in soccer players during the 10-year period prior to the distribution of the questionnaire was sent to all FMCE around the world in September 2019 via an online platform. Voluntary responses from centers were processed and analyzed. Descriptive characteristics were reported using median and interquartile ranges (IQR) for continuous variables and frequencies and percentages (%) for discrete variables.

RESULTS

A total of 15 centers from 5 continents responded to the questionnaire and reported on a total of 4526 soccer players. Among centers, the median age was 27 years (IQR: 23-38), the median rate of male players was 75% (IQR: 68-90), and the median rate of professional players was 10% (IQR: 5-23). The most common reported etiology for cartilage injury was traumatic (median 40%, IQR: 13-73). The most common nonoperative treatment utilized was physical therapy (median 90%, IQR: 51%-100%) and the most common operative treatment utilized was bone marrow stimulation/micro-fracture (median 40%, IQR: 19-54%). The utilization of other cartilage restoration procedures varied across centers.

CONCLUSIONS

Our findings highlight different tendencies in the management of these injuries across FMCE and emphasize the need for collaborative efforts focusing on establishing consensus guidelines for the optimal management of these challenging injuries in soccer players.

Do Self-Reported Drug Allergies Influence Clinically Significant Outcome Improvement Following Osteochondral Allograft Transplantation? A Nested Cohort Study

OBJECTIVE

To compare clinical outcomes for patients who underwent osteochondral allograft transplantation (OCA) based on the presence or absence of one or more self-reported drug allergies.

DESIGN

Prospective data were collected from 245 consecutive patients after OCA of the knee from one large academic institution. Patient-reported allergies were obtained via chart review. Patient-reported outcome measures, including activities of daily living of the Knee Outcome Survey (KOS-ADL), Marx Activity Scale, International Knee Documentation Committee (IKDC), and visual analogue scale (VAS) pain were all collected. The minimal clinically important difference (MCID) for each outcome was quantified using a distribution-based method. Independent t tests were used to compare patient-reported outcome measures between those with and without self-reported allergies, while chi-square analysis of association was used to compare rates of MCID achievement.

RESULTS

Of 245 patients included, 83 (33.9%) reported having at least one drug allergy at the time of OCA. There were no statistically significant differences with regard to patient demographics, including age, body mass index, gender, or sports participation between those with and without a reported allergy. Similarly, there were no significant differences found between baseline preoperative patient-reported outcomes. Overall, both cohorts demonstrated a significant improvement from baseline scores at 2 years postoperatively. There were no differences found between any patient-reported outcome at 2 years postoperatively. The presence of at least one self-reported drug allergy was not a significant risk factor for failing to achieve the MCID in any specific outcome measure.

CONCLUSIONS

The presence of one or more drug allergy was not associated with worse patient-reported outcomes or lower rates of clinically significant outcome improvement after OCA.

SF-36 Physical Component Score Is Predictive of Achieving a Clinically Meaningful Improvement after Osteochondral Allograft Transplantation of the Femur

BACKGROUND

Osteochondral allograft (OCA) transplantation is an increasingly common treatment for patients with symptomatic focal chondral lesions of the knee. There has been increasing interest in determining predictive factors to maximize patient benefit after this operation. The aim of the present study is to evaluate the predictive association of the physical component (PCS) and mental component (MCS) scores of the Short Form 36 (SF-36) questionnaire for achievement of the minimal clinically important difference (MCID) after OCA transplantation.

METHODS

This retrospective study of a longitudinally maintained institutional registry included 91 patients who had undergone OCA transplantation for symptomatic focal osteochondral lesions of the femoral condyle. Included patients were those with complete preoperative questionnaires for the SF-36 and IKDC and completed postoperative IKDC at 2-year follow-up. Multivariate analysis was performed evaluating predictive association of the preoperative MCS and PCS with achievement of the MCID for the IKDC questionnaire.

RESULTS

Logistic multivariate modeling demonstrated a statistically significant association between lower preoperative PCS and achievement of the MCID (P = 0.022). A defect diameter >2 cm was also associated with achievement of MCID (P = 0.049). Preoperative MCS did not demonstrate a significant association (P = 0.09) with achievement of the MCID.

CONCLUSIONS

For this cohort of 91 patients, the preoperative SF-36 PCS and lesion size were predictive of achievement of the MCID at 2-year follow-up after femoral OCA transplantation. These findings support an important role of baseline physical health scores for predicting which patients will obtain a meaningful clinical benefit from this surgery.

Synthetic Biphasic Scaffolds versus Microfracture for Articular Cartilage Defects of the Knee: A Retrospective Comparative Study

OBJECTIVE

The purpose of this study was to compare the results of a biphasic synthetic scaffold (TruFit, Smith & Nephew) to microfracture for the treatment of knee cartilage defects and identify patient- and lesion-specific factors that influence outcomes.

DESIGN

Prospectively collected data from 132 patients (mean age, 41.8 years; 69% male) with isolated chondral or osteochondral femoral defects treated with biphasic synthetic scaffolds (n = 66) or microfracture (n = 66) were reviewed. Clinical outcomes were evaluated longitudinally over 5 years with the Short Form-36 (SF-36), Activities of Daily Living of the Knee Outcome Survey (KOS-ADL), International Knee Documentation Committee (IKDC), and Marx Activity Scale. Cartilage-sensitive magnetic resonance imaging (MRI) was performed to evaluate osseous integration and cartilage fill in a subgroup of patients. Multivariate regression analysis was used to identify predictors of clinical outcomes within the scaffold group.

RESULTS

Both groups demonstrated clinically significant improvements in knee clinical scores over 5 years (P < 0.01). There were no significant differences in KOS-ADL and IKDC scores between groups up to 5 years postoperatively. Marx activity level scores in the microfracture group declined over time, while significant improvements in activity level scores were observed in the scaffold group over 5 years (P < 0.01). Good-quality tissue fill and cartilage isointensity were more often observed in the scaffold group compared with the microfracture group, particularly with longer time intervals. Increasing age, high body mass index, prior microfracture, and traumatic etiology were predictors for inferior outcomes in the scaffold group.

CONCLUSIONS

Activity level and MRI appearance following treatment of cartilage lesions with the biphasic synthetic scaffold were superior to microfracture over time in this nonrandomized, retrospective comparison.

Application of Machine Learning Algorithms to Predict Clinically Meaningful Improvement After Arthroscopic Anterior Cruciate Ligament Reconstruction

Background:

Understanding specific risk profiles for each patient and their propensity to experience clinically meaningful improvement after anterior cruciate ligament reconstruction (ACLR) is important for preoperative patient counseling and management of expectations.

Purpose:

To develop machine learning algorithms to predict achievement of the minimal clinically important difference (MCID) on the International Knee Documentation Committee (IKDC) score at a minimum 2-year follow-up after ACLR.

Study Design:

Case-control study; Level of evidence, 3.

Methods:

An ACLR registry of patients from 27 fellowship-trained sports medicine surgeons at a large academic institution was retrospectively analyzed. Thirty-six variables were tested for predictive value. The study population was randomly partitioned into training and independent testing sets using a 70:30 split. Six machine learning algorithms (stochastic gradient boosting, random forest, neural network, support vector machine, adaptive gradient boosting, and elastic-net penalized logistic regression [ENPLR]) were trained using 10-fold cross-validation 3 times and internally validated on the independent set of patients. Algorithm performance was assessed using discrimination, calibration, Brier score, and decision-curve analysis.

Results:

A total of 442 patients, of whom 39 (8.8%) did not achieve the MCID, were included. The 5 most predictive features of achieving the MCID were body mass index ≤27.4, grade 0 medial collateral ligament examination (compared with other grades), intratunnel femoral tunnel fixation (compared with suspensory), no history of previous contralateral knee surgery, and achieving full knee extension preoperatively. The ENPLR algorithm had the best relative performance (C-statistic, 0.82; calibration intercept, 0.10; calibration slope, 1.15; Brier score, 0.068), demonstrating excellent predictive ability in the study’s data set.

Conclusion:

Machine learning, specifically the ENPLR algorithm, demonstrated good performance for predicting a patient’s propensity to achieve the MCID for the IKDC score after ACLR based on preoperative and intraoperative factors. The femoral tunnel fixation method was the only significant intraoperative variable. Range of motion and medial collateral ligament integrity were found to be important physical examination parameters. Increased body mass index and prior contralateral surgery were also significantly predictive of outcome.

Patient-Reported Outcomes and Factors Associated with Achieving the Minimal Clinically Important Difference After ACL Reconstruction: Results at a Mean 7.7-Year Follow-up

Background

Analyzing outcomes and the minimal clinically important difference (MCID) after anterior cruciate ligament reconstruction (ACLR) is of increased interest in the orthopaedic literature. The purposes of this study were to report outcomes after ACLR at medium to long-term follow-up, identify the threshold preoperative outcome values that would be predictive of achieving the MCID postoperatively, and analyze outcome maintenance at medium to long-term follow-up after ACLR.

Methods

Active athletes who underwent ACLR were identified in an institutional ACL registry. Patient-reported outcome measures (PROMs) were administered preoperatively and at the 2-year and >5-year postoperative follow-up; measures included the International Knee Documentation Committee (IKDC) form, the 12-item Short Form Health Survey (SF-12) Physical Component Summary (PCS) and Mental Component Summary (MCS), and Lysholm scale. We calculated the MCID from baseline to each of the 2 follow-up periods (2-year and mean 7.7-year). Logistic regression was performed to investigate factors associated with achievement of the MCID.

Results

A total of 142 patients (mean follow-up, 7.7 years [range, 6.6 to 9.1 years]) underwent ACLR. The mean age and body mass index at the time of surgery were 27.2 ± 13.0 years and 23.2 ± 3.0 kg/m2, respectively. Final postoperative outcome scores improved significantly from baseline for the IKDC (50.9 ± 14.7 to 87.9 ± 11.2), SF-12 PCS (41.6 ± 8.9 to 55.6 ± 3.2), and Lysholm scale (62.2 ± 17.6 to 90.5 ± 10.3) (p < 0.0001), while the SF-12 MCS did not improve significantly (54.2 ± 8.0 to 54.4 ± 6.0) (p = 0.763). Between 2- and >5-year follow-up, the SF-12 PCS showed significant improvement (54.6 ± 4.5 to 55.6 ± 3.2; p = 0.036), while no change was noted in the IKDC (87.6 ± 11.1 to 87.9 ± 11.2), SF-12 MCS (55.5 ± 5.3 to 54.4 ± 6.0), and Lysholm scale (89.8 ± 10.6 to 90.5 ± 10.3) (p ≥ 0.09). At the time of final follow-up, the MCID was achieved by 94.7% of patients for the IKDC, 80.8% for the Lysholm, 79.0% for the SF-12 PCS, and 28.2% for the SF-12 MCS. At 2-year follow-up, 95.3% of patients were either "very" or "somewhat" satisfied with their surgery, compared with 88.6% at the time of final follow-up.

Conclusions

We found a high level of maintained function following ACLR. The IKDC, SF-12 PCS, and Lysholm scores improved significantly after ACLR at the time of final follow-up and were not significantly different between follow-up periods. Approximately 95% and 89% of patients reported being satisfied with the outcome of surgery at the 2-year and final follow-up, respectively.

Level of Evidence

Therapeutic Level IV. See Instructions for Authors for a complete description of levels of evidence.

Anteriorizing Tibial Tubercle Osteotomy for Patellofemoral Cartilage Lesions

Patellofemoral chondral lesions are common and can lead to significant pain. A tibial tubercle osteotomy (TTO) functions to mechanically unload the patellofemoral joint and improve the clinical success of cartilage restoration procedures. The type of TTO performed is based on several factors. There is a subset of patients with patellofemoral cartilage disease who would benefit from a pure anteriorization of the tibial tubercle. We describe our technique for a pure anteriorization TTO, which functions to safely unload the patellofemoral joint in the appropriately indicated patient.

Effect of Preoperative Imaging and Patient Factors on Clinically Meaningful Outcomes and Quality of Life After Osteochondral Allograft Transplantation: A Machine Learning Analysis of Cartilage Defects of the Knee

BACKGROUND

Fresh osteochondral allograft transplantation (OCA) is an effective method of treating symptomatic cartilage defects of the knee. This restoration technique involves the single-stage implantation of viable, mature hyaline cartilage into a chondral or osteochondral lesion. The extent to which preoperative imaging and patient factors predict achieving clinically meaningful outcomes among patients undergoing OCA for cartilage lesions of the knee remains unknown.

PURPOSE

To determine the predictive relationship of preoperative imaging, preoperative patient-reported outcome measures (PROMs), and patient demographics with achievement of the minimal clinically important difference (MCID) and substantial clinical benefit (SCB) for functional and quality-of-life PROMs at 2 years after OCA for symptomatic cartilage defects of the knee.

STUDY DESIGN

Case-control study; Level of evidence, 3.

METHODS

Data were analyzed for patients who underwent OCA before May 1, 2018, by 2 high-volume fellowship-trained cartilage surgeons. The International Knee Documentation Committee (IKDC) subjective form, Knee Outcome Survey-Activities of Daily Living (KOS-ADL), and mental and physical component summaries of the SF-36 were administered preoperatively and at 2 years postoperatively. A total of 42 predictive models were created using 7 unique architectures to detect achievement of the MCID for each of the 4 outcome measures and the SCB for the IKDC and KOS-ADL. Data inputted into the models included sex, age, body mass index, baseline PROMs, lesion size, concomitant ligamentous or meniscal tear, and presence of "bone bruise" or osseous edema. Shapley additive explanations plot analysis identified predictors of reaching the MCID and SCB.

RESULTS

Of the 185 patients who underwent OCA for the knee and met eligibility criteria from an institutional cartilage registry, 153 (83%) had 2-year follow-up. Preoperative magnetic resonance imaging (MRI), baseline PROMs, and patient demographics best predicted reaching the 2-year MCID and SCB of the IKDC and KOS-ADL PROMs, with areas under the receiver operating characteristic curve of the top-performing models ranging from good (0.88) to excellent (0.91). MRI faired poorly (areas under the curve, 0.60-0.68) in predicting the MCID for the mental and physical component summaries. Higher body mass index, knee malalignment, absence of preoperative osseous edema, concomitant anterior cruciate ligament or meniscal injury, larger defect size, and the implantation of >1 OCA graft were consistent findings contributing to failure to achieve the MCID or SCB at 2 years postoperatively.

CONCLUSION

Our machine learning models demonstrated that preoperative MRI, baseline PROMs, and patient demographics reliably predict the ability to reach clinically meaningful thresholds for functional knee outcomes 2 years after OCA for cartilage defects. Although clinical improvement in knee function can be reliably predicted, improvements in quality of life after OCA depend on a comprehensive preoperative assessment of the patient's perception of his or her mental and physical health. Absence of osseous edema, concomitant anterior cruciate ligament or meniscal injury, larger lesion size on MRI, knee malalignment, and elevated body mass index are predictive of failure to achieve 2-year functional benefits after OCA of the knee.

Preoperative Grades of Osteoarthritis and Meniscus Volume Correlate with Clinical Outcomes of Osteochondral Graft Treatment for Cartilage Defects in the Knee

OBJECTIVE

To identify preoperative imaging-based indicators of knee degeneration that correlate with graft failure risk and postoperative clinical outcome scores after osteochondral graft treatment for chondral defects of the knee.

DESIGN

Prospectively collected data from 113 patients (mean age, 34 years; 65% male) treated with mosaicplasty or osteochondral allograft transplantation (OCA) was reviewed. Four different aspects of knee degeneration were examined based on preoperative radiographs or magnetic resonance imaging: (1) Osteoarthritis using the Kellgren-Lawrence (KL) grading system, (2) meniscus volume, (3) meniscus quality, and (4) synovitis. Primary outcomes included graft failure, defined by removal/revision of the graft or conversion to arthroplasty, and patient responses to clinical outcome scores.

RESULTS

Forty-one knees (36%) underwent mosaicplasty, and 72 knees (64%) underwent OCA. Mean duration of follow-up was 4.5 years (range, 2-14 years). A preoperative KL grade of ≥3 was correlated with increased failure rates (P = 0.01), lower postoperative International Knee Documentation Committee form (IKDC), Activities of Daily Living of the Knee Outcome Survey (KOS-ADL), and Overall Condition scores (P < 0.01), and decreased improvement in Overall Condition scores (P = 0.01). Within an individual tibiofemoral compartment, a preoperative meniscus volume grade of ≥3 (indicating <50% meniscus volume remaining) was correlated with increased condylar graft failure rates (P < 0.01). Preoperative meniscus quality and synovitis grades were not associated with graft failure rates or clinically meaningful differences in postoperative outcome scores.

CONCLUSIONS

Greater preoperative osteoarthritis and meniscus volume loss were correlated with increased graft failure rates after osteochondral graft treatment for chondral defects of the knee.

Return to Sport After Bone-Patellar Tendon-Bone Autograft ACL Reconstruction in High School-Aged Athletes

Background:

Anterior cruciate ligament (ACL) injuries are occurring with increasing frequency in the adolescent population. Outcomes after ACL reconstruction (ACLR) are inconsistently reported in homogeneous patient populations.

Purpose/Hypothesis:

To evaluate outcomes after bone–patellar tendon–bone (BTB) autograft ACLR in competitive high school–aged athletes by examining return to sport (RTS), patient satisfaction, and reinjury rates. Our hypothesis was that RTS rates and satisfaction will be high and reinjury rates will be low.

Study Design:

Case series; Level of evidence, 4.

Methods:

An institutional ACL registry was utilized to identify competitive high school–aged athletes (14-18 years old) who underwent primary ACLR using BTB autograft with a minimum 2-year follow-up. A postoperative questionnaire was administered to determine rates and types of RTS, quality of sports performance, reinjury, and satisfaction. Uni- and multivariable analyses were used to identify demographic, sport-specific, and clinical factors related to RTS.

Results:

A total of 53 patients were included (mean ± SD age at the time of surgery, 16.6 ± 1.34 years). Mean follow-up was 3.78 ± 0.70 years (range, 2.60-4.94 years). The overall ipsilateral ACL retear rate was 7.5% (n = 4). There were 10 subsequent ACL tears to the contralateral knee (19%). Forty-four (83%) patients successfully returned to at least their prior level of sport at a mean 10.5 ± 8.7 months (range, 3-48 months). Overall satisfaction was high, with 91% of patients very satisfied with the outcome. Higher confidence levels regarding performance of the reconstructed knee were associated with increased probability of RTS on multivariate analysis.

Conclusion:

BTB autograft ACLR results in high rates of RTS and satisfaction and low rates of subsequent ipsilateral ACL injuries in competitive high school–aged athletes. Patients with higher confidence in performance of the reconstructed knee are more likely to return to at least their prior level of sport.

Clinical and Research Medical Applications of Artificial Intelligence

Artificial intelligence (AI), including machine learning (ML), has transformed numerous industries through newfound efficiencies and supportive decision-making. With the exponential growth of computing power and large datasets, AI has transitioned from theory to reality in teaching machines to automate tasks without human supervision. AI-based computational algorithms analyze "training sets" using pattern recognition and learning from inputted data to classify and predict outputs that otherwise could not be effectively analyzed with human processing or standard statistical methods. Though widespread understanding of the fundamental principles and adoption of applications have yet to be achieved, recent applications and research efforts implementing AI have demonstrated great promise in predicting future injury risk, interpreting advanced imaging, evaluating patient-reported outcomes, reporting value-based metrics, and augmenting telehealth. With appreciation, caution, and experience applying AI, the potential to automate tasks and improve data-driven insights may be realized to fundamentally improve patient care. The purpose of this review is to discuss the pearls, pitfalls, and applications associated with AI.

Arthroscopic-Assisted Coracoclavicular Ligament Reconstruction: Clinical Outcomes and Return to Activity at Mean 6-Year Follow-Up

PURPOSE

To report clinical and functional outcomes including return to preinjury activity level following arthroscopic-assisted coracoclavicular (CC) ligament reconstruction (AA-CCR) and to determine associations between return to preinjury activity level, radiographic outcomes, and patient-reported outcomes following AA-CCR.

METHODS

A institutional registry review of all AA-CCR using free tendon grafts from 2007 to 2016 was performed. Clinical assessment included Single Assessment Numeric Evaluation (SANE) score and return to preinjury activity level at final follow-up. Treatment failure was defined as (1) revision acromioclavicular stabilization surgery, (2) unable to return to preinjury activity level, or (3) radiographic loss of reduction (RLOR, >25% CC distance compared with contralateral side). SANE scores, return to activity, and RLOR were compared between patients within each category of treatment failure, by grade of injury, and whether concomitant pathology was treated.

RESULTS

There were 88 patients (89.8% male) with mean age of 39.6 years and minimum 2-year clinical follow-up (mean 6.1 years). Most injuries were Rockwood grade V (63.6%). Mean postoperative SANE score was 86.3 ± 17.5. Treatment failure occurred in 17.1%: 8.0% were unable to return to activity, 5.7% had RLOR, and 3.4% underwent revision surgery due to traumatic reinjury. SANE score was lower among patients who were unable to return to activity compared with those with RLOR and compared with nonfailures (P = .0002). There were no differences in revision surgery rates, return to activity, or SANE scores according to Rockwood grade or if concomitant pathology was treated.

CONCLUSIONS

AA-CCR with free tendon grafts resulted in good clinical outcomes and a high rate of return to preinjury activity level. RLOR did not correlate with return to preinjury activity level. Concomitant pathology that required treatment did not adversely affect outcomes. Return to preinjury activity level may be a more clinically relevant outcome measure than radiographic maintenance of acromioclavicular joint reduction.

LEVEL OF EVIDENCE

IV (Case Series).

Metrics of OsteoChondral Allografts (MOCA) Group Consensus Statements on the Use of Viable Osteochondral Allograft

Background:

Osteochondral allograft (OCA) transplantation has evolved into a first-line treatment for large chondral and osteochondral defects, aided by advancements in storage protocols and a growing body of clinical evidence supporting successful clinical outcomes and long-term survivorship. Despite the body of literature supporting OCAs, there still remains controversy and debate in the surgical application of OCA, especially where high-level evidence is lacking.

Purpose:

To develop consensus among an expert group with extensive clinical and scientific experience in OCA, addressing controversies in the treatment of chondral and osteochondral defects with OCA transplantation.

Study Design:

Consensus statement.

Methods:

A focus group of clinical experts on OCA cartilage restoration participated in a 3-round modified Delphi process to generate a list of statements and establish consensus. Questions and statements were initially developed on specific topics that lack scientific evidence and lead to debate and controversy in the clinical community. In-person discussion occurred where statements were not agreed on after 2 rounds of voting. After final voting, the percentage of agreement and level of consensus were characterized. A systematic literature review was performed, and the level of evidence and grade were established for each statement.

Results:

Seventeen statements spanning surgical technique, graft matching, indications, and rehabilitation reached consensus after the final round of voting. Of the 17 statements that reached consensus, 11 received unanimous (100%) agreement, and 6 received strong (80%-99%) agreement.

Conclusion:

The outcomes of this study led to the establishment of consensus statements that provide guidance on surgical and perioperative management of OCAs. The findings also provided insights on topics requiring more research or high-quality studies to further establish consensus and provide stronger evidence.

Association Between Preoperative Mental Health and Clinically Meaningful Outcomes After Osteochondral Allograft for Cartilage Defects of the Knee: A Machine Learning Analysis

BACKGROUND

Fresh osteochondral allograft transplantation (OCA) is an effective method of treating symptomatic cartilage defects of the knee. This cartilage restoration technique involves the single-stage implantation of viable, mature hyaline cartilage into the chondral or osteochondral lesion. Predictive models for reaching the clinically meaningful outcome among patients undergoing OCA for cartilage lesions of the knee remain under investigation.

PURPOSE

To apply machine learning to determine which preoperative variables are predictive for achieving the minimal clinically important difference (MCID) and substantial clinical benefit (SCB) at 1 and 2 years after OCA for cartilage lesions of the knee.

STUDY DESIGN

Case-control study; Level of evidence, 3.

METHODS

Data were analyzed for patients who underwent OCA of the knee by 2 high-volume fellowship-trained cartilage surgeons before May 1, 2018. The International Knee Documentation Committee questionnaire (IKDC), Knee Outcome Survey-Activities of Daily Living (KOS-ADL), and Mental Component (MCS) and Physical Component (PCS) Summaries of the 36-Item Short Form Health Survey (SF-36) were administered preoperatively and at 1 and 2 years postoperatively. A total of 84 predictive models were created using 7 unique architectures to detect achievement of the MCID for each of the 4 outcome measures and the SCB for the IKDC and KOS-ADL at both time points. Data inputted into the models included previous and concomitant surgical history, laterality, sex, age, body mass index (BMI), intraoperative findings, and patient-reported outcome measures (PROMs). Shapley Additive Explanations (SHAP) analysis identified predictors of reaching the MCID and SCB.

RESULTS

Of the 185 patients who underwent OCA for the knee and met eligibility criteria from an institutional cartilage registry, 135 (73%) patients were available for the 1-year follow-up and 153 (83%) patients for the 2-year follow-up. In predicting outcomes after OCA in terms of the IKDC, KOS-ADL, MCS, and PCS at 1 and 2 years, areas under the receiver operating characteristic curve (AUCs) of the top-performing models ranged from fair (0.72) to excellent (0.94). Lower baseline mental health (MCS), higher baseline physical health (PCS) and knee function scores (KOS-ADL, IKDC Subjective), lower baseline activity demand (Marx, Cincinnati sports), worse pain symptoms (Cincinnati pain, SF-36 pain), and higher BMI were thematic predictors contributing to failure to achieve the MCID or SCB at 1 and 2 years postoperatively.

CONCLUSION

Our machine learning models were effective in predicting outcomes and elucidating the relationships between baseline factors contributing to achieving the MCID for OCA of the knee. Patients who preoperatively report poor mental health, catastrophize pain symptoms, compensate with higher physical health and knee function, and exhibit lower activity demands are at risk for failing to reach clinically meaningful outcomes after OCA of the knee.

The state of adoption of anesthesia information management systems in Canadian academic anesthesia departments: a survey

PURPOSE

Anesthesia information management systems (AIMS) are gradually replacing paper documentation of anesthesia care. This study sought to determine the current status of AIMS adoption and the level of health informatics expertise in Canadian academic anesthesia departments.

METHODS

Department heads or their designates of Canadian academic anesthesia departments were invited by e-mail to complete an online survey between September 2019 and February 2020. The survey elicited information on current AIMS or future plans for an AIMS installation, the number of department members dedicated to clinical informatics issues, the gross level of health informatics expertise at each department, perceived advantages of AIMS, and perceived disadvantages of and barriers to implementation of AIMS.

RESULTS

Of the 64 departments invited to participate, 63 (98.4%) completed the survey. Only 21 (33.3%) of the departments had AIMS. Of the 42 departments still charting on paper, 23 (54.8%) reported planning to install an AIMS within the next five years. Forty-six departments (73%) had at least one anesthesiologist tasked with dealing with AIMS or electronic health record issues. Most reported having no department members with extensive knowledge or formal training in health informatics. The top three perceived barriers and disadvantages to an AIMS installation were its initial cost, lack of funding, and a lack of technical support dedicated specifically to AIMS. The top three advantages departments wished to prioritize with AIMS were accurate clinical documentation, better data for quality improvement initiatives, and better data for research.

CONCLUSIONS

A majority of Canadian academic anesthesia departments are still using paper records, but this trend is expected to reverse in the next five years as more departments install an AIMS. Health informatics expertise is lacking in most of the departments, with a minority planning to support the training of future anesthesia informaticians.