Rates of Subjective Failure After Both Isolated and Combined Posterior Cruciate Ligament Reconstruction: A Study From the Norwegian Knee Ligament Registry 2004-2021.

BACKGROUND: Outcomes after posterior cruciate ligament (PCL) reconstruction (PCLR) have been reported to be inferior to those of anterior cruciate ligament reconstruction. Furthermore, combined ligament injuries have been reported to have inferior outcomes compared with isolated PCLR. PURPOSE/HYPOTHESIS: The purpose of this study was to report on PCLR outcomes and failure rates and compare these outcomes between isolated PCLR and multiligament knee surgery involving the PCL. The hypothesis was that combined PCL injury reconstruction would have higher rates of subjective failure and revision relative to isolated PCLR. STUDY DESIGN: Cohort study; Level of evidence, 3. METHODS: Patients with primary PCLR with or without concomitant ligament injuries registered in the Norwegian Knee Ligament Registry between 2004 and 2021 were included. Knee injury and Osteoarthritis Outcome Score (KOOS) totals were collected preoperatively and at 2 years and 5 years postoperatively. The primary outcome measure was failure, defined as either a revision surgery or a KOOS Quality of Life (QoL) subscale score <44. RESULTS: The sample included 631 primary PCLR procedures, with 185 (29%) isolated PCLR procedures and 446 (71%) combined reconstructions, with a median follow-up time of 7.3 and 7.9 years, respectively. The majority of patients had poor preoperative knee function as defined by a KOOS QoL score <44 (90.1% isolated PCLR, 85.7% combined PCL injuries; P = .24). Subjective outcomes improved significantly at 2- and 5-year follow-up compared with preoperative assessments in both groups (P < .001); however, at 2 years, 49.5% and 46.5% had subjective failure (KOOS QoL <44) for isolated PCLR and combined PCLR, respectively (P = .61). At 5 years, the subjective failure rates of isolated and combined PCLR were 46.7% and 34.2%, respectively (P = .04). No significant difference was found in revision rates between the groups at 5 years (1.9% and 4.6%, respectively; P = .07). CONCLUSION: Patients who underwent PCLR had improved KOOS QoL scores relative to their preoperative state. However, the subjective failure rate was high for both isolated and multiligament PCLR. Within the first 2 years after surgery, patients who undergo isolated PCLR can be expected to have similar failure rates to patients who undergo combined ligament reconstructions.

Autologous Chondrocyte Implantation Is Not Better Than Arthroscopic Debridement for the Treatment of Symptomatic Cartilage Lesions of the Knee: Two-Year Results From a Randomized-Controlled Trial.

Purpose: To compare the functional and patient-reported outcome measures after autologous chondrocyte implantation (ACI) and arthroscopic debridement (AD) in symptomatic, isolated cartilage injuries larger than 2 cm2 in patients aged 18 to 50 years. Methods: Twenty-eight patients were included and randomized to ACI (n = 15) or AD (n = 13) and followed for 2 years. The primary outcome was the change in the Knee injury and Osteoarthritis Outcome Score (KOOS) Quality of Life (QoL) subscale. Results: The mean age at inclusion was 34.1 (standard deviation [SD] 8.5) years. There were 19 (68%) male patients. The mean size of the lesion was 4.2 (SD 1.7) cm2. There was a statistically significant and clinically meaningful improvement in patient-reported outcome measures from baseline to 2 years in both groups. The improvement from baseline to final follow-up for the primary endpoint (the KOOS QoL subscale) was larger for the AD group (39.8, SD 9.4) compared with the ACI group (23.8, SD 6.7), but this difference was not statistically significant (P = .17). However, according to a mixed linear model there were statistically significantly greater scores in the AD group for several KOOS subscales at several time points, including KOOS QoL, KOOS pain, and KOOS sport and recreation at 2 years. Conclusions: This study indicates that AD followed by supervised physiotherapy is equal to or better than ACI followed by supervised physiotherapy in patients with isolated cartilage lesions of the knee larger than 2 cm2. The improvement in KOOS QoL score from baseline to 2 years was clinically meaningful for both groups (23.8 points for ACI and 39.8 points AD), and larger for the AD group by 16 points. Level of Evidence: Level I, prospective randomized controlled trial.

Knee dislocations with vascular injuries - a review article.

Knee dislocations are complex and devastating injuries that are potentially limb threatening. A high level of suspicion is required to diagnose and treat these injuries properly and timely because some of the knee dislocations spontaneously reduce, and the seriousness of the injury might not be appreciated early. Early diagnosis of concomitant vascular injuries is imperative to avoid limb loss because the risk of amputation is high when diagnosis and timely intervention are delayed. It is recommended that serial ankle-brachial index (ABI) be performed in all patients with suspected knee dislocation. This is particularly important in fracture dislocations, high-energy trauma, morbidly obese patients, lateral sided injuries, concomitant peroneal nerve injuries and fracture in the ipsilateral limb because these were demonstrated to be associated with a high risk of concomitant vascular injuries in knee dislocations. In cases where serial ABI cannot be performed, in high-risk patients and ABI less-than 0.9, a CT angiography should be performed.

Increased risk for early revision with quadriceps graft compared with patellar tendon graft in primary ACL reconstructions.

PURPOSE: Bone patella-tendon bone (BPTB) and hamstring tendon (HT) autografts are the most used grafts in primary anterior cruciate ligament (ACL) reconstructions (ACLR) in Norway. Quadriceps tendon (QT) autograft has gained more popularity during the past years. The purpose of this study is to compare revision rates and patient-reported outcomes of primary QT with BPTB and HT autograft ACL reconstructions in Norway at 2-year follow-up. It was hypothesized that there would be no difference in 2-year revision rates between all three autografts. METHODS: Data included primary ACLR without concomitant ligament surgeries, registered in the Norwegian Knee Ligament Register from 2004 through 2021. Revision rates at 2 years were calculated using Kaplan-Meier analysis. Hazard ratios (HR) for revision were estimated using multivariable Cox regression analysis with revision within 2 years as endpoint. Mean change in patient-reported outcome was recorded preoperatively and at 2 years through the Knee Injury and Osteoarthritis Outcome Score (KOOS) subcategories 'Sport' and 'Quality of Life' was measured for patients that were not revised and analysed with multiple linear regression. RESULTS: A total of 24,790 primary ACLRs were identified, 10,924 with BPTB, 13,263 with HT and 603 with a QT graft. Patients in the QT group were younger (23.5 years), more of them were women (58.2%) and over 50% had surgery <3 months after injury. The QT group had the highest prevalence of meniscal injuries (61.9%). Revision estimates at 2-years were 3.6%, 2.5% and 1.2% for QT, HT and BPTB, respectively (p < 0.001). In a Cox regression analysis with QT as reference, BPTB had a lower risk of revision (HR 0.4, 95% Cl 0.2-0.7, p < 0.001). No significant difference was observed in the revision risk between QT and HT (HR 1.1, 95% Cl 0.7-1.8, n.s.). The two most common reported reasons for revision were: traumatic graft rupture and nontraumatic graft failure. There were no differences between the groups in change of KOOS in subcategories 'Sport' and 'Quality of Life' at 2-years follow-up. CONCLUSION: The 2-year risk of revision after ACLR with QT was higher than BPTB and similar to HT. No difference was found between the groups in patient-reported outcomes. This study provides valuable insights for both surgeons and patients when making decisions about the choice of autografts in primary ACL reconstructions. LEVEL OF EVIDENCE: Level II.

Unsupervised Machine Learning of the Combined Danish and Norwegian Knee Ligament Registers: Identification of 5 Distinct Patient Groups With Differing ACL Revision Rates.

BACKGROUND: Most clinical machine learning applications use a supervised learning approach using labeled variables. In contrast, unsupervised learning enables pattern detection without a prespecified outcome. PURPOSE/HYPOTHESIS: The purpose of this study was to apply unsupervised learning to the combined Danish and Norwegian knee ligament register (KLR) with the goal of detecting distinct subgroups. It was hypothesized that resulting groups would have differing rates of subsequent anterior cruciate ligament reconstruction (ACLR) revision. STUDY DESIGN: Cohort study; Level of evidence, 3. METHODS: K-prototypes clustering was performed on the complete case KLR data. After performing the unsupervised learning analysis, the authors defined clinically relevant characteristics of each cluster using variable summaries, surgeons' domain knowledge, and Shapley Additive exPlanations analysis. RESULTS: Five clusters were identified. Cluster 1 (revision rate, 9.9%) patients were young (mean age, 22 years; SD, 6 years), received hamstring tendon (HT) autograft (91%), and had lower baseline Knee injury and Osteoarthritis Outcome Score (KOOS) Sport and Recreation (Sports) scores (mean, 25.0; SD, 15.6). Cluster 2 (revision rate, 6.9%) patients received HT autograft (89%) and had higher baseline KOOS Sports scores (mean, 67.2; SD, 16.5). Cluster 3 (revision rate, 4.7%) patients received bone-patellar tendon-bone (BPTB) or quadriceps tendon (QT) autograft (94%) and had higher baseline KOOS Sports scores (mean, 65.8; SD, 16.4). Cluster 4 (revision rate, 4.1%) patients received BPTB or QT autograft (88%) and had low baseline KOOS Sports scores (mean, 20.5; SD, 14.0). Cluster 5 (revision rate, 3.1%) patients were older (mean age, 42 years; SD, 7 years), received HT autograft (89%), and had low baseline KOOS Sports scores (mean, 23.4; SD, 17.6). CONCLUSION: Unsupervised learning identified 5 distinct KLR patient subgroups and each grouping was associated with a unique ACLR revision rate. Patients can be approximately classified into 1 of the 5 clusters based on only 3 variables: age, graft choice (HT, BPTB, or QT autograft), and preoperative KOOS Sports subscale score. If externally validated, the resulting groupings may enable quick risk stratification for future patients undergoing ACLR in the clinical setting. Patients in cluster 1 are considered high risk (9.9%), cluster 2 patients medium risk (6.9%), and patients in clusters 3 to 5 low risk (3.1%-4.7%) for revision ACLR.

Previous cartilage surgery is associated with inferior patient-reported outcomes after knee arthroplasty.

PURPOSE: The hypothesis of the present study assumed that a history of focal cartilage lesions would not affect Knee Injury and Osteoarthritis Outcome scores (KOOSs) following knee arthroplasty compared to a matched national cohort of knee arthroplasty patients. METHODS: Fifty-eight knee arthroplasty patients with previous surgery for focal cartilage lesions (cartilage cohort) were compared to a matched cohort of 116 knee arthroplasty patients from the Norwegian Arthroplasty Register (control group). Age, sex, primary or revision arthroplasty, type of arthroplasty (total, unicondylar or patellofemoral), year of arthroplasty surgery and arthroplasty brand were used as matching criteria. Demographic data and KOOS were obtained through questionnaires. Regression models were employed to adjust for confounding factors. RESULTS: Mean follow-up post knee arthroplasty surgery was 7.6 years (range 1.2-20.3) in the cartilage cohort and 8.1 (range 1.0-20.9) in the control group. The responding patients were at the time of surgery 54.3 versus 59.0 years in the cartilage and control group, respectively. At follow-up the control group demonstrated higher adjusted Knee Injury and Osteoarthritis Outcome subscores than the previous focal cartilage patients with a mean adjusted difference (95% confidence interval in parentheses): Symptoms 8.4 (0.3, 16.4), Pain 11.8 (2.2, 21.4), Activities of daily living (ADL) 9.3 (-1.2, 18.6), Sport and recreation 8.9 (-1.6, 19.4) and Quality of Life (QoL) 10.6 (0.2, 21.1). The control group also demonstrated higher odds of reaching the patient-acceptable symptom state threshold for the Knee Injury and Osteoarthritis Outcome subscores with odds ratio: Symptoms 2.7 (1.2, 6.4), Pain 3.0 (1.3, 7.0), ADL 2.1 (0.9, 4.6) and QoL 2.4 (1.0, 5.5). CONCLUSION: Previous cartilage surgery was associated with inferior patient-reported outcomes after knee arthroplasty. These patients also exhibited significantly lower odds of reaching the patient-acceptable symptom state threshold for the Knee Injury and Osteoarthritis Outcome subscores. LEVEL OF EVIDENCE: Level III.

The Delaware-Oslo ACL Cohort treatment algorithm yields superior outcomes to usual care 9-12 years after anterior cruciate ligament reconstruction.

PURPOSE: Patient-reported outcomes were compared between participants who followed the treatment algorithm of the Delaware-Oslo ACL Cohort, consisting of progressive preoperative and postoperative rehabilitation, patient education, clinical testing and shared decision-making about treatment choice, and those who followed usual care 9-12 years after anterior cruciate ligament reconstruction (ACLR). METHODS: Participants with primary ACLR were included from the Norwegian arm of the Delaware-Oslo ACL Cohort and the Norwegian Knee Ligament Registry (usual care). The Knee Injury and Osteoarthritis Outcome Score (KOOS) subscale scores and the International Knee Documentation Committee-Subjective Knee Form (IKDC-SKF) scores were compared. KOOS scores for the usual care group were converted to IKDC-SKF scores with recently published validated crosswalk. The percentages of participants with scores above predefined thresholds for patient acceptable symptom state (PASS) were also calculated. RESULTS: Eighty of 100 (80%) participants from the Delaware-Oslo ACL Cohort and 1588 of 3248 (49%) from the usual care group participated in the follow-up. Participants from the Delaware-Oslo ACL Cohort had higher KOOS subscale (p < 0.001) and IKDC-SKF scores (p < 0.001), and a higher percentage reached PASS (84%-96% vs. 62%-76%, p ≤ 0.002) for KOOS Pain, symptoms, activities of daily living and sports compared to the usual care group. No significant differences were found for KOOS quality of life scores (not significant [n.s.]) or PASS percentages (80% vs. 74%, n.s.). CONCLUSION: Participants with ACLR who followed the Delaware-Oslo ACL Cohort treatment algorithm had reduced knee symptoms, superior function and higher percentages of satisfactory outcomes than participants who followed usual care. LEVEL OF EVIDENCE: Level II.

External validation of the Norwegian anterior cruciate ligament reconstruction revision prediction model using patients from the STABILITY 1 Trial.

PURPOSE: A machine learning-based anterior cruciate ligament (ACL) revision prediction model has been developed using Norwegian Knee Ligament Register (NKLR) data, but lacks external validation outside Scandinavia. This study aimed to assess the external validity of the NKLR model (https://swastvedt.shinyapps.io/calculator_rev/) using the STABILITY 1 randomized clinical trial (RCT) data set. The hypothesis was that model performance would be similar. METHODS: The NKLR Cox Lasso model was selected for external validation owing to its superior performance in the original study. STABILITY 1 patients with all five predictors required by the Cox Lasso model were included. The STABILITY 1 RCT was a prospective study which randomized patients to receive either a hamstring tendon autograft (HT) alone or HT plus a lateral extra-articular tenodesis (LET). Since all patients in the STABILITY 1 trial received HT ± LET, three configurations were tested: 1: all patients coded as HT, 2: HT + LET group coded as bone-patellar tendon-bone (BPTB) autograft, 3: HT + LET group coded as unknown/other graft choice. Model performance was assessed via concordance and calibration. RESULTS: In total, 591/618 (95.6%) STABILITY 1 patients were eligible for inclusion, with 39 undergoing revisions within 2 years (6.6%). Model performance was best when patients receiving HT + LET were coded as BPTB. Concordance was similar to the original NKLR prediction model for 1- and 2-year revision prediction (STABILITY: 0.71; NKLR: 0.68-0.69). Concordance 95% confidence interval (CI) ranged from 0.63 to 0.79. The model was well calibrated for 1-year prediction while the 2-year prediction demonstrated evidence of miscalibration. CONCLUSION: When patients in STABILITY 1 who received HT + LET were coded as BPTB in the NKLR prediction model, concordance was similar to the index study. However, due to a wide 95% CI, the true performance of the prediction model with this Canadian and European cohort is unclear and a larger data set is required to definitively determine the external validity. Further, better calibration for 1-year predictions aligns with general prediction modelling challenges over longer periods. While not a large enough sample size to elicit the true accuracy and external validity of the prediction model when applied to North American patients, this analysis provides more support for the notion that HT plus LET performs similarly to BPTB reconstruction. In addition, despite the wide confidence interval, this study suggests optimism regarding the accuracy of the model when applied outside of Scandinavia. LEVEL OF EVIDENCE: Level 3, cohort study.

Utilization of Imaging for Severe Injuries at the Beijing 2022 Winter Olympic Games.

Purpose: In order to better understand the imaging of severe trauma in sport, this study describes the imaging modalities utilized to image athletes who experienced severe traumatic injuries at the Beijing Winter Olympic Games 2022, the distribution of these modalities in relation to the sporting facilities, and the types of injuries imaged in each sport. Methods: This is a retrospective analysis with descriptive tables and figures, performed on a single population (athletes of the Beijing Winter Olympic Games 2022). Results: Of the 2871 athletes in the Beijing Winter Olympic Games, there were 40 athletes with severe injuries who underwent medical imaging. MRI was used more often than Radiography or CT. Athletes at venues without MRI on site had to be transferred to adjacent hospitals for care. Alpine and Freestyle skiing athletes experienced the majority of severe traumatic injuries at this Olympic Games, and the majority of injuries were to the lower limb. Conclusions: Access to medical imaging for severely injured athletes is a critical consideration in the organization of any sporting event. MRI in particular is highly utilized in this population.

Olympic Games during nationwide lockdown: sports injuries and illnesses, including COVID-19, at the Beijing 2022 Winter Olympics.

OBJECTIVE: The objective of this study is to describe the incidence of injuries and illnesses sustained during the Beijing Winter Olympic Games from 4 February 2022 to 20 February 2022. METHODS: We recorded the daily number of athlete injuries and illnesses (1) through the reporting of all National Olympic Committee (NOC) medical teams and (2) in the polyclinic and medical venues by the Beijing 2022 medical staff. RESULTS: In total, 2848 athletes (1276 women, 45%; 1572 men, 55%) from 91 NOCs were followed prospectively for the occurrence of injury and illness. NOC and Beijing 2022 medical staff reported 289 injuries and 109 illnesses, equalling 10.1 injuries and 3.8 illnesses per 100 athletes over the 17-day period. The injury incidence was highest in ski halfpipe (30%), ski big air (28%), snowboard slopestyle (23%) and ski slopestyle (22%), and lowest (1%-2%) in curling, alpine mixed team parallel slalom, Nordic combined and alpine super-G. The illness incidence was highest in ski aerials (10%), skeleton (8%), cross-country skiing (8%) and Nordic combined (7%). In the study period, COVID-19 affected 32 athletes, accounting for 29% of all illnesses affecting 1.1% of all athletes. CONCLUSION: Overall, 10% of the athletes incurred an injury and 4% an illness during the Beijing Winter Olympic Games. The incidence of illnesses overall, which was the lowest yet recorded in the Winter Olympic Games, and COVID-19 was mitigated through comprehensive countermeasures.

2023 International Olympic Committee's (IOC) consensus statement on Relative Energy Deficiency in Sport (REDs).

Relative Energy Deficiency in Sport (REDs) was first introduced in 2014 by the International Olympic Committee's expert writing panel, identifying a syndrome of deleterious health and performance outcomes experienced by female and male athletes exposed to low energy availability (LEA; inadequate energy intake in relation to exercise energy expenditure). Since the 2018 REDs consensus, there have been >170 original research publications advancing the field of REDs science, including emerging data demonstrating the growing role of low carbohydrate availability, further evidence of the interplay between mental health and REDs and more data elucidating the impact of LEA in males. Our knowledge of REDs signs and symptoms has resulted in updated Health and Performance Conceptual Models and the development of a novel Physiological Model. This Physiological Model is designed to demonstrate the complexity of either problematic or adaptable LEA exposure, coupled with individual moderating factors, leading to changes in health and performance outcomes. Guidelines for safe and effective body composition assessment to help prevent REDs are also outlined. A new REDs Clinical Assessment Tool-Version 2 is introduced to facilitate the detection and clinical diagnosis of REDs based on accumulated severity and risk stratification, with associated training and competition recommendations. Prevention and treatment principles of REDs are presented to encourage best practices for sports organisations and clinicians. Finally, methodological best practices for REDs research are outlined to stimulate future high-quality research to address important knowledge gaps.

A Machine Learning Model Demonstrates Excellent Performance in Predicting Subscapularis Tears Based on Pre-Operative Imaging Parameters Alone.

PURPOSE: The purpose of this study was to develop a machine learning model capable of identifying subscapularis tears before surgery based on imaging and physical examination findings. METHODS: Between 2010 and 2020, 202 consecutive shoulders underwent arthroscopic rotator cuff repair by a single surgeon. Patient demographics, physical examination findings (including range of motion, weakness with internal rotation, lift/push-off test, belly press test, and bear hug test), and imaging (including direct and indirect signs of tearing, biceps status, fatty atrophy, cystic changes, and other similar findings) were included for model creation. RESULTS: Sixty percent of the shoulders had partial or full thickness tears of the subscapularis verified during surgery (83% of these were upper third). Using only preoperative imaging-related parameters, the XGBoost model demonstrated excellent performance at predicting subscapularis tears (c-statistic, 0.84; accuracy, 0.85; F1 score, 0.87). The top 5 features included direct signs related to the presence of tearing as evidenced on magnetic resonance imaging (MRI) (changes in tendon morphology and signal), as well as the quality of the MRI and biceps pathology. CONCLUSION: In this study, machine learning was successful in predicting subscapularis tears by MRI alone in 85% of patients, and this accuracy did not decrease by isolating the model to the top features. The top five features included direct signs related to the presence of tearing as evidenced on MRI (changes in tendon morphology and signal), as well as the quality of the MRI and biceps pathology. Last, in advanced modeling, the addition of physical examination or patient characteristics did not make a significant difference in the predictive ability of this model. LEVEL OF EVIDENCE: Level III, diagnostic case-control study.

Injury Patterns in Posterolateral Corner Knee Injury.

Background: Posterolateral corner (PLC) knee injuries associated with different injury mechanisms are not well known. Purpose/Hypothesis: This study sought to assess the patterns of associated injuries in the setting of PLC injury. The hypothesis was that there are recognizable injury patterns in PLC injuries that may correlate with injury mechanism. Study Design: Cross-sectional study; Level of evidence, 3. Methods: Patients who sustained a multiligament knee injury were retrospectively reviewed. Patients who sustained an acute grade 3 PLC injury and underwent surgery were enrolled in this study. A description of the PLC injury (location of the injury of the fibular collateral ligament [FCL], popliteus tendon, and/or popliteofibular ligament) and reported concomitant injuries (biceps femoris tendon or meniscal tears, cartilage pathology and/or peroneal nerve palsy, or bone bruises) were collected and classified based on intraoperative and magnetic resonance imaging (MRI) findings. Results: Of 135 patients reviewed, 83 did not have PLC involvement and 13 were excluded due to insufficient MRI scans available. Thus, 39 patients were included in this study. For both the anterior cruciate ligament (ACL)-PLC and ACL-posterior cruciate ligament-PLC injury patterns, the most frequent injury pattern entailed a bone bruise of the anteromedial (AM) femur and tibia, an FCL tear from the fibular head, the popliteus tendon avulsed off the femur, a biceps femoris tendon torn off the fibular head, and a common peroneal nerve palsy. Conversely, when no bone bruise occurred on the AM femur and tibia, the FCL was injured on the femoral side and the popliteus tendon, biceps femoris, and peroneal nerve were not injured. Conclusion: AM bone bruise was associated with a peroneal nerve injury in almost half of the patients, and peroneal nerve injury was not seen if there was no AM bone bruise.

Major Increase in Incidence of Pediatric ACL Reconstructions From 2005 to 2021: A Study From the Norwegian Knee Ligament Register.

BACKGROUND: The incidence of pediatric and adolescent anterior cruciate ligament reconstruction (ACLR) is increasing in several countries. It is uncertain whether this trend applies to countries that traditionally prefer an initial nonoperative treatment approach whenever possible, like Norway. Nationwide, long-term patient-reported outcomes and revision rates after ACLR in the pediatric population are also lacking. PURPOSE: To determine the incidence of pediatric ACLR in Norway since 2005, as well as to detect trends in surgical details and describe patient-reported outcomes up to 10 years after ACLR. STUDY DESIGN: Descriptive cohort study. METHODS: This study is based on prospectively collected data on girls ≤14 years and boys ≤16 years, registered in the Norwegian Knee Ligament Register at the time of their primary ACLR, between 2005 and 2021. The main outcome was the incidence of ACLR, adjusted to the corresponding population numbers for each year. The time trend was analyzed by comparing the mean of the first and last 3-year period (2005-2007 and 2019-2021). Patient-reported outcomes were assessed using the Knee injury and Osteoarthritis Outcome Score preoperatively and at 2, 5, and 10 years postoperatively. RESULTS: A total of 1476 patients (1484 cases) were included, with a mean follow-up of 8.1 years (range, 1-17). The incidence of pediatric ACLRs per 100,000 population increased from 18 to 26, which corresponds to an increase of 40% for boys and 55% for girls. Concurrent meniscal procedures increased significantly from 45% to 62%, and the proportion of meniscal repairs increased from 19% to 43% when comparing the first and last time period. The mean Knee injury and Osteoarthritis Outcome Score values for the Sport and Recreation and Quality of Life subscales were between 72 and 75 at the 2-, 5- and 10-year follow-up. The 5-year revision rate was 9.9%. CONCLUSION: There was a major increase in incidence of pediatric ACLR in Norway during the study period. There was a shift in the approach to concomitant meniscal procedures from resection to repair, with more than a doubling of the proportion of meniscal repairs. Patient-reported outcomes revealed long-lasting reduced knee function.

Surveillance of athlete mental health symptoms and disorders: a supplement to the International Olympic Committee's consensus statement on injury and illness surveillance.

In 2019, the International Olympic Committee (IOC) published a consensus statement outlining the principles for recording and reporting injury and illness in elite sport. The authors encouraged sport federations to adapt the framework to their sport-specific context. Since this publication, several sports have published extensions to the IOC consensus statement.In response to a paucity of epidemiological data on athlete mental health, the IOC mental health working group adapted the IOC consensus statement on injury and illness surveillance to improve the capturing of athlete mental health data. In addition to the members of the working group, other experts and athlete representatives joined the project team to address gaps in expertise, and to add stakeholder perspective, respectively. Following an in-person meeting, the authors worked remotely, applying the scientific literature on athlete mental health to the IOC injury and illness surveillance framework. A virtual meeting was held to reach consensus on final recommendations.Practical outcomes based on the analysis of the scientific literature are provided with respect to surveillance design, data collection and storage, data analysis and reporting of athlete mental health data. Mental health-specific report forms for athlete and health professional utilisation are included for both longitudinal and event-specific surveillance.Ultimately, this publication should encourage the standardisation of surveillance methodology for mental health symptoms and disorders among athletes, which will improve consistency in study designs, thus facilitating the pooling of data and comparison across studies. The goal is to encourage systematic surveillance of athlete mental health.

Epidemiology of International Match Injuries in Scottish Rugby: A Prospective Cohort Study.

Fifteen-a-side rugby union ("rugby") is a full-contact sport played separately by men and women, with large injury incidences reported previously. Context specific injury surveillance fulfils governing bodies' duty of care to understand risks to player welfare, yet no contemporary match injury epidemiology studies exist for international players in Scotland. The current study therefore aimed to describe the incidence, severity, burden and nature of match injuries sustained by Scotland's men's and women's national teams. A prospective cohort study of injuries recorded in matches across the 2017/18 and 2018/19 seasons was undertaken, with injury and exposure definitions in line with the international consensus for injury surveillance in rugby. Injury incidence was 120.0 (men) and 166.7/1,000 player match hours (women), injury severity was 12.0 (median) and 31.2 days (mean) for men, and 11.0 (median) and 30.2 days (mean) for women. Injury burden was 3,745 (men) and 5,040 days absence/1,000 player match hours (women). Concussion was the most common specific injury for men (22.5/1,000 hours) and women (26.7/1,000 hours). No statistical differences were found for incidence or severity measures between sexes. Injury incidence was greater than recent Rugby World Cup studies. High incidences of concussion reinforces the need for prevention strategies targeting this injury.

Ceiling Effect of the Combined Norwegian and Danish Knee Ligament Registers Limits Anterior Cruciate Ligament Reconstruction Outcome Prediction.

BACKGROUND: Clinical tools based on machine learning analysis now exist for outcome prediction after primary anterior cruciate ligament reconstruction (ACLR). Relying partly on data volume, the general principle is that more data may lead to improved model accuracy. PURPOSE/HYPOTHESIS: The purpose was to apply machine learning to a combined data set from the Norwegian and Danish knee ligament registers (NKLR and DKRR, respectively), with the aim of producing an algorithm that can predict revision surgery with improved accuracy relative to a previously published model developed using only the NKLR. The hypothesis was that the additional patient data would result in an algorithm that is more accurate. STUDY DESIGN: Cohort study; Level of evidence, 3. METHODS: Machine learning analysis was performed on combined data from the NKLR and DKRR. The primary outcome was the probability of revision ACLR within 1, 2, and 5 years. Data were split randomly into training sets (75%) and test sets (25%). There were 4 machine learning models examined: Cox lasso, random survival forest, gradient boosting, and super learner. Concordance and calibration were calculated for all 4 models. RESULTS: The data set included 62,955 patients in which 5% underwent a revision surgical procedure with a mean follow-up of 7.6 ± 4.5 years. The 3 nonparametric models (random survival forest, gradient boosting, and super learner) performed best, demonstrating moderate concordance (0.67 [95% CI, 0.64-0.70]), and were well calibrated at 1 and 2 years. Model performance was similar to that of the previously published model (NKLR-only model: concordance, 0.67-0.69; well calibrated). CONCLUSION: Machine learning analysis of the combined NKLR and DKRR enabled prediction of the revision ACLR risk with moderate accuracy. However, the resulting algorithms were less user-friendly and did not demonstrate superior accuracy in comparison with the previously developed model based on patients from the NKLR alone, despite the analysis of nearly 63,000 patients. This ceiling effect suggests that simply adding more patients to current national knee ligament registers is unlikely to improve predictive capability and may prompt future changes to increase variable inclusion.