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.

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.

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.

Musculoskeletal pain is not clearly associated with the risk of anterior cruciate ligament reconstruction in adolescents.

Objectives: The purpose of this study was to investigate whether self-reported musculoskeletal pain (MSP) was associated with a future anterior cruciate ligament reconstruction (ACLR). Methods: In this population-based prospective cohort study, we included 8087 participants from the adolescent part of the Trøndelag Health Study (Young-HUNT) in Norway. The exposure was self-reported MSP from the Young-HUNT3 study (2006-2008), which was categorised into two MSP load groups (high MSP and low MSP) based on frequency and number of pain sites. The outcome was ACLRs recorded in the Norwegian Knee Ligament Register between 2006 and 2019. Logistic regression was used to investigate association between MSP load and ACLR, given as ORs with 95% CIs. All tests were two-sided and p values of ≤0.05 were considered statistically significant. Results: 8087 adolescents were included. We identified a total of 99 ACLRs, with 6 ACLRs (0.9%) in adolescents who reported high MSP load and 93 ACLRs (1.3%) among those who reported low MSP load. Adolescents reporting high MSP load had 23% lower odds of an ACLR (OR 0.77, 95% CI 0.31 to 1.91) compared with adolescents with low MSP load. However, the CIs were very wide. Conclusion: Self-reported high MSP load in adolescents was not associated with increased risk of future ACLR. Although the number of participants was high, the relatively few cases of ACLR mean that we cannot be conclusive about the presence or absence of an association.

Predicting subjective failure of ACL reconstruction: a machine learning analysis of the Norwegian Knee Ligament Register and patient reported outcomes.

OBJECTIVES: Accurate prediction of outcome following anterior cruciate ligament (ACL) reconstruction is challenging, and machine learning has the potential to improve our predictive capability. The purpose of this study was to determine if machine learning analysis of the Norwegian Knee Ligament Register (NKLR) can (1) identify the most important risk factors associated with subjective failure of ACL reconstruction and (2) develop a clinically meaningful calculator for predicting the probability of subjective failure following ACL reconstruction. METHODS: Machine learning analysis was performed on the NKLR. All patients with 2-year follow-up data were included. The primary outcome was the probability of subjective failure 2 years following primary surgery, defined as a Knee Injury and Osteoarthritis Outcome Score (KOOS) Quality of Life (QoL) subscale score of <44. Data were split randomly into training (75%) and test (25%) sets. Four models intended for this type of data were tested: Lasso logistic regression, random forest, generalized additive model (GAM), and gradient boosted regression (GBM). These four models represent a range of approaches to statistical details like variable selection and model complexity. Model performance was assessed by calculating calibration and area under the curve (AUC). RESULTS: Of the 20,818 patients who met the inclusion criteria, 11,630 (56%) completed the 2-year follow-up KOOS QoL questionnaire. Of those with complete KOOS data, 22% reported subjective failure. The lasso logistic regression, GBM, and GAM all demonstrated AUC in the moderate range (0.67-0.68), with the GAM performing best (0.68; 95% CI 0.64-0.71). Lasso logistic regression, GBM, and the GAM were well-calibrated, while the random forest showed evidence of mis-calibration. The GAM was selected to create an in-clinic calculator to predict subjective failure risk at a patient-specific level (https://swastvedt.shinyapps.io/calculator_koosqol/). CONCLUSION: Machine learning analysis of the NKLR can predict subjective failure risk following ACL reconstruction with fair accuracy. This algorithm supports the creation of an easy-to-use in-clinic calculator for point-of-care risk stratification. Clinicians can use this calculator to estimate subjective failure risk at a patient-specific level when discussing outcome expectations preoperatively. LEVEL OF EVIDENCE: Level-III Retrospective review of a prospective national register.

ACL Reconstruction Patients Have Increased Risk of Knee Arthroplasty at 15 Years of Follow-up: Data from the Norwegian Knee Ligament Register and the Norwegian Arthroplasty Register from 2004 to 2020.

Anterior cruciate ligament (ACL) injury is considered a risk factor for osteoarthritis. The primary aim of the present study was to investigate the cumulative risk of, and risk factors associated with, a subsequent knee arthroplasty after an ACL reconstruction at up to 15 years of follow-up. The secondary aim was to compare the relative risk of knee arthroplasty after ACL reconstruction compared with that in the general population. Methods: Data were analyzed by combining data from 2 national registries, the Norwegian Knee Ligament Register and the Norwegian Arthroplasty Register. The cumulative risk of knee arthroplasty after undergoing ACL reconstruction was calculated as 1 minus the corresponding Kaplan-Meier estimate, and possible risk factors for knee arthroplasty after ACL reconstruction were assessed in a Cox regression model with hazard ratios (HRs) as estimated effect measurements. The relative risk of knee arthroplasty for patients managed with ACL reconstruction as compared with that in the general population was calculated in stratified age groups. Results: From the study population of 27,122 knees, 115 knees underwent knee arthroplasty. We found a 1.1% (95% confidence interval [CI], 0.9 to 1.4) cumulative risk of knee arthroplasty 15 years after ACL reconstruction. Deep cartilage injury, ICRS (International Cartilage Repair Society) grade 3 to 4 (HR, 4.8; 95% CI, 3.1 to 7.6), revision of the ACL (HR, 3.9; 95% CI, 2.2 to 7.1), and a 2-year postoperative KOOS Sport/Recreation subscore of <44 (HR, 3.1; 95% CI, 1.5 to 6.2) were important risk factors for knee arthroplasty. We found a higher risk of knee arthroplasty at the age of 30 to 39 years after a previous ACL reconstruction as compared with the general population (relative risk, 3.3; 95% CI, 1.6 to 6.7). Conclusions: Fifteen years after an ACL reconstruction, the overall cumulative risk of knee arthroplasty was 1.1%. Cartilage injury at the time of ACL reconstruction, revision ACL reconstruction, and a KOOS Sport/Recreation subscore of <44 (at 2 years postoperatively) were major risk factors for subsequent knee arthroplasty. We found a 3.3-times higher risk of knee arthroplasty at the age of 30 to 39 years after a previous ACL reconstruction as compared with that in the general population. Level of Evidence: Prognostic Level II. See Instructions for Authors for a complete description of levels of evidence.

Good validity in the Norwegian Knee Ligament Register: assessment of data quality for key variables in primary and revision cruciate ligament reconstructions from 2004 to 2013.

BACKGROUND: The Norwegian Knee Ligament Register was founded in 2004 to provide representative and reliable data on cruciate ligament surgery. The aim of this study was to evaluate the validity of key variables in the Norwegian Knee Ligament Register to reveal and prevent systematic errors or incompleteness, which can lead to biased reports and study conclusions. METHOD: We included a stratified cluster sample of 83 patients that had undergone both primary and revision anterior cruciate ligament surgery. A total of 166 medical records were reviewed and compared with their corresponding data in the database of the Norwegian Knee Ligament Register. We assessed the validity of a selection of key variables using medical records as a reference standard to compute the positive predictive values of the register data for the variables. RESULTS: The positive predictive values for the variables of primary and revision surgery ranged from 92 to 100% and from 39 to 100% with a mean positive predictive value of 99% and 88% respectively. Data on intraoperative findings and surgical details had high positive predictive values, ranging from 91 to 100% for both primary and revision surgery. The positive predictive value for the variable "date of injury" was 92% for primary surgeries but only 39% for revision surgeries. The positive predictive value for "activity at the time of injury" was 99% for primary surgeries and 52% for revisions. CONCLUSION: Overall, the data quality of the key variables examined in the Norwegian Knee Ligament Register was high, making the register a valid source for research.

Machine learning algorithm to predict anterior cruciate ligament revision demonstrates external validity.

PURPOSE: External validation of machine learning predictive models is achieved through evaluation of model performance on different groups of patients than were used for algorithm development. This important step is uncommonly performed, inhibiting clinical translation of newly developed models. Machine learning analysis of the Norwegian Knee Ligament Register (NKLR) recently led to the development of a tool capable of estimating the risk of anterior cruciate ligament (ACL) revision ( https://swastvedt.shinyapps.io/calculator_rev/ ). The purpose of this study was to determine the external validity of the NKLR model by assessing algorithm performance when applied to patients from the Danish Knee Ligament Registry (DKLR). METHODS: The primary outcome measure of the NKLR model was probability of revision ACL reconstruction within 1, 2, and/or 5 years. For external validation, all DKLR patients with complete data for the five variables required for NKLR prediction were included. The five variables included graft choice, femur fixation device, KOOS QOL score at surgery, years from injury to surgery, and age at surgery. Predicted revision probabilities were calculated for all DKLR patients. The model performance was assessed using the same metrics as the NKLR study: concordance and calibration. RESULTS: In total, 10,922 DKLR patients were included for analysis. Average follow-up time or time-to-revision was 8.4 (± 4.3) years and overall revision rate was 6.9%. Surgical technique trends (i.e., graft choice and fixation devices) and injury characteristics (i.e., concomitant meniscus and cartilage pathology) were dissimilar between registries. The model produced similar concordance when applied to the DKLR population compared to the original NKLR test data (DKLR: 0.68; NKLR: 0.68-0.69). Calibration was poorer for the DKLR population at one and five years post primary surgery but similar to the NKLR at two years. CONCLUSION: The NKLR machine learning algorithm demonstrated similar performance when applied to patients from the DKLR, suggesting that it is valid for application outside of the initial patient population. This represents the first machine learning model for predicting revision ACL reconstruction that has been externally validated. Clinicians can use this in-clinic calculator to estimate revision risk at a patient specific level when discussing outcome expectations pre-operatively. While encouraging, it should be noted that the performance of the model on patients undergoing ACL reconstruction outside of Scandinavia remains unknown. LEVEL OF EVIDENCE: III.

Predicting Anterior Cruciate Ligament Reconstruction Revision: A Machine Learning Analysis Utilizing the Norwegian Knee Ligament Register.

BACKGROUND: Several factors are associated with an increased risk of anterior cruciate ligament (ACL) reconstruction revision. However, the ability to accurately translate these factors into a quantifiable risk of revision at a patient-specific level has remained elusive. We sought to determine if machine learning analysis of the Norwegian Knee Ligament Register (NKLR) can identify the most important risk factors associated with subsequent revision of primary ACL reconstruction and develop a clinically meaningful calculator for predicting revision of primary ACL reconstruction. METHODS: Machine learning analysis was performed on the NKLR data set. The primary outcome was the probability of revision ACL reconstruction within 1, 2, and/or 5 years. Data were split randomly into training sets (75%) and test sets (25%). Four machine learning models were tested: Cox Lasso, survival random forest, generalized additive model, and gradient boosted regression. Concordance and calibration were calculated for all 4 models. RESULTS: The data set included 24,935 patients, and 4.9% underwent a revision surgical procedure during a mean follow-up (and standard deviation) of 8.1 ± 4.1 years. All 4 models were well-calibrated, with moderate concordance (0.67 to 0.69). The Cox Lasso model required only 5 variables for outcome prediction. The other models either used more variables without an appreciable improvement in accuracy or had slightly lower accuracy overall. An in-clinic calculator was developed that can estimate the risk of ACL revision (Revision Risk Calculator). This calculator can quantify risk at a patient-specific level, with a plausible range from near 0% for low-risk patients to 20% for high-risk patients at 5 years. CONCLUSIONS: Machine learning analysis of a national knee ligament registry can predict the risk of ACL reconstruction revision with moderate accuracy. This algorithm supports the creation of an in-clinic calculator for point-of-care risk stratification based on the input of only 5 variables. Similar analysis using a larger or more comprehensive data set may improve the accuracy of risk prediction, and future studies incorporating patients who have experienced failure of ACL reconstruction but have not undergone subsequent revision may better predict the true risk of ACL reconstruction failure. LEVEL OF EVIDENCE: Prognostic Level III. See Instructions for Authors for a complete description of levels of evidence.

Low annual hospital volume of anterior cruciate ligament reconstruction is not associated with higher revision rates.

PURPOSE: Surgery performed in low-volume centres has been associated with longer operating time, longer hospital stays, lower functional outcomes, and higher rates of revision surgery, complications and mortality. This has been reported consistently in the arthroplasty literature, but there is a paucity of data regarding the relationship between surgical volume and outcome following anterior cruciate ligament (ACL) reconstruction. The purpose was to compare ACL reconstruction failure rates between hospitals performing different annual surgical volumes. METHODS: All patients from the Norwegian Knee Ligament Register having primary autograft ACL reconstruction between 2004 and 2016 were included. Hospital volume was divided into quintiles based on the number of ACL reconstructions performed annually, defined arbitrarily as: 1-12 (V1), 13-24 (V2), 25-49 (V3), 50-99 (V4) and ≥ 100 (V5) annual procedures. Kaplan-Meier estimated survival curves and survival percentages were calculated with revision ACL reconstruction as the end point. Secondary outcome measures included (1) mean change in Knee Injury and Osteoarthritis Outcome Score (KOOS) Quality of Life (QoL) and Sport subsections from pre-operative to 5-year follow-up and (2) subjective failure defined as KOOS QoL < 44. RESULTS: Twenty thousand eight hundred and fifty patients met the inclusion criteria and 1195 (5.7%) underwent subsequent revision ACL reconstruction over the study period. Revision rates were lower in the lower volume hospitals compared with the higher volume hospitals (p < 0.001). There was no clinically significant difference in improvement between pre-operative and 5-year follow-up KOOS scores between hospital volume categories, but a higher proportion of patients having surgery at lower volume hospitals reported a subjective failure. Patients in the lower volume categories (V1-3) were more often male and older compared to the higher volume hospitals (V4-5). Concomitant meniscal injuries and participation in pivoting sports were most common in V5 compared with V1 (p < 0.001). Median operative time decreased as hospital volume increased, ranging from 90 min at V1 hospitals to 56 min at V5 hospitals (p < 0.001). CONCLUSION: Patients having ACL reconstruction at lower volume hospitals had a lower rate of subsequent revision surgery relative to higher volume hospitals. However, complications occurred more frequently, operative duration was longer, and the number of patients reporting a subjective failure of ACL reconstruction was highest at these lower volume hospitals. LEVEL OF EVIDENCE: Level III.

Chronic hyperglycemia, hypercholesterolemia, and metabolic syndrome are associated with risk of tendon injury.

Tendon injury is a considerable problem affecting both physically active and sedentary people. The aim of this study was to examine the relationship between markers for metabolic disorders (hyperglycemia, hypercholesterolemia, and metabolic syndrome) and the risk of developing tendon injuries requiring referral to a hospital. The Copenhagen City Heart Study is a prospective study of diabetic and non-diabetic individuals from the Danish general population with different physical activity levels. The cohort was followed for 3 years via national registers with respect to tendon injuries. Data from 5856 individuals (median age 62 years) were included. The overall incidence of tendon injury in both upper and lower extremities that required an out-patient or in-house visit to a hospital was ~5.7/1000 person years. Individuals with elevated HbA1c (glycated hemoglobin) even in the prediabetic range (HbA1c>5.7%) had a ~3 times higher risk of tendon injury in the lower extremities only, as compared to individuals with normal HbA1C levels. Hypercholesterolemia (total cholesterol>5 mmol/L) increased risk of tendon injury in the upper extremities by ~1.5 times, and individuals with metabolic syndrome had ~2.5 times higher risk of tendon injury in both upper and lower extremities. In conclusion, these data demonstrate for the first time in a large cohort with different physical activity levels that the indicators for metabolic syndrome are a powerful systemic determinant of tendon injury, and two of its components, hyperglycemia and hypercholesterolemia, each independently make tendons susceptible for damage and injury.

How to translate and locally adapt a PROM. Assessment of cross-cultural differential item functioning.

Translating patient-reported outcome measures (PROMs) can alter the meaning of items and undermine the PROM's psychometric properties (quantified as cross-cultural differential item functioning [DIF]). The aim of this paper was to present the theoretical background for PROM translation, adaptation, and cross-cultural validation, and assess how PROMs used in sports medicine research have been translated and adapted. We also assessed DIF for the Knee Injury and Osteoarthritis Outcome Score (KOOS) across Danish, Norwegian, and Swedish versions. We conducted a search in PubMed and Scopus to identify the method of translation, adaptation, and validation of PROMs relevant to musculoskeletal research. Additionally, 150 preoperative KOOS questionnaires were obtained from the Scandinavian knee ligament reconstruction registries, and cross-cultural DIF was evaluated using confirmatory factor analysis and Rasch analysis. There were 392 studies identified, describing the translation of 61 PROMs. Ninety-four percent were performed with forward-backward technique. Forty-nine percent used cognitive interviews to ensure appropriate wording, understandability, and adaptation to the target culture. Only two percent were validated according to modern test theory. No study assessed cross-cultural DIF. One KOOS subscale showed no cross-cultural DIF, two had DIF with respect to some (but not all) items, and thus conversion tables could be constructed, and two KOOS subscales could not be pooled. Most PROM translations are of undocumented quality, despite the common conclusion that they are valid and reliable. Scores from three of five KOOS subscales can be pooled across the Danish, Norwegian, and Swedish versions, but two of these must be adjusted for DIF.

Norwegican Cartilage Project - a study protocol for a double-blinded randomized controlled trial comparing arthroscopic microfracture with arthroscopic debridement in focal cartilage defects in the knee.

BACKGROUND: Focal lesions to the articular cartilage in the knee might have demolishing consequences to the knee. There exists a wide range of possible surgical procedures targeting these injuries, however no significant differences have been found between these procedures. This may support that the improvement is a result of rehabilitation, and not the surgery itself. Arthroscopic microfracture (MF) treatment has gained popularity, and has become the treatment of choice in patients with knee cartilage defects globally. In this study we want to increase knowledge, both clinical and economic, about arthroscopic microfracture (AF) compared to arthroscopic debridement (AD) and physical rehabilitation both in the short run, and in the long run. METHODS/DESIGN: To compare arthroscopic microfracture with arthroscopic debridement and physiotherapy for the treatment of focal cartilage lesions in the knee, a long-term, double-blinded, randomized controlled multicenter trial will be conducted. A total of 114 men and non-pregnant women with a symptomatic focal full thickness cartilage lesion in the knee less than 2 cm2 will be included in the study. The two treatment allocations will receive identical rehabilitation, which is made up of 3 phases: accommodation, rehabilitation and return to activity. Follow up is 24 months, where all will be invited to participate in late follow ups after 5 and 10 years. The Knee Injury and Osteoarthritis Outcome Score (KOOS) knee-related quality of life (QoL) subscore is the primary endpoint. Clinical parameters, questionnaires and radiologic modalities (Magnetic Resonance Imaging (MRI) and x-ray) will be used as secondary endpoints. DISCUSSION: This is an ongoing multicenter study with a high level of evidence to compare arthroscopic microfracture with arthroscopic debridement and physiotherapy for the treatment of isolated symptomatic full thickness cartilage lesions in the knee joint. TRIAL REGISTRATION: ClinicalTrials.gov ID: NCT02637505 (December 15, 2015).

Mechanical properties of the patellar tendon in elite volleyball players with and without patellar tendinopathy.

BACKGROUND: Although differences in mechanical properties between symptomatic and healthy tendons have been observed for the Achilles tendon, the impact of tendinopathy on patellar tendon mechanics is not fully documented. The aim of the present case-control study was to assess the mechanical properties of the tendon and jump performance in elite athletes with and without patellar tendinopathy. METHODS: We identified 17 male volleyball players with patellar tendinopathy and 18 healthy matched controls from a 5-year prospective cohort study on junior elite volleyball players. Outcome variables included three measures of maximal vertical jump performance and ultrasound-based assessments of patellar tendon cross-sectional area, stiffness and Young's modulus. RESULTS: The proximal cross-sectional area of the patellar tendon was significantly larger in the tendinopathic group (133 ± 11 vs 112 ± 9 mm(2), respectively; p < 0.001). Pathological tendons presented lower stiffness (2254 ± 280 vs 2826 ± 603 N/mm, respectively; p = 0.006) and Young's modulus (0.99 ± 0.16 vs 1.17 ± 0.25 GPa, respectively; p = 0.04) than healthy tendons. However, the difference between the countermovement jump height and the squat jump height (3.4 ± 2.2 vs 1.2 ± 1.5 cm, p = 0.005) was significantly higher in the tendinopathic group compared with the control group. CONCLUSIONS: Patellar tendinopathy is associated with a decrease in the mechanical and material properties of the tendon in elite athletes subjected to a high volume of jumping activity. However, compared with their healthy counterparts, tendinopathic volleyball players have a better ability to utilise the stretch-shortening cycle when jumping.

Jumper's knee paradox--jumping ability is a risk factor for developing jumper's knee: a 5-year prospective study.

BACKGROUND: The 'jumper's knee paradox', where symptomatic athletes appear to perform better in a counter movement jump (CMJ) compared to asymptomatic controls in previous case-control studies is not fully understood. AIM: The aim was to examine the relationship between jumping ability and change of jumping ability as potential risk factors for developing jumper's knee. METHODS: A 5-year prospective cohort study among elite volleyball players, aged 16-18. Jump tests were done on a portable force plate at the time of inclusion and semiannually. Jumper's knee was diagnosed based on a standardised clinical examination. RESULTS: All 150 students (68 males and 82 females) were included and 28 developed jumper's knee (22 males and 6 females). At the time of inclusion, male athletes who went on to develop jumper's knee had significantly better results in CMJ (38.0±5.8 cm) compared to asymptomatic males (34.6±5.5 cm, p=0.03), while no difference was detected in standing jump (SJ: jumper's knee: 30.3±7.4 cm, asymptomatic: 28.1±6.1 cm, p=0.23). In a multivariate logistic regression analysis corrected for gender and previous volleyball training, the OR was 2.09 (1.03-4.25) per cm difference in CMJ at the time of inclusion. Our results did not reveal any significant differences in the change in jumping ability between the groups, although both groups improved their jump performance. CONCLUSIONS: Volleyball players with a natural ability for jumping high are at an increased risk for developing jumper's knee.

The evolution of eccentric training as treatment for patellar tendinopathy (jumper's knee): a critical review of exercise programmes.

BACKGROUND AND AIM: Eccentric training has become a popular treatment for patellar tendinopathy. Our purpose was to review the evolution of eccentric strength training programmes for patellar tendinopathy with a focus on the exercise prescriptions used, to help clinicians make appropriate choices and identify areas needing further research. METHODS: A computerised search of the entire MEDLINE database was performed on 1 September 2006 to identify prospective and randomised clinical trials with a focus on clinical outcome of eccentric training for patellar tendinopathy. RESULTS: 7 articles with a total of 162 patients and in which eccentric training was one of the interventions, all published after 2000, were included. The results were positive, but study quality was variable, with small numbers or short follow-up periods. The content of the different training programmes varied, but most were home-based programmes with twice daily training for 12 weeks. A number of potentially significant differences were identified in the eccentric programmes used: drop squats or slow eccentric movement, squatting on a decline board or level ground, exercising into tendon pain or short of pain, loading the eccentric phase only or both phases, and progressing with speed then loading or simply loading. CONCLUSION: Most studies suggest that eccentric training may have a positive effect, but our ability to recommend a specific protocol is limited. The studies available indicate that the treatment programme should include a decline board and should be performed with some level of discomfort, and that athletes should be removed from sports activity. However, these aspects need further study.

No effect of eccentric training on jumper's knee in volleyball players during the competitive season: a randomized clinical trial.

BACKGROUND: The effect of surgery on patellar tendinopathy (jumper's knee) is questionable, and conservative treatment protocols have not been properly documented. PURPOSE: : The aim of this study was to investigate the effect of a newly developed eccentric training program for patellar tendinopathy in volleyball players during the competitive season. STUDY DESIGN: Randomized clinical trial. METHODS: Patients were recruited from male and female elite volleyball teams in Norway, and the diagnosis was based on clinical examination alone. Of 51 players diagnosed with patellar tendinopathy, 29 could be included in the study. The training group (n = 13) performed squats on a 25 degrees decline board as a home exercise program (3 x 15 repetitions twice daily) for a 12-week intervention period during the final half of the competitive season. The eccentric (downward) component was done on the affected leg. The control group (n = 16) trained as usual. The primary outcome was a symptom-based questionnaire developed specifically for patellar tendinopathy (Victorian Institute of Sport Assessment score), and patients were followed up before and after the intervention period, as well as after 6 and 30 weeks. All subjects self-recorded training to document their activity level (eccentric training, volleyball training, matches, other training). RESULTS: There was no change in Victorian Institute of Sport Assessment score during the intervention period in the training (pre, 71.1 +/- 11.3; post, 70.2 +/- 15.4) or control group (pre, 76.4 +/- 12.1; post, 75.4 +/- 16.7), nor was there any change during the follow-up period at 6 weeks or 6 months. The training group completed 8.2 +/- 4.6 weekly sessions of eccentric training during the intervention period (59% of the recommended volume), and there was no difference between groups in training or competition load. CONCLUSION: There was no effect on knee function from a 12-week program with eccentric training among a group of volleyball players with patellar tendinopathy who continued to train and compete during the treatment period. Whether the training would be effective if the patients did not participate in sports activity is not known.