On a Trajectory for Success—9 in Every 10 People With a Degenerative Meniscus Tear Have Improved Knee Function Within 2 Years After Treatment: A Secondary Exploratory Analysis of a Randomized Controlled Trial

Berg, Bjørnar; Roos, Ewa M.; Kise, Nina Jullum; Engebretsen, Lars; Holm, Inger; Risberg, May Arna

doi:10.2519/jospt.2021.10025

Cited by 13 publications

(9 citation statements)

References 46 publications

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“…Recently, the feasibility of artificial intelligence-based meniscus tear detection on MRI images has been confirmed [ 1 , 2 , 23 , 24 ]. However, to date, there are few artificial intelligence training software algorithms that can successfully and comprehensively evaluate the complete cross-sectional imaging research in musculoskeletal radiology.…”

Section: Discussionmentioning

confidence: 99%

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Feasibility of Constructing an Automatic Meniscus Injury Detection Model Based on Dual-Mode Magnetic Resonance Imaging (MRI) Radiomics of the Knee Joint

Wang

Huang

et al. 2022

Computational and Mathematical Methods in Medicine

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Objective. To explore the feasibility of automatically detecting the degree of meniscus injury by radiomics fusion of dual-mode magnetic resonance imaging (MRI) features of sagittal and coronal planes of the knee joint. Methods. This retrospective study included 164 arthroscopically confirmed meniscus injuries in 152 patients admitted to the Department of Orthopaedics of our hospital from July 2018 to March 2021. A total of 1316-dimensional radiomics signatures were extracted from single-mode sagittal and coronal plane images of menisci, respectively. Then, the sagittal and coronal plane features were fused to form a dual-mode joint feature group with a total of 2632-dimensional radiomics signatures. The minimum redundancy maximum relevance (mRMR) algorithm and the least absolute shrinkage and selection operator (LASSO) regression were used to select features and generate optimal radiomics signatures. The single-mode sagittal plane feature model (Model 1), single-mode coronal plane feature model (Model 2), and the combined sagittal and coronal plane feature model (Model 3) performance were tested by receiver operating characteristic (ROC) curves and Delong test. The calibration curve test was used to verify the reliability of radiomics signatures of the three models. Results. The average intra- and interobserver intraclass correlation coefficients (ICCs) of the most significant 8-dimensional radiomics signatures of Model 1 and Model 2 were 0.935 (range 0.832-0.998) and 0.928 (range 0.845-0.998), respectively. All the three models had good detection performance; Model 3 had the most significant performance (the areas under the curve (AUCs) of training, and validation sets were 0.947 and 0.923, respectively), which was superior to Model 1 (AUCs of training set and validation set were 0.889 and 0.876, respectively) and Model 2 (AUCs of training set and validation set were 0.831 and 0.851, respectively). The detection probability of training and validation sets in the three models was highly consistent with the actual clinical probability. Conclusions. It is feasible to establish a model for automatic detection of meniscus damage by means of radiomics. The detection performance of the dual-mode knee MRI model is better than that of any single-mode model, showing potent feature analysis ability and outstanding detection performance.

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Section: Discussionmentioning

confidence: 99%

“…Meniscus injury is the most common type of knee injury, which can be divided into meniscus tear and meniscus degeneration [ 1 , 2 ]. The treatment of meniscus injury varies, depending on the degree of injury.…”

Section: Introductionmentioning

confidence: 99%

Feasibility of Constructing an Automatic Meniscus Injury Detection Model Based on Dual-Mode Magnetic Resonance Imaging (MRI) Radiomics of the Knee Joint

Wang

Huang

et al. 2022

Computational and Mathematical Methods in Medicine

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“…We found that participants who reported regular physical activity at baseline had a lower risk of poor HRQoL and physical function trajectories, suggesting a protective effect on the symptoms and structural progression of OA (40). Maintaining regular physical activity is one of the core recommended interventions for HKOA (41) and most people follow improvement trajectories in physical function after physical activity programs (29,42). Therefore, we hypothesize that speci c, personalized, and supportive interventions that consider modi able risks factors for poor trajectories, such as physical activity, may improve HRQoL and physical function in the long term as well as the pattern of progression of these outcomes.…”

Section: Discussionmentioning

confidence: 74%

Trajectories of physical function and quality of life in people with osteoarthritis: Results from a 10-year population-based cohort

Costa

Lopes

Cruz

et al. 2022

Preprint

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Objective To identify long-term trajectories of physical function and health-related quality of life (HRQoL) among people with hip and/or knee osteoarthritis (HKOA) and the sociodemographic, lifestyle, and clinical factors associated with different trajectories. Methods Participants with HKOA from the EpiDoC study, a 10-year follow-up (2011–2021) population-based cohort, were considered. Sociodemographic, lifestyle, and clinical variables were collected at baseline in a structured interview and clinical appointment. Physical function and HRQoL were evaluated with the Health Assessment Questionnaire (HAQ) and EuroQoL, respectively, at baseline and the three follow-ups. Group-based trajectory modeling identified physical function and HRQoL trajectories. Multinomial logistic regression analyzed the associations between the covariates of interest and trajectory assignment (p < 0.05). Results We included 983 participants with HKOA. We identified three trajectories for each outcome: “consistently low disability” (32.0%), “slightly worsening moderate disability” (47.0%), and “consistently high disability” (21.0%) for physical function; “consistently high HRQoL” (18.3%), “consistently moderate HRQoL” (48.4%) and “consistently low HRQoL” (33.4%) for HRQoL. Age ≥ 75 years, female sex, multimorbidity, and high baseline clinical severity were associated with higher risk of assignment to poorer physical function and HRQoL trajectories. Participants with high education level and with regular physical activity had a lower risk of assignment to a poor trajectory. Unmanageable pain levels increased the risk of assignment to the “consistently moderate HRQoL” trajectory. Conclusion The levels of physical function and HRQoL remained stable over 10 years and highlight the importance of tailored interventions that target individuals’ modifiable risk factors associated with low physical function and HRQoL trajectories.

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“…To our knowledge, this study is the first to explore different trajectories after ACL injury or in a comparable patient group (young active patients with acute knee injuries). Berg et al 3 found trajectories similar to the Low, Moderate, and High trajectories for middle-aged patients with degenerative meniscal tears and no/minimal concomitant knee osteoarthritis.…”

Section: Discussionmentioning

confidence: 89%

“…In other areas of musculoskeletal research, sophisticated statistical methods such as group-based trajectory modeling 30 , 31 have been used to identify homogeneous subgroups or phenotypes that share common trajectories of knee function. 3 , 5 , 18 Identifying such subgroups among patients with ACL injury may improve our understanding of longitudinal differences in responses to injury or surgery and could develop our knowledge about prognosis. This information could help clinicians to better educate patients about expected outcomes and time to recovery.…”

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confidence: 99%

Four Distinct 5-Year Trajectories of Knee Function Emerge in Patients Who Followed the Delaware-Oslo ACL Cohort Treatment Algorithm

et al. 2022

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Background: Impairments and dysfunction vary considerably after anterior cruciate ligament (ACL) injury, and distinct subgroups may exist. Purpose: (1) To identify subgroups of patients with ACL injury who share common trajectories of patient-reported knee function from initial presentation to 5 years after a treatment algorithm where they chose either ACL reconstruction (ACLR) plus rehabilitation or rehabilitation alone. (2) To assess associations with trajectory affiliation. Study Design: Cohort study; Level of evidence, 3. Methods: We included 276 patients with a acute first-time complete unilateral ACL injury. All patients underwent a 5-week neuromuscular and strength training program before a shared decision-making process about treatment. Within their latest attended follow-up, 62% of patients had undergone early ACLR (<6 months after the 5-week program), 11% delayed ACLR (>6 months after the 5-week program), and 27% progressive rehabilitation alone. Patients completed the International Knee Documentation Committee Subjective Knee Form (IKDC-SKF) at inclusion, after the 5-week program, and at 6 months, 1 year, 2 years, and 5 years after ACLR or completion of the 5-week program (patients treated with rehabilitation alone). We used group-based trajectory modeling to identify trajectories of IKDC-SKF and multinomial logistic regression to assess associations with trajectory affiliation. Results: Four distinct trajectories of IKDC-SKF were identified: Low (n = 22; 8.0% of the cohort), Moderate (n = 142; 51.4%), High (n = 105; 38.0%), and High Before Declining (n = 7; 2.5%). The High trajectory had higher scores at inclusion than the Moderate trajectory, but both improved considerably within 1 year and had thereafter stable high scores. The High Before Declining trajectory also started relatively high and improved considerably within 1 year but experienced a large deterioration between 2 and 5 years. The Low trajectory started low and had minimal improvement. New knee injuries were important characteristics of the High Before Declining trajectory, concomitant meniscal injuries were significantly associated with following the Low (vs Moderate) trajectory, and early/preoperative quadriceps strength and hop symmetry (measured at inclusion) were significantly associated with following the High (vs Moderate) trajectory. Conclusion: We identified 4 distinct 5-year trajectories of patient-reported knee function, indicating 4 subgroups of patients with ACL injury. Importantly, 88% of the patients who followed our treatment algorithm followed the Moderate and High trajectories characterized by good improvement and high scores. Due to eligibility criteria and procedures in our cohort, we can only generalize our model to athletes without major concomitant injuries who follow a similar treatment algorithm. Concomitant meniscal injuries and new knee injuries were important factors in the unfavorable Low and High Before Declining trajectories. These associations were exploratory but support the trajectories’ validity. Our findings can contribute to patient education about prognosis and underpin the importance of continued secondary injury prevention.

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On a Trajectory for Success—9 in Every 10 People With a Degenerative Meniscus Tear Have Improved Knee Function Within 2 Years After Treatment: A Secondary Exploratory Analysis of a Randomized Controlled Trial

Cited by 13 publications

References 46 publications

Feasibility of Constructing an Automatic Meniscus Injury Detection Model Based on Dual-Mode Magnetic Resonance Imaging (MRI) Radiomics of the Knee Joint

Feasibility of Constructing an Automatic Meniscus Injury Detection Model Based on Dual-Mode Magnetic Resonance Imaging (MRI) Radiomics of the Knee Joint

Trajectories of physical function and quality of life in people with osteoarthritis: Results from a 10-year population-based cohort

Four Distinct 5-Year Trajectories of Knee Function Emerge in Patients Who Followed the Delaware-Oslo ACL Cohort Treatment Algorithm

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