ArticleBMJ open sport & exercise medicine2022
Predictive models for musculoskeletal injury risk: why statistical approach makes all the difference.
Article in BMJ open sport & exercise medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed.
- Key determinants for lowering the risk of joint replacement in weight-bearing joints: a population-based cohort study.Arthroplasty (London, England) · 2026Article
- Sit-to-Stand Navicular Drop Test-Based Injury Risk Zones Derived from a U-Shaped Relationship in Male University Athletes.Journal of clinical medicine · 2026Article
- External validation of three risk prediction models for deep vein thrombosis in patients with acute stroke: a single-center cohort study.Frontiers in cardiovascular medicine · 2026Article
- Risk prediction models for venous thromboembolism in stroke: a systematic review and meta-analysis.Frontiers in cardiovascular medicine · 2026Review
- Identifying contributory risk factors for neck pain in fast jet aircrew: a prospective cohort study.International archives of occupational and environmental health · 2025Article
- Model for Musculoskeletal Injury Risk Factors Among US Army Basic Combat Trainees.JAMA network open · 2025Article
- Multi modal fusion of medical imaging and biomechanical data using attention based swin-unet and LSTM for sports injury prediction.Frontiers in physiology · 2025Article
- Developing clinical prediction models: a step-by-step guide.BMJ (Clinical research ed.) · 2024Article
- Limitations of Separating Athletes into High or Low-Risk Groups based on a Cut-Off. A Clinical Commentary.International journal of sports physical therapy · 2024Article
- A machine learning framework to classify musculoskeletal injury risk groups in military service members.Frontiers in artificial intelligence · 2024Article
- Musculoskeletal Injury Risk Stratification: A Traffic Light System for Military Service Members.Healthcare (Basel, Switzerland) · 2023Article
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objective: Compare performance between an injury prediction model categorising predictors and one that did not and compare a selection of predictors based on univariate significance versus assessing non-linear relationships. Methods: Validation and replication of a previously developed injury prediction model in a cohort of 1466 service members followed for 1 year after physical performance, medical history and sociodemographic variables were collected. The original model dichotomised 11 predictors. The second model (M2) kept predictors continuous but assumed linearity and the third model (M3) conducted non-linear transformations. The fourth model (M4) chose predictors the proper way (clinical reasoning and supporting evidence). Model performance was assessed with R Results: 478 personnel sustained an injury. The original model demonstrated poorer R Conclusion: Model performance was substantially worse in the models with dichotomised variables. This highlights the need to follow established recommendations when developing prediction models.
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