AI Article Synopsis

  • An increase in musculoskeletal injury prediction models in sports medicine necessitates evaluating their quality for effective clinical use.
  • A systematic review identified 30 studies involving 204 models, revealing that most used regression methods and none were externally validated, indicating a high risk of bias in the majority.
  • Current prediction models are inadequately developed and reported, highlighting the urgent need for improved methodology to ensure they can be clinically useful.

Article Abstract

Background: An increasing number of musculoskeletal injury prediction models are being developed and implemented in sports medicine. Prediction model quality needs to be evaluated so clinicians can be informed of their potential usefulness.

Objective: To evaluate the methodological conduct and completeness of reporting of musculoskeletal injury prediction models in sport.

Methods: A systematic review was performed from inception to June 2021. Studies were included if they: (1) predicted sport injury; (2) used regression, machine learning, or deep learning models; (3) were written in English; (4) were peer reviewed.

Results: Thirty studies (204 models) were included; 60% of studies utilized only regression methods, 13% only machine learning, and 27% both regression and machine learning approaches. All studies developed a prediction model and no studies externally validated a prediction model. Two percent of models (7% of studies) were low risk of bias and 98% of models (93% of studies) were high or unclear risk of bias. Three studies (10%) performed an a priori sample size calculation; 14 (47%) performed internal validation. Nineteen studies (63%) reported discrimination and two (7%) reported calibration. Four studies (13%) reported model equations for statistical predictions and no machine learning studies reported code or hyperparameters.

Conclusion: Existing sport musculoskeletal injury prediction models were poorly developed and have a high risk of bias. No models could be recommended for use in practice. The majority of models were developed with small sample sizes, had inadequate assessment of model performance, and were poorly reported. To create clinically useful sports musculoskeletal injury prediction models, considerable improvements in methodology and reporting are urgently required.

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Source
http://dx.doi.org/10.1007/s40279-022-01698-9DOI Listing

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