Prognostic factors for specific lower extremity and spinal musculoskeletal injuries identified through medical screening and training load monitoring in professional football (soccer): a systematic review

Abstract

BackgroundMedical screening and load monitoring procedures are commonly used in professional football to assess factors perceived to be associated with injury.ObjectivesTo identify prognostic factors (PFs) and models for lower extremity and spinal musculoskeletal injuries in professional/elite football players from medical screening and training load monitoring processes.MethodsThe MEDLINE, AMED, EMBASE, CINAHL Plus, SPORTDiscus and PubMed electronic bibliographic databases were searched (from inception to January 2017). Prospective and retrospective cohort studies of lower extremity and spinal musculoskeletal injury incidence in professional/elite football players aged between 16 and 40 years were included. The Quality in Prognostic Studies appraisal tool and the modified Grading of Recommendations Assessment, Development and Evaluation synthesis approach was used to assess the quality of the evidence.ResultsFourteen studies were included. 16 specific lower extremity injury outcomes were identified. No spinal injury outcomes were identified. Meta-analysis was not possible due to heterogeneity and study quality. All evidence related to PFs and specific lower extremity injury outcomes was of very low to low quality. On the few occasions where multiple studies could be used to compare PFs and outcomes, only two factors demonstrated consensus. A history of previous hamstring injuries (HSI) and increasing age may be prognostic for future HSI in male players.ConclusionsThe assumed ability of medical screening tests to predict specific musculoskeletal injuries is not supported by the current evidence. Screening procedures should currently be considered as benchmarks of function or performance only. The prognostic value of load monitoring modalities is unknown.

Pre-season screening currently has no value for injury prediction: The development and internal validation of a multivariable prognostic model to predict indirect muscle injury risk in elite football (soccer) players

“…The dataset contained 60 candidate factors [20]. Because of the sample size considerations, before any analysis, the set of candidates was reduced based upon data quality and reliability assessment, previous evidence of prognostic value [19] and clinical reasoning [20]. This process left a final set of 10 candidate factors, represented by 12 model parameters (Table 1).…”

“…Such models could be used to identify high-risk individuals who may require an intervention that is designed to reduce risk [17], thus assisting clinical decision making [18]. Despite the potential benefits of prognostic models for injury, we are unaware of any that have been developed using PHE data in elite football [19].…”

Periodic Health Examination and Injury Prediction in Professional Football (Soccer): Theoretically, the Prognosis is Good

“…Some factors may have a strong or weak influence on the risk of injury [ 17 ] and the relative influence of each is dynamic, often changing over time [ 13 ]. To confirm factors as causal (such as those investigated during PHE), a body of high quality evidence is required [ 12 ], but this is currently lacking for injuries specifically in professional football [ 18 , 19 ] and is of variable quality in other sports [ 20 – 27 ]. Studies that investigate causal factors should provide detailed methodology and design, explicit definitions and measurement criteria for causal factors, confounding factors and pathological outcomes.…”

“…We prefer the PROGRESS definition for outcomes in sports medicine, as it reflects that importantly, both causal and non-causal factors can be a PF, as long as they provide information that contributes toward outcome prediction [ 14 ]. Again, this is also more reflective of PHE in professional football, as there are no clear causal links between PHE assessment and injuries [ 18 ]. One of the objectives of prognosis research is to combine several PFs within a multivariable prognostic (or prediction) model to determine the absolute risk of an injury for an individual [ 14 , 38 ].…”

Studying the Predictive Power of Common FIFA Pre-Season Medical Assessments and Functional Tests With the Rate and Severity of Injuries to Elite Football Players

“…According to Fuller et al players with cardiovascular, neurological and musculoskeletal risk factors are more likely to be injured and affected by intense exercise [10]. Hughes et al in a systematic review, concluded that medical screening tests of professional football players are defective in predicting and preventing injuries [11].…”