Background Proximal stability has been proposed as a contributor to athletic knee injuries. However, it is unclear if this is supported by current evidence.
Objective Examine the association between proximal stability and future athletic knee injuries
Design Systematic review, meta-analysis and best-evidence synthesis.
Setting Amateur to elite athletic settings.
Patients (or Participants) Healthy athletic populations participating in any sport, performing arts, military or physical education teacher education settings with no restriction on sex, age, or level of competition.
Interventions (or Assessment of Risk Factors) Six electronic databases were searched (April 2019) for original research articles. Prospective cohort studies investigating at least one proximal stability variable (lumbopelvic-hip strength, endurance, biomechanics, control, proprioception) for knee injuries in athletic populations were included. Quality of studies was assessed using the Quality in Prognostic Studies (QUIPS) tool.
Main Outcome Measurements Odds ratio effect measures of association between proximal stability variables and future knee injuries. Data not suitable for meta-analysis were synthesized in a best-evidence synthesis.
Results Twenty-one studies met the inclusion criteria, with a high risk of bias found in six studies. Meta-analysis revealed that stronger hip extension and external rotation strength were associated with 34% (OR 0.66, 95% CI 0.45–0.96, p<0.05) and 32% (OR 0.68, 95% CI: 0.53, 0.86, p < 0.05) decreased odds of future knee injuries, respectively. Results of best-evidence synthesis found that 10 of 15 proximal stability variables were not associated with future knee injuries.
Conclusions Hip extension and external rotation strength are the strongest predictors of future knee injuries. The majority of proximal stability variables included in this review were not associated with knee injuries. This review was limited by heterogeneity of measurement methods, making categorizing them difficult. Future studies should consider larger sample sizes to ensure adequate power, and the use of multivariable and complex systems approaches to account for the multifactorial nature of athletic injuries.
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