title: Field-expedient screening and injury risk algorithm categories as predictors of noncontact lower extremity injury.
abstract: In athletics, efficient screening tools are sought to curb the rising number of noncontact injuries and associated health care costs. The authors hypothesized that an injury prediction algorithm that incorporates movement screening performance, demographic information, and injury history can accurately categorize risk of noncontact lower extremity (LE) injury. One hundred eighty-three collegiate athletes were screened during the preseason. The test scores and demographic information were entered into an injury prediction algorithm that weighted the evidence-based risk factors. Athletes were then prospectively followed for noncontact LE injury. Subsequent analysis collapsed the groupings into two risk categories: Low (normal and slight) and High (moderate and substantial). Using these groups and noncontact LE injuries, relative risk (RR), sensitivity, specificity, and likelihood ratios were calculated. Forty-two subjects sustained a noncontact LE injury over the course of the study. Athletes identified as High Risk (n = 63) were at a greater risk of noncontact LE injury (27/63) during the season [RR: 3.4 95% confidence interval 2.0 to 6.0]. These results suggest that an injury prediction algorithm composed of performance on efficient, low-cost, field-ready tests can help identify individuals at elevated risk of noncontact LE injury.
authors.affiliation: Department of Physical Therapy, Lebanon Valley College, Annville, PA 17003-1400, USA. mlehr@lvc.edu
authors.forename: M E
authors.initials: ME
authors.lastname: Lehr
authors.forename: P J
authors.initials: PJ
authors.lastname: Plisky
authors.forename: R J
authors.initials: RJ
authors.lastname: Butler
authors.forename: M L
authors.initials: ML
authors.lastname: Fink
authors.forename: K B
authors.initials: KB
authors.lastname: Kiesel
authors.forename: F B
authors.initials: FB
authors.lastname: Underwood
mesh_terms: D000293:Adolescent; D000465:Algorithms; D016512:Ankle Injuries / Q000517:prevention & control; D000070598:Anterior Cruciate Ligament Injuries; D001265:Athletic Injuries / Q000517:prevention & control*; D015331:Cohort Studies; D005260:Female; D006801:Humans; D007718:Knee Injuries / Q000517:prevention & control; D007869:Leg Injuries / Q000517:prevention & control*; D016013:Likelihood Functions; D008297:Male; D011446:Prospective Studies; D012306:Risk; D018570:Risk Assessment / Q000379:methods*; D013180:Sprains and Strains / Q000517:prevention & control*; D055815:Young Adult
keywords: injury prevention; neuromuscular; pre-participation screening; sports injuries; sports medicine