MONDAY, July 19 (HealthDay News) -- A novel, low-cost, in-office approach can accurately identify female athletes at increased risk of anterior cruciate ligament (ACL) injury, according to a study published online July 1 in the American Journal of Sports Medicine and presented at the annual meeting of the American Orthopaedic Society for Sports Medicine, held from July 15 to 18 in Providence, R.I.

In a prospective cohort laboratory study, Gregory D. Myer, M.D., of the Cincinnati Children's Hospital, and colleagues tested 100 female athletes using laboratory-based measures to confirm the validity of a clinic-based prediction algorithm that was designed to identify which athletes are at higher risk of ACL injury. In addition, another cohort of 20 female athletes was simultaneously tested with both clinic-based and laboratory-based measures to assess selected clinic-based surrogate predictors.

The prediction model that was derived from laboratory-based surrogates included knee valgus motion (odds ratio [OR], 1.59), knee flexion range of motion (OR, 0.94), body mass (OR, 0.98), tibia length (OR, 1.55), and quadriceps to hamstrings ratio (OR, 1.70). The researchers found that the algorithm predicted high knee abduction moment status with 84 percent sensitivity and 67 percent specificity. Clinic-based techniques that used a standard measuring tape, a calibrated physician's scale, ImageJ software (National Institutes of Health public domain), a standard camcorder, and an isokinetic dynamometer were highly correlated with simultaneous laboratory-based measurements.

"Use of the developed clinic-based assessment tool may facilitate high-risk athletes' entry into appropriate interventions that will have greater potential to reduce their injury risk," the authors write.

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