Sports Health A Multidisciplinary Approach · 2020 · 82 citations · 45 references
Public HealthInjury PreventionSports MedicineInjury SurveillanceMusculoskeletal MedicineSports Injury PreventionInjury EpidemiologyInjury RiskInjury Risk ReductionMusculoskeletal HealthMusculoskeletal InjuriesSports InjuriesInjury Risk AssessmentInjury Risk ScreeningLogistic RegressionMultifactorial RiskMusculoskeletal Risk AssessmentRisk Factor IdentificationSports Injury EpidemiologySports Injury Risk
Background: Musculoskeletal injuries are a primary source of disability. Understanding how risk factors predict injury is necessary to individualize and enhance injury reduction programs. Hypothesis: Because of the multifactorial nature of musculoskeletal injuries, multiple risk factors will provide a useful method of categorizing warrior athletes based on injury risk. Study Design: Prospective observational cohort study. Level of Evidence: Level 2. Methods: Baseline data were collected on 922 US Army soldiers/warrior athletes (mean age, 24.7 ± 5.2 years; mean body mass index, 26.8 ± 3.4 kg/m 2 ) using surveys and physical measures. Injury occurrence and health care utilization were collected for 1 year. Variables were compared in healthy versus injured participants using independent t tests or chi-square analysis. Significantly different factors between each group were entered into a logistic regression equation. Receiver operating characteristic curve and accuracy statistics were calculated for regression variables. Results: Of the 922 warrior athletes, 38.8% suffered a time-loss injury (TLI). Overall, 35 variables had a significant relationship with TLIs. The logistic regression equation, consisting of 11 variables of interest, was significant (adjusted R 2 = 0.21; odds ratio, 5.7 [95% CI, 4.1-7.9]; relative risk, 2.5 [95% CI, 2.1-2.9]; area under the curve, 0.73). Individuals with 2 variables had a sensitivity of 0.89, those with 7 or more variables had a specificity of 0.94. Conclusion: The sum of individual risk factors (prior injury, prior work restrictions, lower perceived recovery from injury, asymmetrical ankle dorsiflexion, decreased or asymmetrical performance on the Lower and Upper Quarter Y-Balance test, pain with movement, slower 2-mile run times, age, and sex) produced a highly sensitive and specific multivariate model for TLI in military servicemembers. Clinical Relevance: A better understanding of characteristics associated with future injury risk can provide a foundation for prevention programs designed to reduce medical costs and time lost.
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Kurt Kroenke, Robert L. Spitzer, Janet B. W. Williams · Journal of General Internal Medicine · 2001 · 44.2K citations · Full text
Index for rating diagnostic tests
W. J. Youden · Cancer · 1950 · 11.5K citations · Full text
Education, Educational Assessment, Educational Measurement +11