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Identification of Risk Factors Prospectively Associated With Musculoskeletal Injury in a Warrior Athlete Population.
Teyhen, Deydre S; Shaffer, Scott W; Goffar, Stephen L; Kiesel, Kyle; Butler, Robert J; Rhon, Daniel I; Plisky, Phillip J.
Afiliación
  • Teyhen DS; Walter Reed Army Institute of Research (WRAIR), Silver Spring, Maryland.
  • Shaffer SW; Department of Physical Therapy, Texas State University, Round Rock, Texas.
  • Goffar SL; School of Physical Therapy, University of the Incarnate Word, San Antonio, Texas.
  • Kiesel K; Department of Physical Therapy, University of Evansville, Evansville, Indiana.
  • Butler RJ; St Louis Cardinals, St Louis, Missouri.
  • Rhon DI; Doctoral Physical Therapy Programs (DPT and DSc), Baylor University, JBSA Fort Sam Houston, Texas.
  • Plisky PJ; Department of Physical Therapy, University of Evansville, Evansville, Indiana.
Sports Health ; 12(6): 564-572, 2020.
Article en En | MEDLINE | ID: mdl-32134698
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/m2) 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 R2 = 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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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Personal Militar / Sistema Musculoesquelético Tipo de estudio: Diagnostic_studies / Etiology_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Límite: Adult / Humans Idioma: En Revista: Sports Health Año: 2020 Tipo del documento: Article Pais de publicación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Personal Militar / Sistema Musculoesquelético Tipo de estudio: Diagnostic_studies / Etiology_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Límite: Adult / Humans Idioma: En Revista: Sports Health Año: 2020 Tipo del documento: Article Pais de publicación: Estados Unidos