Modeling Risk for Lower Extremity Musculoskeletal Injury in U.S. Military Academy Cadet Basic Training

Area of Science:

• Sports Medicine
• Military Health
• Biomechanics

Background:

• Musculoskeletal injuries are prevalent in sport and tactical populations.
• Existing research identifies multiple injury risk variables but lacks a combined, pragmatic model for practical application.
• No studies have evaluated a predetermined combination of risk factors for tactical and sports settings.

Purpose of the Study:

• To develop and validate multivariable risk models for predicting lower extremity musculoskeletal injuries.
• To assess the predictive capability of these models in a cadet basic training population at the U.S. Military Academy.

Main Methods:

• Collected data on sex, injury history, Body Mass Index (BMI), aerobic fitness, movement screening (Landing Error Scoring System), and cadence from cadets.
• Utilized Kaplan-Meier survival curves and Cox regression analysis to identify injury risk factors and compare model performance using Akaike Information Criterion (AIC).

Main Results:

• Identified sex, injury history, Landing Error Scoring System score, and Physical Fitness Test (PT) Run Score as significant predictors of injury risk.
• A model incorporating aerobic fitness and BMI demonstrated superior fit compared to models with movement screening and cadence.
• The most precise model included all significant univariable predictors, indicating a comprehensive approach to risk assessment.

Conclusions:

• Variables such as injury history, BMI, and aerobic fitness, commonly collected in tactical settings, are crucial for risk identification.
• Incorporating kinematic testing (e.g., Landing Error Scoring System) significantly enhances the precision of musculoskeletal injury risk models.
• These findings support the continued use of kinematic testing in screening cadets for elevated injury risk.