Automated Landing Error Scoring System Performance and the Risk of Bone Stress Injury in Military Trainees

Abstract

Context: Lower extremity bone stress injuries (BSI) place a significant burden on the health and readiness of the US Armed Forces. Objective: To determine if pre-injury baseline performance on an expanded and automated 22-item version of the Landing Error Scoring System (LESS-22) is associated with the incidence of BSI in a military training population. Design: Prospective cohort study. Setting: US Military Academy at West Point Participants: 2,235 (510 females, 22.8%) incoming cadets Main outcome measures: Multivariable Poisson regression models were used to produce adjusted incidence rate ratios (IRR) to quantify the association between pre-injury LESS scores and BSI incidence rate during follow-up, adjusted for pertinent risk factors. Risk factors were included as covariates in the final model if the 95% confidence interval (95% CI) for the crude IRR did not contain 1.00. Results: A total of 54 BSI occurred during the study period, resulting in an overall incidence rate of 0.07 BSI per 1,000 person-days (95% CI: 0.05, 0.09). The mean number of exposure days was 345.4 (SD 61.12, range 3–368). The final model was adjusted for sex and BMI and yielded an adjusted IRR for LESS-22 score of 1.06 (95% CI: 1.002, 1.13; p=0.04), indicating that each additional LESS error documented at baseline was associated with a 6.0% increase in the incidence rate of BSI during the follow-up period. In addition, six individual LESS-22 items, including two newly added items, were significantly associated with BSI incidence. Conclusions: This study provides evidence that performance on the expanded and automated version of the LESS is associated with BSI incidence in a military training population. These results suggest that the automated LESS-22 may be a scalable solution for screening military training populations for BSI risk.

Identifying special operative trainees at-risk for musculoskeletal injury using full body kinematics

“…Over the past decade, a growing interest has developed in the use of biomechanics to evaluate MSKI risk during military training ( Sammito et al, 2021 ). Biomechanical assessments typically include the analysis of an individual’s movement (kinematics) ( Hando et al, 2021 ; Bird et al, 2022 ; Cameron et al, 2022 ; Eckard et al, 2022 ; Bird et al, 2023 ), force transmission through the body (kinetics) ( Bird et al, 2022 ; Hando et al, 2022 ; Bird et al, 2023 ), and/or overall fitness ( Tomes et al, 2020 ). These analyses have been fruitful in discovering biomechanical measures associated with injury.…”

“…However, the few studies to investigate their use for injury risk assessments have yielded mixed results, and it is unclear if these systems provide meaningful information to predict MSKI. For example, Eckard et al and Cameron et al used results from a markerless motion capture system to compute the Landing Error Scoring System (LESS) and found a significant association between individual subjects’ jumping/landing characteristics and lower limb bone stress injury ( Cameron et al, 2022 ; Eckard et al, 2022 ). While promising, the association was most meaningful among female trainees and may not be strong enough to make actionable decisions for both males and females ( Eckard et al, 2022 ).…”

“…For example, Eckard et al and Cameron et al used results from a markerless motion capture system to compute the Landing Error Scoring System (LESS) and found a significant association between individual subjects’ jumping/landing characteristics and lower limb bone stress injury ( Cameron et al, 2022 ; Eckard et al, 2022 ). While promising, the association was most meaningful among female trainees and may not be strong enough to make actionable decisions for both males and females ( Eckard et al, 2022 ). Moreover, the findings were only applicable to a small percentage of participants who landed in a very particular way ( Cameron et al, 2022 ).…”

“…We believe the application of markerless motion capture and the subsequent analyses of the kinematics obtained from such systems have greater potential to identify MSKI risk than these prior studies suggest. The majority of studies, including those cited earlier, use univariate measures that are decided upon a priori and researchers must subjectively choose what may or may not be predictive of injury ( Chorba et al, 2010 ; Lisman et al, 2013 ; Sefton et al, 2016 ; Markström et al, 2019 ; Sammito et al, 2021 ; Bird et al, 2022 ; Cameron et al, 2022 ; Eckard et al, 2022 ; Hando et al, 2022 ). Individuals perform specific movements through unique, coordinated patterns of time-dependent joint motions that cannot be adequately described with univariate measures (or even a collection of univariate measures).…”