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What Risk Factors Are Associated With Musculoskeletal Injury in US Army Rangers? A Prospective Prognostic Study

Overview of attention for article published in Clinical Orthopaedics & Related Research, September 2015
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (86th percentile)
  • High Attention Score compared to outputs of the same age and source (90th percentile)

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14 X users
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10 Facebook pages

Citations

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99 Dimensions

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249 Mendeley
Title
What Risk Factors Are Associated With Musculoskeletal Injury in US Army Rangers? A Prospective Prognostic Study
Published in
Clinical Orthopaedics & Related Research, September 2015
DOI 10.1007/s11999-015-4342-6
Pubmed ID
Authors

Deydre S. Teyhen, Scott W. Shaffer, Robert J. Butler, Stephen L. Goffar, Kyle B. Kiesel, Daniel I. Rhon, Jared N. Williamson, Phillip J. Plisky

Abstract

Musculoskeletal injury is the most common reason that soldiers are medically not ready to deploy. Understanding intrinsic risk factors that may place an elite soldier at risk of musculoskeletal injury may be beneficial in preventing musculoskeletal injury and maintaining operational military readiness. Findings from this population may also be useful as hypothesis-generating work for particular civilian settings such as law enforcement officers (SWAT teams), firefighters (smoke jumpers), or others in physically demanding professions. The purposes of this study were (1) to examine whether using baseline measures of self-report and physical performance can identify musculoskeletal injury risk; and (2) to determine whether a combination of predictors would enhance the accuracy for determining future musculoskeletal injury risk in US Army Rangers. Our study was a planned secondary analysis from a prospective cohort examining how baseline factors predict musculoskeletal injury. Baseline predictors associated with musculoskeletal injury were collected using surveys and physical performance measures. Survey data included demographic variables, injury history, and biopsychosocial questions. Physical performance measures included ankle dorsiflexion, Functional Movement Screen, lower and upper quarter Y-balance test, hop testing, pain provocation, and the Army Physical Fitness Test (consisting of a 2-mile run and 2 minutes of sit-ups and push-ups). A total of 320 Rangers were invited to enroll and 211 participated (66%). Occurrence of musculoskeletal injury was tracked for 1 year using monthly injury surveillance surveys, medical record reviews, and a query of the Department of Defense healthcare utilization database. Injury surveillance data were available on 100% of the subjects. Receiver operator characteristic curves and accuracy statistics were calculated to identify predictors of interest. A logistic regression equation was then calculated to find the most pertinent set of predictors. Of the 188 Rangers (age, 23.3 ± 3.7 years; body mass index, 26.0 ± 2.4 kg/m(2)) remaining in the cohort, 85 (45.2%) sustained a musculoskeletal injury of interest. Smoking, prior surgery, recurrent prior musculoskeletal injury, limited-duty days in the prior year for musculoskeletal injury, asymmetrical ankle dorsiflexion, pain with Functional Movement Screen clearing tests, and decreased performance on the 2-mile run and 2-minute sit-up test were associated with increased injury risk. Presenting with one or fewer predictors resulted in a sensitivity of 0.90 (95% confidence interval [CI], 0.83-0.95), and having three or more predictors resulted in a specificity of 0.98 (95% CI, 0.93-0.99). The combined factors that contribute to the final multivariable logistic regression equation yielded an odds ratio of 4.3 (95% CI, 2.0-9.2), relative risk of 1.9 (95% CI, 1.4-2.6), and an area under the curve of 0.64. Multiple factors (musculoskeletal injury history, smoking, pain provocation, movement tests, and lower scores on physical performance measures) were associated with individuals at risk for musculoskeletal injury. The summation of the number of risk factors produced a highly sensitive (one or less factor) and specific (three or more factors) model that could potentially be used to effectively identify and intervene in those persons with elevated risk for musculoskeletal injury. Future research should establish if screening and intervening can improve musculoskeletal health and if our findings among US Army Rangers translate to other occupations or athletes. Level II, prognostic study.

X Demographics

X Demographics

The data shown below were collected from the profiles of 14 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 249 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 3 1%
United States 2 <1%
Canada 1 <1%
Brazil 1 <1%
Unknown 242 97%

Demographic breakdown

Readers by professional status Count As %
Student > Master 37 15%
Student > Ph. D. Student 30 12%
Researcher 26 10%
Student > Bachelor 26 10%
Other 16 6%
Other 47 19%
Unknown 67 27%
Readers by discipline Count As %
Medicine and Dentistry 57 23%
Sports and Recreations 45 18%
Nursing and Health Professions 32 13%
Engineering 10 4%
Social Sciences 4 2%
Other 18 7%
Unknown 83 33%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 13. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 25 May 2017.
All research outputs
#2,828,019
of 25,374,917 outputs
Outputs from Clinical Orthopaedics & Related Research
#488
of 7,298 outputs
Outputs of similar age
#36,069
of 276,789 outputs
Outputs of similar age from Clinical Orthopaedics & Related Research
#11
of 119 outputs
Altmetric has tracked 25,374,917 research outputs across all sources so far. Compared to these this one has done well and is in the 88th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,298 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.8. This one has done particularly well, scoring higher than 93% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 276,789 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 86% of its contemporaries.
We're also able to compare this research output to 119 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 90% of its contemporaries.