Literature DB >> 26013150

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

Deydre S Teyhen1, Scott W Shaffer, Robert J Butler, Stephen L Goffar, Kyle B Kiesel, Daniel I Rhon, Jared N Williamson, Phillip J Plisky.   

Abstract

BACKGROUND: 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. QUESTIONS/PURPOSES: 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.
METHODS: 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.
RESULTS: 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.
CONCLUSIONS: 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 OF EVIDENCE: Level II, prognostic study.

Entities:  

Mesh:

Year:  2015        PMID: 26013150      PMCID: PMC4523518          DOI: 10.1007/s11999-015-4342-6

Source DB:  PubMed          Journal:  Clin Orthop Relat Res        ISSN: 0009-921X            Impact factor:   4.176


  42 in total

1.  Disabilities due to injury in the military.

Authors:  T J Songer; R E LaPorte
Journal:  Am J Prev Med       Date:  2000-04       Impact factor: 5.043

2.  Reliability of lower quarter physical performance measures in healthy service members.

Authors:  Deydre S Teyhen; Scott W Shaffer; Chelsea L Lorenson; Samantha L Wood; Shay M Rogers; Jessica L Dugan; Michael J Walker; John D Childs; John C Childs
Journal:  US Army Med Dep J       Date:  2011 Jul-Sep

3.  Risk factors for training-related injuries among men and women in basic combat training.

Authors:  J J Knapik; M A Sharp; M Canham-Chervak; K Hauret; J F Patton; B H Jones
Journal:  Med Sci Sports Exerc       Date:  2001-06       Impact factor: 5.411

4.  A process to identify military injury prevention priorities based on injury type and limited duty days.

Authors:  Bruce A Ruscio; Bruce H Jones; Steven H Bullock; Bruce R Burnham; Michelle Canham-Chervak; Christopher P Rennix; Timothy S Wells; Jack W Smith
Journal:  Am J Prev Med       Date:  2010-01       Impact factor: 5.043

5.  Upper Quarter Y Balance Test: reliability and performance comparison between genders in active adults.

Authors:  Paul P Gorman; Robert J Butler; Phillip J Plisky; Kyle B Kiesel
Journal:  J Strength Cond Res       Date:  2012-11       Impact factor: 3.775

Review 6.  Smoking Predisposes to Rotator Cuff Pathology and Shoulder Dysfunction: A Systematic Review.

Authors:  Julie Y Bishop; Juan E Santiago-Torres; Nathan Rimmke; David C Flanigan
Journal:  Arthroscopy       Date:  2015-03-19       Impact factor: 4.772

7.  Smoking Cessation Related to Improved Patient-Reported Pain Scores Following Spinal Care.

Authors:  Caleb Behrend; Mark Prasarn; Ellen Coyne; MaryBeth Horodyski; John Wright; Glenn R Rechtine
Journal:  J Bone Joint Surg Am       Date:  2012-12-05       Impact factor: 5.284

8.  Strategies for optimizing military physical readiness and preventing musculoskeletal injuries in the 21st century.

Authors:  Bradley C Nindl; Thomas J Williams; Patricia A Deuster; Nikki L Butler; Bruce H Jones
Journal:  US Army Med Dep J       Date:  2013 Oct-Dec

9.  The Functional Movement Screen: a reliability study.

Authors:  Deydre S Teyhen; Scott W Shaffer; Chelsea L Lorenson; Joshua P Halfpap; Dustin F Donofry; Michael J Walker; Jessica L Dugan; John D Childs
Journal:  J Orthop Sports Phys Ther       Date:  2012-05-14       Impact factor: 4.751

10.  Smoking increases risk of pain chronification through shared corticostriatal circuitry.

Authors:  Bogdan Petre; Souraya Torbey; James W Griffith; Gildasio De Oliveira; Kristine Herrmann; Ali Mansour; Alex T Baria; Marwan N Baliki; Thomas J Schnitzer; Apkar Vania Apkarian
Journal:  Hum Brain Mapp       Date:  2014-10-12       Impact factor: 5.038

View more
  20 in total

Review 1.  Reliability and Association with Injury of Movement Screens: A Critical Review.

Authors:  Robert McCunn; Karen Aus der Fünten; Hugh H K Fullagar; Ian McKeown; Tim Meyer
Journal:  Sports Med       Date:  2016-06       Impact factor: 11.136

2.  Physical and Performance Characteristics Related to Unintentional Musculoskeletal Injury in Special Forces Operators: A Prospective Analysis.

Authors:  Nicholas R Heebner; John P Abt; Mita Lovalekar; Kim Beals; Timothy C Sell; Jeffery Morgan; Shawn Kane; Scott Lephart
Journal:  J Athl Train       Date:  2017-12-11       Impact factor: 2.860

3.  Predictive models for musculoskeletal injury risk: why statistical approach makes all the difference.

Authors:  Daniel I Rhon; Deydre S Teyhen; Gary S Collins; Garrett S Bullock
Journal:  BMJ Open Sport Exerc Med       Date:  2022-10-14

4.  Identification of Risk Factors Prospectively Associated With Musculoskeletal Injury in a Warrior Athlete Population.

Authors:  Deydre S Teyhen; Scott W Shaffer; Stephen L Goffar; Kyle Kiesel; Robert J Butler; Daniel I Rhon; Phillip J Plisky
Journal:  Sports Health       Date:  2020-03-05       Impact factor: 3.843

5.  LOWER QUARTER- AND UPPER QUARTER Y BALANCE TESTS AS PREDICTORS OF RUNNING-RELATED INJURIES IN HIGH SCHOOL CROSS-COUNTRY RUNNERS.

Authors:  Natalie J Ruffe; Samantha R Sorce; Michael D Rosenthal; Mitchell J Rauh
Journal:  Int J Sports Phys Ther       Date:  2019-09

6.  THE EFFECT of ONE-ON-ONE INTERVENTION in ATHLETES with MULTIPLE RISK FACTORS for INJURY.

Authors:  Kate Schwartzkopf-Phifer; Robert A English; Carl G Mattacola; Emily V Dressler; Kyle B Kiesel
Journal:  Int J Sports Phys Ther       Date:  2019-06

7.  INJURY IDENTIFICATION: THE EFFICACY OF THE FUNCTIONAL MOVEMENT SCREEN™ IN FEMALE AND MALE RUGBY UNION PLAYERS.

Authors:  Ross Armstrong; Matt Greig
Journal:  Int J Sports Phys Ther       Date:  2018-08

8.  Underreporting of Musculoskeletal Injuries in the US Army: Findings From an Infantry Brigade Combat Team Survey Study.

Authors:  Laurel Smith; Richard Westrick; Sarah Sauers; Adam Cooper; Dennis Scofield; Pedro Claro; Bradley Warr
Journal:  Sports Health       Date:  2016-11       Impact factor: 3.843

9.  Knee problems and its associated factors among active cyclists in Eastern Province, Saudi Arabia.

Authors:  Abdullatif K Althunyan; Magdy A Darwish; Moataza M Abdel Wahab
Journal:  J Family Community Med       Date:  2017 Jan-Apr

10.  VALIDITY OF FUNCTIONAL SCREENING TESTS TO PREDICT LOST-TIME LOWER QUARTER INJURY IN A COHORT OF FEMALE COLLEGIATE ATHLETES.

Authors:  P David Walbright; Nicole Walbright; Heidi Ojha; Todd Davenport
Journal:  Int J Sports Phys Ther       Date:  2017-11
View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.