- ICH GCP
- US Clinical Trials Registry
- Clinical Trial NCT02776930
Predictive Models for Spine and Lower Extremity Injury After Discharge From Rehab (MP3-RD)
Development of Predictive Models for Lower Extremity, Lumbar, and Thoracic Injury After Discharge From Physical Rehabilitation
The purpose of this study is to develop algorithms that will help predict future injury and/or re-injury after being returned to duty from a musculoskeletal injury. After completion of an episode of care with a physical therapist, the subjects will undergo a battery of physical performance tests and fill out associated surveys. The subjects will then be followed for a year to identify the occurrence/re-occurence of any injuries. Based on the performance on the physical evaluation tests, algorithms will be derived using regression analysis to predict injury.
Subjects will be recruited from the pool of patients that have recently completed physical rehabilitation in physical therapy clinics for their lower extremity or lumbar/thoracic spine injury.
Study Overview
Status
Conditions
Detailed Description
Subjects will be recruited across 4 medical centers after having completed a regimen of physical therapy for a spine or lower extremity injury. Upon discharge back to full duty, they will be given the opportunity to enroll in the study and undergo a battery of physical performance tests and associated surveys. The subjects will then be followed for a year to identify the occurrence of any injuries. Prediction algorithms will be derived using regression analysis to predict injury based on performance on the physical evaluation tests.
The overall hypothesis is that Service Member performance on a battery of physical performance tests performed upon discharge from care and return to duty, will be able to predict 1) the risk of sustaining any injury as well as 2) reoccurrence of the same injury that they were seeking care for during the year following discharge from rehabilitation. The current assumption is that when a Service Member is discharged from medical care, it has been done based on the expectation that it is appropriate and safe for them to return to function in their operational environment. Because history of prior injury is a well-established risk factor, every single Service Member that is returned to duty after medical care for a musculoskeletal (MSK) injury is already at a higher risk for future injury than his or her non-injured counterpart. The investigators hypothesize that decreased performance on the proposed testing protocol will be related to increase in the risk of 1 year-injury and recurrence of injury. Successfully identifying those at increased risk of recurrence provides the ability for secondary and tertiary prevention programs to optimize return to duty rates. Injury will be defined as any new musculoskeletal injury or the re-occurrence of the same injury during the 1-year surveillance period.
The battery of physical performance tests will include: Selective Functional Movement Assessment (SFMA), Functional Movement Screen (FMS), Upper Quarter Y-balance Test (YBT-UQ), Lower Quarter Y-balance Test (YBT-LQ), Closed Kinetic Chain Dorsiflexion (CKC DF), a Single Hop Test, Triple Hop Test, Triple Crossover Hop Test, Carry Test, and a un-weighted and weighted 300 yard Shuttle Run Test.
Each subject will then also be contacted monthly via a SMS (Short Message Service, e.g. text message) survey for the following year to identify information about additional injury or profile that they may have sustained during the prior period of time. Information about injury will also be calculated from patient chart reviews and Department of Defense healthcare utilization database (claims data). This will provide a robust method in which to capture data injury data regardless of subject availability for follow-up.
Subjects will be dichotomized as injured or non-injured based on the injury surveillance data. Key demographic, physical performance (FMS, YBT, SFMA, Hop Test, Carry test, & Shuttle Run), and self-report measures will be examined for group differences. Potential predictor variables will be entered into a backward stepwise logistic regression model to determine the most accurate set of variables predictive of musculoskeletal injury status.
Risk stratification (low, moderate, or high) will be based on likelihood ratios (LR) associated with the clinical prediction rule for injury outlined above. A positive LR > 10 will place the individual as high risk, a LR between 2 and 10 would place the individual as moderate risk. Those with a positive LR less than 2 will be listed as low risk.
Study Type
Enrollment (Actual)
Contacts and Locations
Study Locations
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North Carolina
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Fort Bragg, North Carolina, United States, 28307
- Womack Army Medical Center
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Texas
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Fort Bliss, Texas, United States, 79920
- William Beaumont Army Medical Center
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San Antonio, Texas, United States, 78234
- Brooke Army Medical Center
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Washington
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Tacoma, Washington, United States, 98431
- Madigan Army Medical Center
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Participation Criteria
Eligibility Criteria
Ages Eligible for Study
Accepts Healthy Volunteers
Genders Eligible for Study
Sampling Method
Study Population
Description
Inclusion Criteria:
- Active duty service member eligible for Tricare benefits
- Lower extremity or lumbar/thoracic spine injury is the patient's primary complaint.
- Determined fit for duty (cleared to return to work) after completing a course of physical therapy for a lower extremity or lumbar/thoracic spine musculoskeletal injury
Exclusion Criteria:
- Individuals planing on leaving the military within the next 10 months.
- Trauma or polytrauma that results in amputation of any limbs or appendages.
- Pregnancy, or recently pregnant within the last 6 months - subjects that become pregnant during the course of the study will be withdrawn based on the different injury risk factors that are associated with pregnancy.
Study Plan
How is the study designed?
Design Details
Cohorts and Interventions
Group / Cohort |
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Return to Duty after Rehab from Injury
Patients deemed healthy enough to return to full duty without any restrictions after completing a course of rehabilitation for a lumbar/thoracic spine or lower extremity injury.
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What is the study measuring?
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
---|---|---|
Injury Occurrence
Time Frame: 1 year
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Monthly SMS survey capturing new musculoskeletal injury since the prior survey
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1 year
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Secondary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
---|---|---|
Injury-Related Healthcare Utilization
Time Frame: 1 year
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Healthcare utilization for musculoskeletal injury taken from the Tricare claims database (MHS Data Repository)
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1 year
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Collaborators and Investigators
Sponsor
Collaborators
Investigators
- Principal Investigator: Daniel Rhon, DSc, Brooke Army Medical Center
Publications and helpful links
General Publications
- Ernat J, Knox J, Orchowski J, Owens B. Incidence and risk factors for acute low back pain in active duty infantry. Mil Med. 2012 Nov;177(11):1348-51. doi: 10.7205/milmed-d-12-00183.
- Lincoln AE, Smith GS, Amoroso PJ, Bell NS. The natural history and risk factors of musculoskeletal conditions resulting in disability among US Army personnel. Work. 2002;18(2):99-113.
- Knapik JJ, Graham B, Cobbs J, Thompson D, Steelman R, Jones BH. A prospective investigation of injury incidence and injury risk factors among Army recruits in military police training. BMC Musculoskelet Disord. 2013 Jan 17;14:32. doi: 10.1186/1471-2474-14-32.
- Jones BH, Thacker SB, Gilchrist J, Kimsey CD Jr, Sosin DM. Prevention of lower extremity stress fractures in athletes and soldiers: a systematic review. Epidemiol Rev. 2002;24(2):228-47. doi: 10.1093/epirev/mxf011. No abstract available.
- Wilkinson DM, Blacker SD, Richmond VL, Horner FE, Rayson MP, Spiess A, Knapik JJ. Injuries and injury risk factors among British army infantry soldiers during predeployment training. Inj Prev. 2011 Dec;17(6):381-7. doi: 10.1136/ip.2010.028233. Epub 2011 Apr 19.
- Lehr ME, Plisky PJ, Butler RJ, Fink ML, Kiesel KB, Underwood FB. Field-expedient screening and injury risk algorithm categories as predictors of noncontact lower extremity injury. Scand J Med Sci Sports. 2013 Aug;23(4):e225-32. doi: 10.1111/sms.12062. Epub 2013 Mar 20.
- Butler RJ, Contreras M, Burton LC, Plisky PJ, Goode A, Kiesel K. Modifiable risk factors predict injuries in firefighters during training academies. Work. 2013 Jan 1;46(1):11-7. doi: 10.3233/WOR-121545.
- Peate WF, Bates G, Lunda K, Francis S, Bellamy K. Core strength: a new model for injury prediction and prevention. J Occup Med Toxicol. 2007 Apr 11;2:3. doi: 10.1186/1745-6673-2-3.
- Larsson H, Broman L, Harms-Ringdahl K. Individual risk factors associated with premature discharge from military service. Mil Med. 2009 Jan;174(1):9-20. doi: 10.7205/milmed-d-03-7407.
- Bahr R. Why screening tests to predict injury do not work-and probably never will...: a critical review. Br J Sports Med. 2016 Jul;50(13):776-80. doi: 10.1136/bjsports-2016-096256. Epub 2016 Apr 19.
- Jones BH, Perrotta DM, Canham-Chervak ML, Nee MA, Brundage JF. Injuries in the military: a review and commentary focused on prevention. Am J Prev Med. 2000 Apr;18(3 Suppl):71-84. doi: 10.1016/s0749-3797(99)00169-5.
- Knapik JJ, Bullock SH, Canada S, Toney E, Wells JD, Hoedebecke E, Jones BH. Influence of an injury reduction program on injury and fitness outcomes among soldiers. Inj Prev. 2004 Feb;10(1):37-42. doi: 10.1136/ip.2003.002808.
- Parkkari J, Kujala UM, Kannus P. Is it possible to prevent sports injuries? Review of controlled clinical trials and recommendations for future work. Sports Med. 2001;31(14):985-95. doi: 10.2165/00007256-200131140-00003.
- de la Motte SJ, Lisman P, Sabatino M, Beutler AI, O'Connor FG, Deuster PA. The Relationship Between Functional Movement, Balance Deficits, and Previous Injury History in Deploying Marine Warfighters. J Strength Cond Res. 2016 Jun;30(6):1619-25. doi: 10.1519/JSC.0000000000000850.
- Kodesh E, Shargal E, Kislev-Cohen R, Funk S, Dorfman L, Samuelly G, Hoffman JR, Sharvit N. Examination of the Effectiveness of Predictors for Musculoskeletal Injuries in Female Soldiers. J Sports Sci Med. 2015 Aug 11;14(3):515-21. eCollection 2015 Sep.
- Bonazza NA, Smuin D, Onks CA, Silvis ML, Dhawan A. Reliability, Validity, and Injury Predictive Value of the Functional Movement Screen: A Systematic Review and Meta-analysis. Am J Sports Med. 2017 Mar;45(3):725-732. doi: 10.1177/0363546516641937. Epub 2016 Jul 21.
- Rhon DI, Teyhen DS, Shaffer SW, Goffar SL, Kiesel K, Plisky PP. Developing predictive models for return to work using the Military Power, Performance and Prevention (MP3) musculoskeletal injury risk algorithm: a study protocol for an injury risk assessment programme. Inj Prev. 2018 Feb;24(1):81-88. doi: 10.1136/injuryprev-2016-042234. Epub 2016 Nov 24.
Study record dates
Study Major Dates
Study Start (Actual)
Primary Completion (Actual)
Study Completion (Actual)
Study Registration Dates
First Submitted
First Submitted That Met QC Criteria
First Posted (Estimate)
Study Record Updates
Last Update Posted (Actual)
Last Update Submitted That Met QC Criteria
Last Verified
More Information
Terms related to this study
Additional Relevant MeSH Terms
Other Study ID Numbers
- 215032
Plan for Individual participant data (IPD)
Plan to Share Individual Participant Data (IPD)?
IPD Plan Description
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