There was no significant difference between the groups at 2 years. Most patients perceived little to no change in status at 2 years, and one-third of military patients were not medically fit for duty at 2 years. Limitations include a single hospital, a single surgeon, and a high rate of crossover. Registration: NCT01993615 ( ClinicalTrials.gov identifier).

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. 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 situp 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 o...

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Introduction Noncombat injuries (“injuries”) greatly impact soldier health and United States (U.S.) Army readiness; they are the leading cause of outpatient medical encounters (more than two million annually) among active component (AC) soldiers. Noncombat musculoskeletal injuries (“MSKIs”) may account for nearly 60% of soldiers’ limited duty days and 65% of soldiers who cannot deploy for medical reasons. Injuries primarily affect readiness through increased limited duty days, decreased deployability rates, and increased medical separation rates. MSKIs are also responsible for exorbitant medical costs to the U.S. government, including service-connected disability compensation. A significant subset of soldiers develops chronic pain or long-term disability after injury; this may increase their risk for chronic disease or secondary health deficits potentially associated with MSKIs. The authors will review trends in U.S. Army MSKI rates, summarize MSKI readiness-related impacts, and highlight the importance of standardizing surveillance approaches, including injury definitions used in injury surveillance. Materials/Methods This review summarizes current reports and U.S. Department of Defense internal policy documents. MSKIs are defined as musculoskeletal disorders resulting from mechanical energy transfer, including traumatic and overuse injuries, which may cause pain and/or limit function. This review focuses on various U.S. Army populations, based on setting, sex, and age; the review excludes combat or battle injuries. Results More than half of all AC soldiers sustained at least one injury (MSKI or non-MSKI) in 2017. Overuse injuries comprise at least 70% of all injuries among AC soldiers. Female soldiers are at greater risk for MSKI than men. Female soldiers’ aerobic and muscular fitness performances are typically lower than men’s performances, which could account for their higher injury rates. Older soldiers are at greater injury risk than younger soldiers. Soldiers in noncombat arms units tend to have higher incidences of reported MSKIs, more limited duty days, and higher rates of limited duty days for chronic MSKIs than soldiers in combat arms units. MSKIs account for 65% of medically nondeployable AC soldiers. At any time, 4% of AC soldiers cannot deploy because of MSKIs. Once deployed, nonbattle injuries accounted for approximately 30% of all medical evacuations, and were the largest category of soldier evacuations from both recent major combat theaters (Iraq and Afghanistan). More than 85% of service members medically evacuated for MSKIs failed to return to the theater. MSKIs factored into (1) nearly 70% of medical disability discharges across the Army from 2011 through 2016 and (2) more than 90% of disability discharges within enlisted soldiers’ first year of service from 2010 to 2015. MSKI-related, service-connected (SC) disabilities account for 44% of all SC disabilities (more than any other body system) among compensated U.S. Global War on Terrorism veterans. Conclusions MSKIs significantly impact soldier health and U.S. Army readiness. MSKIs also figure prominently in medical disability discharges and long-term, service-connected disability costs. MSKI patterns and trends vary between trainees and soldiers in operational units and among military occupations and types of operational units. Coordinated injury surveillance efforts are needed to provide standardized metrics and accurately measure temporal changes in injury rates.

Cardon Rehabilitation Products through the American Academy of Orthopaedic Manual Physical Therapists.

Background: Musculoskeletal injuries are a primary source of disability. Understanding how risk factors predict injury is necessary to individualize and enhance injury reduction programs. Hypothesis: Because of the multifactorial nature of musculoskeletal injuries, multiple risk factors will provide a useful method of categorizing warrior athletes based on injury risk. Study Design: Prospective observational cohort study. Level of Evidence: Level 2. Methods: Baseline data were collected on 922 US Army soldiers/warrior athletes (mean age, 24.7 ± 5.2 years; mean body mass index, 26.8 ± 3.4 kg/m2) using surveys and physical measures. Injury occurrence and health care utilization were collected for 1 year. Variables were compared in healthy versus injured participants using independent t tests or chi-square analysis. Significantly different factors between each group were entered into a logistic regression equation. Receiver operating characteristic curve and accuracy statistics were calculated for regression variables. Results: Of the 922 warrior athletes, 38.8% suffered a time-loss injury (TLI). Overall, 35 variables had a significant relationship with TLIs. The logistic regression equation, consisting of 11 variables of interest, was significant (adjusted R2 = 0.21; odds ratio, 5.7 [95% CI, 4.1-7.9]; relative risk, 2.5 [95% CI, 2.1-2.9]; area under the curve, 0.73). Individuals with 2 variables had a sensitivity of 0.89, those with 7 or more variables had a specificity of 0.94. Conclusion: The sum of individual risk factors (prior injury, prior work restrictions, lower perceived recovery from injury, asymmetrical ankle dorsiflexion, decreased or asymmetrical performance on the Lower and Upper Quarter Y-Balance test, pain with movement, slower 2-mile run times, age, and sex) produced a highly sensitive and specific multivariate model for TLI in military servicemembers. Clinical Relevance: A better understanding of characteristics associated with future injury risk can provide a foundation for prevention programs designed to reduce medical costs and time lost.

Background: The effectiveness of blood flow restriction training (BFRT) as compared with other forms of training, such as resistance training, has been evaluated in the literature in clinical and nonclinical populations. However, the safety of this intervention has been summarized only in healthy populations and not in clinical populations with musculoskeletal disorders. Purpose: To evaluate the safety and adverse events associated with BFRT in patients with musculoskeletal disorders. Study Design: Systematic review. Methods: A literature search was conducted with 3 online databases (MEDLINE, CINAHL, and Embase). Eligibility criteria for selecting studies were as follows: (1) BFRT was used as a clinical intervention, (2) study participants had a disorder of the musculoskeletal system, (3) authors addressed adverse events, (4) studies were published in English, and (5) the intervention was performed with human participants. Results: Nineteen studies met eligibility criteria, with a pooled sample size of 322. Diagnoses included various knee-related disorders, inclusion body myositis, polymyositis or dermatomyositis, thoracic outlet syndrome, Achilles tendon rupture, and bony fractures. Nine studies reported no adverse events, while 3 reported rare adverse events, including an upper extremity deep vein thrombosis and rhabdomyolysis. Three case studies reported common adverse events, including acute muscle pain and acute muscle fatigue. In the randomized controlled trials, individuals exposed to BFRT were not more likely to have an adverse event than individuals exposed to exercise alone. Of the 19 studies, the adverse events were as follows: overall, 14 of 322; rare overall, 3 of 322; rare BFRT, 3 of 168; rare control, 0 of 154; any adverse BFRT, 10 of 168; any adverse control, 4 of 154. A majority of studies were excluded because they did not address safety. Conclusion: BFRT appears to be a safe strengthening approach for knee-related musculoskeletal disorders, but further research is needed to make definitive conclusions and to evaluate the safety in other musculoskeletal conditions. Improved definitions of adverse events related to BFRT are needed to include clear criteria for differentiating among common, uncommon, and rare adverse events. Finally, further research is needed to effectively screen who might be at risk for rare adverse events.

BackgroundLarge healthcare databases, with their ability to collect many variables from daily medical practice, greatly enable health services research. These longitudinal databases provide large cohorts and longitudinal time frames, allowing for highly pragmatic assessment of healthcare delivery. The purpose of this paper is to discuss the methodology related to the use of the United States Military Health System Data Repository (MDR) for longitudinal assessment of musculoskeletal clinical outcomes, as well as address challenges of using this data for outcomes research.MethodsThe Military Health System manages care for approximately 10 million beneficiaries worldwide. Multiple data sources pour into the MDR from multiple levels of care (inpatient, outpatient, military or civilian facility, combat theater, etc.) at the individual patient level. To provide meaningful and descriptive coding for longitudinal analysis, specific coding for timing and type of care, procedures, medications, and provider type must be performed. Assumptions often made in clinical trials do not apply to these cohorts, requiring additional steps in data preparation to reduce risk of bias. The MDR has a robust system in place to validate the quality and accuracy of its data, reducing risk of analytic error. Details for making this data suitable for analysis of longitudinal orthopaedic outcomes are provided.ResultsAlthough some limitations exist, proper preparation and understanding of the data can limit bias, and allow for robust and meaningful analyses. There is the potential for strong precision, as well as the ability to collect a wide range of variables in very large groups of patients otherwise not captured in traditional clinical trials. This approach contributes to the improved understanding of the accessibility, quality, and cost of care for those with orthopaedic conditions.ConclusionThe MDR provides a robust pool of longitudinal healthcare data at the person-level. The benefits of using the MDR database appear to outweigh the limitations.