Power training was more effective than strength training for improving physical function in community-dwelling older adults.

Context:Lower extremity stress fractures among athletes and military recruits cause significant morbidity, fiscal costs, and time lost from sport or training. During fiscal years (FY) 2012 to 2014, 1218 US Air Force trainees at Joint Base San Antonio–Lackland, Texas, were diagnosed with stress fracture(s). Diagnosis relied heavily on bone scans, often very early in clinical course and often in preference to magnetic resonance imaging (MRI), highlighting the need for an evidence-based algorithm for stress injury diagnosis and initial management.Evidence Acquisition:To guide creation of an evidence-based algorithm, a literature review was conducted followed by analysis of local data. Relevant articles published between 1995 and 2015 were identified and reviewed on PubMed using search terms stress fracture, stress injury, stress fracture imaging, and stress fracture treatment. Subsequently, charts were reviewed for all Air Force trainees diagnosed with 1 or more stress injury in their outpatient medical record in FY 2014.Study Design:Clinical review.Level of Evidence:Level 4.Results:In FY 2014, 414 trainees received a bone scan and an eventual diagnosis of stress fracture. Of these scans, 66.4% demonstrated a stress fracture in the symptomatic location only, 21.0% revealed stress fractures in both symptomatic and asymptomatic locations, and 5.8% were negative in the symptomatic location but did reveal stress fracture(s) in asymptomatic locations. Twenty-one percent (18/85) of MRIs performed a mean 6 days (range, 0- 21 days) after a positive bone scan did not demonstrate any stress fracture.Conclusion:Bone stress injuries in military training environments are common, costly, and challenging to diagnose. MRI should be the imaging study of choice, after plain radiography, in those individuals meeting criteria for further workup.

AC is a better predictor of musculoskeletal injury risk than BMI in a large military population. Although absolute injury risk is greatest in 18- to 24-yr-old participants, the effect of obesity on injury risk is greatest in 25- to 34-yr-old participants. There is a dose-response relation between obesity and musculoskeletal injury risk, an effect seen with both BMI and AC.

Exertional rhabdomyolysis (ER) is an uncommon condition with a paucity of evidence-based guidance for diagnosis, management, and return to duty or play. Recently, a clinical practice guideline for diagnosis and management of ER in warfighters was updated by a team of military and civilian physicians and researchers using current scientific literature and decades of experience within the military population. The revision concentrated on challenging and controversial clinical questions with applicability to providers in the military and those in the greater sports medicine community. Specific topics addressed: 1) diagnostic criteria for ER; 2) clinical decision making for outpatient versus inpatient treatment; 3) optimal strategies for inpatient management; 4) discharge criteria; 5) identification and assessment of warfighters/athletes at risk for recurrent ER; 6) an appropriate rehabilitative plan; and finally, 7) key clinical questions warranting future research.

Background: A novel algorithm and clinical prediction rule (CPR), with 18 variables, was created in 2014. The CPR generated a bone stress injury (BSI) score, which was used to determine the necessity of imaging in suspected BSI. To date, there are no validated algorithms for imaging selection in patients with suspected BSI. Hypothesis: A simplified CPR will assist clinicians with diagnosis and decision making in patients with suspected BSI. Study Design: Prospective cohort study. Level of Evidence: Level 3. Methods: A total of 778 military trainees with lower extremity pain were enrolled. All trainees were evaluated for 18 clinical variables suggesting BSI. Participants were monitored via electronic medical record review. Then, a prediction model was developed using logistic regression to identify clinical variables with the greatest predictive value and assigned appropriate weight. Test characteristics for various BSI score thresholds were calculated. Results: Of the enrolled trainees, 204 had imaging-confirmed BSI in or distal to the femoral condyles. The optimized CPR selected 4 clinical variables (weighted score): bony tenderness (3), prior history of BSI (2), pes cavus (2), and increased walking/running volume (1). The optimized CPR with a score ≥3 yielded 97.5% sensitivity, 54.2% specificity, and 98.2% negative predictive value. An isolated measure, bony tenderness, demonstrated similar statistical performance. Conclusion: The optimized CPR, which uses bony tenderness, prior history of BSI, pes cavus, and increased walking/running volume, is valid for detecting BSI in or distal to the femoral condyles. However, bony tenderness alone provides a simpler criterion with an equally strong negative predictive value for BSI decision making. Clinical Relevance: For suspected BSI in or distal to the femoral condyles, imaging can be deferred when there is no bony tenderness. When bony tenderness is present in the setting of 1 or more proven risk factors and no clinical evidence of high-risk bone involvement, presumptive treatment for BSI and serial radiographs may be appropriate.