Browsing by Author "Simon, Janet E."

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    Fracture discrimination capability of ulnar flexural rigidity measured via Cortical Bone Mechanics Technology: study protocol for The STRONGER Study
    (Oxford University Press, 2024-01-04) Warden, Stuart J.; Dick, Andrew; Simon, Janet E.; Manini, Todd M.; Russ, David W.; Lyssikatos, Charalampos; Clark, Leatha A.; Clark, Brian C.; Physical Therapy, School of Health and Human Sciences
    Osteoporosis is characterized by low bone mass and structural deterioration of bone tissue, which leads to bone fragility (ie, weakness) and an increased risk for fracture. The current standard for assessing bone health and diagnosing osteoporosis is DXA, which quantifies areal BMD, typically at the hip and spine. However, DXA-derived BMD assesses only one component of bone health and is notably limited in evaluating the bone strength, a critical factor in fracture resistance. Although multifrequency vibration analysis can quickly and painlessly assay bone strength, there has been limited success in advancing a device of this nature. Recent progress has resulted in the development of Cortical Bone Mechanics Technology (CBMT), which conducts a dynamic 3-point bending test to assess the flexural rigidity (EI) of ulnar cortical bone. Data indicate that ulnar EI accurately estimates ulnar whole bone strength and provides unique and independent information about cortical bone compared to DXA-derived BMD. Consequently, CBMT has the potential to address a critical unmet need: Better identification of patients with diminished bone strength who are at high risk of experiencing a fragility fracture. However, the clinical utility of CBMT-derived EI has not yet been demonstrated. We have designed a clinical study to assess the accuracy of CBMT-derived ulnar EI in discriminating post-menopausal women who have suffered a fragility fracture from those who have not. These data will be compared to DXA-derived peripheral and central measures of BMD obtained from the same subjects. In this article, we describe the study protocol for this multi-center fracture discrimination study (The STRONGER Study).
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    Injury Rates in Age-Only Versus Age-and-Weight Playing Standard Conditions in American Youth Football
    (SAGE Publications, 2015-09) Kerr, Zachary Y.; Marshall, Stephen W.; Simon, Janet E.; Hayden, Ross; Snook, Erin M.; Dodge, Thomas; Gallo, Joseph A.; Valovich McLeod, Tamara C.; Mensch, James; Murphy, Joseph M.; Nittoli, Vincent C.; Dompier, Thomas P.; Ragan, Brian; Yeargin, Susan W.; Parsons, John T.; School of Health and Rehabilitation Sciences
    BACKGROUND: American youth football leagues are typically structured using either age-only (AO) or age-and-weight (AW) playing standard conditions. These playing standard conditions group players by age in the former condition and by a combination of age and weight in the latter condition. However, no study has systematically compared injury risk between these 2 playing standards. PURPOSE: To compare injury rates between youth tackle football players in the AO and AW playing standard conditions. STUDY DESIGN: Cohort study; Level of evidence, 2. METHODS: Athletic trainers evaluated and recorded injuries at each practice and game during the 2012 and 2013 football seasons. Players (age, 5-14 years) were drawn from 13 recreational leagues across 6 states. The sample included 4092 athlete-seasons (AW, 2065; AO, 2027) from 210 teams (AW, 106; O, 104). Injury rate ratios (RRs) with 95% CIs were used to compare the playing standard conditions. Multivariate Poisson regression was used to estimate RRs adjusted for residual effects of age and clustering by team and league. There were 4 endpoints of interest: (1) any injury, (2) non-time loss (NTL) injuries only, (3) time loss (TL) injuries only, and (4) concussions only. RESULTS: Over 2 seasons, the cohort accumulated 1475 injuries and 142,536 athlete-exposures (AEs). The most common injuries were contusions (34.4%), ligament sprains (16.3%), concussions (9.6%), and muscle strains (7.8%). The overall injury rate for both playing standard conditions combined was 10.3 per 1000 AEs (95% CI, 9.8-10.9). The TL injury, NTL injury, and concussion rates in both playing standard conditions combined were 3.1, 7.2, and 1.0 per 1000 AEs, respectively. In multivariate Poisson regression models controlling for age, team, and league, no differences were found between playing standard conditions in the overall injury rate (RRoverall, 1.1; 95% CI, 0.4-2.6). Rates for the other 3 endpoints were also similar (RRNTL, 1.1 [95% CI, 0.4-3.0]; RRTL, 0.9 [95% CI, 0.4-1.9]; RRconcussion, 0.6 [95% CI, 0.3-1.4]). CONCLUSION: For the injury endpoints examined in this study, the injury rates were similar in the AO and AW playing standards. Future research should examine other policies, rules, and behavioral factors that may affect injury risk within youth football.