Center for the Intrepid, Brooke Army Medical Center, JBSA, Fort Sam Houston, Texas, USA.
Doctoral Program in Physical Therapy, Baylor University, JBSA, Fort Sam Houston, Texas, USA.
Inj Prev. 2018 Feb;24(1):81-88. doi: 10.1136/injuryprev-2016-042234. Epub 2016 Nov 24.
Musculoskeletal injuries are a primary source of disability in the US Military, and low back pain and lower extremity injuries account for over 44% of limited work days annually. History of prior musculoskeletal injury increases the risk for future injury. This study aims to determine the risk of injury after returning to work from a previous injury. The objective is to identify criteria that can help predict likelihood for future injury or re-injury.
There will be 480 active duty soldiers recruited from across four medical centres. These will be patients who have sustained a musculoskeletal injury in the lower extremity or lumbar/thoracic spine, and have now been cleared to return back to work without any limitations. Subjects will undergo a battery of physical performance tests and fill out sociodemographic surveys. They will be followed for a year to identify any musculoskeletal injuries that occur. Prediction algorithms will be derived using regression analysis from performance and sociodemographic variables found to be significantly different between injured and non-injured subjects.
Due to the high rates of injuries, injury prevention and prediction initiatives are growing. This is the first study looking at predicting re-injury rates after an initial musculoskeletal injury. In addition, multivariate prediction models appear to have move value than models based on only one variable. This approach aims to validate a multivariate model used in healthy non-injured individuals to help improve variables that best predict the ability to return to work with lower risk of injury, after a recent musculoskeletal injury.
NCT02776930.
肌肉骨骼损伤是美国军队残疾的主要原因,每年有超过 44%的工作受限天数是由于下腰痛和下肢损伤造成的。既往肌肉骨骼损伤史会增加未来损伤的风险。本研究旨在确定从前次损伤恢复工作后再次受伤的风险。目的是确定有助于预测未来损伤或再损伤可能性的标准。
将从四个医疗中心招募 480 名现役士兵。这些将是下肢或腰椎/胸椎遭受肌肉骨骼损伤且现已康复并可无限制重返工作岗位的患者。受试者将接受一系列体能测试并填写社会人口学调查。将对他们进行为期一年的随访,以确定是否发生任何肌肉骨骼损伤。将使用回归分析从受伤和未受伤受试者之间存在显著差异的表现和社会人口学变量中得出预测算法。
由于受伤率较高,预防和预测受伤的措施正在增加。这是第一项研究,旨在预测初次肌肉骨骼损伤后的再受伤率。此外,多变量预测模型似乎比仅基于一个变量的模型更有价值。这种方法旨在验证一种用于健康未受伤个体的多变量模型,以帮助改善可最佳预测在近期肌肉骨骼损伤后重返工作岗位并降低受伤风险的能力的变量。
NCT02776930。