Pugh Mary Jo, Finley Erin P, Wang Chen-Pin, Copeland Laurel A, Jaramillo Carlos A, Swan Alicia A, Elnitsky Christine A, Leykum Luci K, Mortensen Eric M, Eapen Blessen A, Noel Polly H, Pugh Jacqueline A
a South Texas Veterans Health Care System , San Antonio , TX , USA.
b Department of Epidemiology and Biostatistics.
Brain Inj. 2016;30(12):1481-1490. doi: 10.1080/02699052.2016.1219055.
To identify and validate trajectories of comorbidity associated with traumatic brain injury in male and female Iraq and Afghanistan war Veterans (IAV).
Derivation and validation cohorts were compiled of IAV who entered the Department of Veterans Affairs (VA) care and received 3 years of VA care between 2002-2011. Chronic disease and comorbidities associated with deployment including TBI were identified using diagnosis codes. A latent class analysis (LCA) of longitudinal comorbidity data was used to identify trajectories of comorbidity.
LCA revealed five trajectories that were similar for women and men: (1) Healthy, (2) Chronic Disease, (3) Mental Health, (4) Pain and (5) Polytrauma Clinical Triad (PCT: pain, mental health and TBI). Two additional classes found in men were 6) Minor Chronic and 7) PCT with chronic disease. Among these gender-stratified trajectories, it was found that women were more likely to experience headache (Pain trajectory) and depression (Mental Health trajectory), while men were more likely to experience lower back pain (Pain trajectory) and substance use disorder (Mental Health trajectory). The probability of TBI was highest in the PCT-related trajectories, with significantly lower probabilities in other trajectories.
It was found that TBI was most common in PCT-related trajectories, indicating that TBI is commonly comorbid with pain and mental health conditions for both men and women. The relatively young age of this cohort raises important questions regarding how disease burden, including the possibility of neurodegenerative sequelae, will accrue alongside normal age-related decline in individuals with TBI. Additional 'big data' methods and a longer observation period may allow the development of predictive models to identify individuals with TBI that are at-risk for adverse outcomes.
识别并验证伊拉克和阿富汗战争退伍军人（IAV）中与创伤性脑损伤相关的共病轨迹，该研究涉及男性和女性退伍军人。
研究对象为2002年至2011年间进入退伍军人事务部（VA）接受治疗并接受了3年VA护理的IAV，以此组成推导队列和验证队列。使用诊断代码识别与部署相关的慢性疾病和共病，包括创伤性脑损伤（TBI）。对纵向共病数据进行潜在类别分析（LCA）以识别共病轨迹。
LCA揭示了男性和女性相似的五种轨迹：（1）健康，（2）慢性疾病，（3）心理健康，（4）疼痛，以及（5）多发伤临床三联征（PCT：疼痛、心理健康和TBI）。在男性中发现的另外两类轨迹是6）轻度慢性疾病和7）伴有慢性疾病的PCT。在这些按性别分层的轨迹中，发现女性更有可能经历头痛（疼痛轨迹）和抑郁（心理健康轨迹），而男性更有可能经历下背痛（疼痛轨迹）和物质使用障碍（心理健康轨迹）。TBI的概率在与PCT相关的轨迹中最高，在其他轨迹中概率显著较低。
研究发现TBI在与PCT相关的轨迹中最为常见，这表明TBI在男性和女性中通常与疼痛和心理健康状况共病。该队列相对年轻的年龄引发了关于疾病负担（包括神经退行性后遗症的可能性）将如何随着TBI个体正常的年龄相关衰退而累积的重要问题。额外的“大数据”方法和更长的观察期可能有助于开发预测模型，以识别有不良后果风险的TBI个体。
