Bombardier Charles H, Hoekstra Trynke, Dikmen Sureyya, Fann Jesse R
1 Department of Rehabilitation Medicine, University of Washington , Seattle, Washington.
2 Faculty of Earth and Life Sciences, Department of Health Sciences and the EMGO Institute of Health and Care Research, VU University, Department of Epidemiology and Biostatistics, VU University Medical Center , Amsterdam, The Netherlands .
J Neurotrauma. 2016 Dec 1;33(23):2115-2124. doi: 10.1089/neu.2015.4349. Epub 2016 May 6.
Major depression is prevalent after traumatic brain injury (TBI) and associated with poor outcomes. Little is known about the course of depression after TBI. Participants were 559 consecutively admitted patients with mild to severe TBI recruited from inpatient units at Harborview Medical Center, a Level I trauma center in Seattle, WA. Participants were assessed with the Patient Health Questionnaire-9 (PHQ-9) depression measure at months 1-6, 8, 10, and 12 post-injury. We used linear latent class growth mixture modeling (LCGMM) of PHQ-9 total scores to identify homogeneous subgroups with distinct longitudinal trajectories. A four-class LCGMM had good fit indices and clinical interpretability. Trajectory groups were: low depression (70.1%), delayed depression (13.2%), depression recovery (10.4%), and persistent depression (6.3%). Multinomial logistic regression analyses were used to distinguish trajectory classes based on baseline demographic, psychiatric history, and clinical variables. Relative to the low depression group, the other three groups were consistently more likely to have a pre-injury history of other mental health disorders or major depressive disorder, a positive toxicology screen for cocaine or amphetamines at the time of injury, and a history of alcohol dependence. They were less likely to be on Medicare versus commercial insurance. Trajectories based on LCGMM are an empirical and clinically meaningful way to characterize distinct courses of depression after TBI. When combined with baseline predictors, this line of research may improve our ability to predict prognosis and target groups who may benefit from treatment or secondary prevention efforts (e.g., proactive telephone counseling).
重度抑郁症在创伤性脑损伤(TBI)后很常见,且与不良预后相关。目前对于TBI后抑郁症的病程了解甚少。研究参与者为559名从华盛顿州西雅图市一级创伤中心哈博维尤医疗中心住院部连续招募的轻至重度TBI患者。在受伤后1至6个月、8个月、10个月和12个月,使用患者健康问卷9项(PHQ - 9)抑郁量表对参与者进行评估。我们采用PHQ - 9总分的线性潜在类别增长混合模型(LCGMM)来识别具有不同纵向轨迹的同质亚组。四类LCGMM具有良好的拟合指数和临床可解释性。轨迹组分别为:低抑郁组(70.1%)、延迟抑郁组(13.2%)、抑郁恢复组(10.4%)和持续抑郁组(6.3%)。采用多项逻辑回归分析,根据基线人口统计学、精神病史和临床变量来区分轨迹类别。与低抑郁组相比,其他三组更有可能有其他心理健康障碍或重度抑郁症的伤前病史、受伤时可卡因或苯丙胺毒理学筛查呈阳性以及酒精依赖史。他们参加医疗保险而非商业保险的可能性较小。基于LCGMM的轨迹是描述TBI后抑郁症不同病程的一种经验性且具有临床意义的方法。当与基线预测因素相结合时,这一研究方向可能会提高我们预测预后的能力,并确定可能从治疗或二级预防措施(如主动电话咨询)中受益的目标群体。