Hirata Sarah, Ovbiagele Bruce, Markovic Daniela, Towfighi Amytis
University of Hawaii John A. Burns School of Medicine, Honolulu, Hawaii.
Department of Neurology, Medical University of South Carolina, Charleston, South Carolina.
J Stroke Cerebrovasc Dis. 2016 May;25(5):1090-1095. doi: 10.1016/j.jstrokecerebrovasdis.2015.12.042. Epub 2016 Feb 10.
Depression, one of the most common complications encountered after stroke, is associated with poorer outcomes. The aim of this study was to determine the factors independently associated with and predictive of poststroke depression (PSD).
We assessed the prevalence of depression (Patient Health Questionnaire [PHQ-8] score >10) among a national sample of adults (≥20 years) with stroke who participated in the National Health and Nutrition Examination Surveys from 2005 to 2010. Logistic regression and random forest models were used to determine the factors associated with and predictive of PSD, after adjusting for sociodemographic and clinical factors.
Of the 17,132 individuals surveyed, 546 stroke survivors were screened for depression, and 17% had depression, corresponding to 872,237 stroke survivors with depression in the United States. In the logistic regression model, after adjustment for sociodemographic variables, poverty (poverty index <200% versus ≥200%, odds ratio [OR] 2.61, 95% confidence interval [CI] 1.23-5.53) and 3 or more medical comorbidities (OR 1.59, 95% CI 1.01-2.49) were associated with higher odds of PSD; increasing age was associated with lower odds of PSD (per year OR .95, 95% CI .94-.97). In the random forest model, the 10 most important factors predictive of PSD were younger age, lower education level, higher body mass index, black race, poverty, smoking, female sex, single marital status, lack of cancer history, and previous myocardial infarction (specificity = 70%, sensitivity = 64%).
Although numerous factors were predictive of developing PSD, younger age, poverty, and multiple comorbidities were strong and independent factors. More aggressive screening for depression in these individuals may be warranted.
抑郁症是中风后最常见的并发症之一，与较差的预后相关。本研究的目的是确定与中风后抑郁症（PSD）独立相关并可预测的因素。
我们评估了2005年至2010年参加全国健康和营养检查调查的全国成年人（≥20岁）中风样本中抑郁症的患病率（患者健康问卷[PHQ-8]评分>10）。在调整了社会人口统计学和临床因素后，使用逻辑回归和随机森林模型来确定与PSD相关并可预测的因素。
在接受调查的17132名个体中，对546名中风幸存者进行了抑郁症筛查，17%的人患有抑郁症，在美国相当于872237名患有抑郁症的中风幸存者。在逻辑回归模型中，调整社会人口统计学变量后，贫困（贫困指数<200%与≥200%相比，优势比[OR]2.61，95%置信区间[CI]1.23-5.53）和3种或更多种合并症（OR 1.59，95%CI 1.01-2.49）与PSD的较高几率相关；年龄增加与PSD的较低几率相关（每年OR 0.95，95%CI 0.94-0.97）。在随机森林模型中，预测PSD的10个最重要因素是年龄较小、教育水平较低、体重指数较高、黑人种族、贫困、吸烟、女性、单身婚姻状况、无癌症病史和既往心肌梗死（特异性=70%，敏感性=64%）。
虽然有许多因素可预测PSD的发生，但年龄较小、贫困和多种合并症是强有力的独立因素。对这些个体进行更积极的抑郁症筛查可能是必要的。
