School of Life Course and Population Sciences, King's College London, London, UK.
School of Life Course and Population Sciences, King's College London, London, UK.
Lancet. 2023 Nov;402 Suppl 1:S64. doi: 10.1016/S0140-6736(23)02111-6.
Previous studies have investigated the risk factors for post-stroke depression at only one timepoint, neglecting its dynamic nature. We aimed to identify trajectories of post-stroke depression from multiple assessments and explore their risk factors.
We did a population-based cohort study with the South London Stroke Register (1995-2019). All stroke patients with three or more measurements of the Hospital Anxiety and Depression Scale were included. We identified trajectories of post-stroke depression over a 10-year follow-up using group-based trajectory modelling. We determined the optimal number and shape of trajectories based on the lowest Bayesian information criterion, average posterior probability of assignment of each group over 0·70, and inclusion of at least 5% of participants within each group. We used multinomial logistic regression adjusted for age, sex, ethnicity, comorbidity, physical disability, stroke severity, history of depression and cognitive impairment to explore associations with different trajectories.
The analysis comprised 1968 participants (mean age 64·9 years [SD 13·8], 56·6% male and 43·4% female, 65·1% white ethnicity, 30·7% severe disability and 32·7% severe stroke). We identified four patterns of symptoms: no depressive symptoms (14·1%, n=277), low symptoms (41·7%, n=820), moderate symptoms and symptoms worsening early and then improving (34·6%, n=681), and high and increasing symptoms (9·7%, n=190). Compared with no depressive symptom trajectory, patients with severe disability, severe stroke, pre-stroke depression, and cognitive impairment were more likely to be in the moderate and high symptom groups (adjusted odds ratios [ORs] 2·26 [95% CI 1·56-3·28], 1·75 [1·19-2·57], 2·20 [1·02-4·74], and 2·04 [1·25-3·32], respectively). Female sex was associated with high depression (OR 1·65 [1·13-2·41]), while older age (≥65 years) was associated with moderate depression (OR 1·82 [1·36-2·45]). In men, the ORs for patients with severe disability, severe stroke, pre-stroke depression, and cognitive impairment being in the high depression group were 1·91 (1·01-3·60), 2·41 (1·26-4·60), 2·57 (0·84-7·88), and 2·68 (1·28-5·60), respectively. In women, the ORs were 1·08 (0·52-2·23), 1·30 (0·60-2·79), 19·2 (2·35-156·05), and 3·80 (1·44-10·01), respectively.
Female sex and older age were associated with distinct courses of depressive symptoms. In men, high depressive symptom trajectory was associated with severe stroke and severe disability, which was not the case in women. These findings were limited to patients with three or more assessments, who tended to have less severe disabilities than excluded patients and might not generalise to all stroke survivors.
National Institute for Health and Care Research (NIHR).
先前的研究仅在一个时间点上调查了卒中后抑郁的风险因素,而忽略了其动态性质。我们旨在从多次评估中确定卒中后抑郁的轨迹,并探讨其风险因素。
我们进行了一项基于人群的队列研究,纳入了来自伦敦南部卒中登记处(1995-2019 年)的所有卒中患者。所有卒中患者均进行了三次或以上的医院焦虑和抑郁量表测量。我们使用基于群组的轨迹建模方法,在 10 年的随访中确定卒中后抑郁的轨迹。我们基于最低贝叶斯信息准则、每个群组的分配后概率的平均值超过 0.70、以及每个群组中至少有 5%的参与者,确定轨迹的最佳数量和形状。我们使用调整了年龄、性别、种族、合并症、身体残疾、卒中严重程度、抑郁和认知障碍病史的多变量逻辑回归来探讨与不同轨迹的关联。
该分析共纳入了 1968 名参与者(平均年龄 64.9 岁[标准差 13.8],56.6%为男性,43.4%为女性,65.1%为白人,30.7%为严重残疾,32.7%为严重卒中)。我们确定了四种症状模式:无症状(14.1%,n=277)、轻度症状(41.7%,n=820)、中度症状和症状早期加重然后改善(34.6%,n=681),以及高症状和持续加重(9.7%,n=190)。与无症状轨迹相比,严重残疾、严重卒中、卒中前抑郁和认知障碍患者更有可能处于中度和高症状组(调整后的比值比[ORs]分别为 2.26[95%CI 1.56-3.28]、1.75[1.19-2.57]、2.20[1.02-4.74]和 2.04[1.25-3.32])。女性与高抑郁相关(OR 1.65[1.13-2.41]),而年龄较大(≥65 岁)与中度抑郁相关(OR 1.82[1.36-2.45])。在男性中,严重残疾、严重卒中、卒中前抑郁和认知障碍患者处于高抑郁组的 OR 分别为 1.91[1.01-3.60]、2.41[1.26-4.60]、2.57[0.84-7.88]和 2.68[1.28-5.60]。在女性中,OR 分别为 1.08[0.52-2.23]、1.30[0.60-2.79]、19.2[2.35-156.05]和 3.80[1.44-10.01]。
女性性别和年龄较大与抑郁症状的不同轨迹相关。在男性中,高抑郁症状轨迹与严重卒中和严重残疾相关,而在女性中则不然。这些发现仅限于进行了三次或以上评估的患者,这些患者的残疾程度往往比排除的患者轻,并且可能不适用于所有卒中幸存者。
英国国家卫生与保健研究所(NIHR)。