Department of Neurosciences, Research Group Psychiatry, Neuropsychiatry, Academic Center for ECT and Neuromodulation (AcCENT), University Psychiatric Center KU Leuven, Kortenberg, Belgium; Department of Neurosciences, Mind Body Research, KU Leuven, Leuven, Belgium.
Department of Psychiatry, Leiden University Medical Center, Leiden, the Netherlands; Department of Public Health and Primary Care, Health Campus the Hague, Leiden University Medical Center, The Hague, the Netherlands.
Brain Stimul. 2023 Nov-Dec;16(6):1677-1683. doi: 10.1016/j.brs.2023.11.004. Epub 2023 Nov 10.
The recent network perspective of depression conceptualizes depression as a dynamic network of causally related symptoms, that contrasts with the traditional view of depression as a discrete latent entity that causes all symptoms. Electroconvulsive therapy (ECT) is an effective treatment for severe depression, but little is known about the temporal trajectories of symptom improvement during a course of ECT.
To gain insight into the dynamics of depressive symptoms in individuals treated with ECT.
The Quick Inventory of Depressive Symptomatology (QIDS) was used to assess symptoms twice a week in 68 participants with a unipolar or bipolar depression treated with ECT, with an average of 12 assessments per participant. Dynamic time warping (DTW) was used to analyze individual time series data, which were subsequently aggregated to calculate a directed symptom network and the in- and out-strength for each symptom.
Participants had a mean age of 49.6 (SD = 12.8) and 60% were female. Somatic symptoms (e.g., decreased weight) and suicidal ideation showed the highest out-strength values, indicating that their improvement tended to precede improvements in mood symptoms, which showed high in-strength. Sad mood had the highest in-strength, and thus appeared to be the last symptom to improve during ECT treatment (p < 0.001).
This study addresses a gap in the existing literature on ECT, by first analysing the temporal trajectories of symptoms within individual patients and subsequently aggregating them to the group level. The results show that somatic symptoms tend to improve before mood symptoms during ECT.
近期抑郁症的网络视角将抑郁症视为因果相关症状的动态网络，与传统的将抑郁症视为导致所有症状的离散潜在实体的观点形成对比。电抽搐治疗（ECT）是治疗重度抑郁症的有效方法，但对于 ECT 治疗过程中症状改善的时间轨迹知之甚少。
深入了解接受 ECT 治疗的个体中抑郁症状的动态变化。
使用快速抑郁症状清单（QIDS）每周两次评估 68 名单相或双相抑郁症患者的症状，每位患者平均评估 12 次。使用动态时间扭曲（DTW）分析个体时间序列数据，随后将其汇总以计算有向症状网络以及每个症状的入度和出度。
参与者的平均年龄为 49.6（SD=12.8），其中 60%为女性。躯体症状（如体重减轻）和自杀意念显示出最高的出度值，表明它们的改善倾向于先于情绪症状的改善，而情绪症状的改善具有较高的入度。悲伤情绪具有最高的入度，因此似乎是 ECT 治疗期间最后一个改善的症状（p<0.001）。
本研究通过首先分析个体患者内症状的时间轨迹，然后将其汇总到群体水平，填补了 ECT 现有文献中的空白。结果表明，在 ECT 治疗期间，躯体症状往往会先于情绪症状改善。
