Department of Psychiatry and Psychotherapy,University of Muenster,Muenster,Germany.
Department of Psychiatry and Psychotherapy,University of Marburg,Marburg,Germany.
Psychol Med. 2018 Oct;48(14):2391-2398. doi: 10.1017/S0033291718000016. Epub 2018 Feb 8.
Patients with major depression show reduced hippocampal volume compared to healthy controls. However, the contribution of patients' cumulative illness severity to hippocampal volume has rarely been investigated. It was the aim of our study to find a composite score of cumulative illness severity that is associated with hippocampal volume in depression.
We estimated hippocampal gray matter volume using 3-tesla brain magnetic resonance imaging in 213 inpatients with acute major depression according to DSM-IV criteria (employing the SCID interview) and 213 healthy controls. Patients' cumulative illness severity was ascertained by six clinical variables via structured clinical interviews. A principal component analysis was conducted to identify components reflecting cumulative illness severity. Regression analyses and a voxel-based morphometry approach were used to investigate the influence of patients' individual component scores on hippocampal volume.
Principal component analysis yielded two main components of cumulative illness severity: Hospitalization and Duration of Illness. While the component Hospitalization incorporated information from the intensity of inpatient treatment, the component Duration of Illness was based on the duration and frequency of illness episodes. We could demonstrate a significant inverse association of patients' Hospitalization component scores with bilateral hippocampal gray matter volume. This relationship was not found for Duration of Illness component scores.
Variables associated with patients' history of psychiatric hospitalization seem to be accurate predictors of hippocampal volume in major depression and reliable estimators of patients' cumulative illness severity. Future studies should pay attention to these measures when investigating hippocampal volume changes in major depression.
与健康对照组相比，重度抑郁症患者的海马体体积较小。然而，患者的累计疾病严重程度对海马体体积的影响很少被研究。我们的研究旨在寻找一个与抑郁症患者海马体体积相关的累计疾病严重程度的综合评分。
我们根据 DSM-IV 标准（采用 SCID 访谈）对 213 名急性重度抑郁症住院患者和 213 名健康对照组进行了 3 特斯拉脑磁共振成像，以估计海马灰质体积。通过结构临床访谈，使用六个临床变量确定患者的累计疾病严重程度。进行主成分分析以确定反映累计疾病严重程度的成分。回归分析和基于体素的形态计量学方法用于研究患者个体成分评分对海马体体积的影响。
主成分分析得出了两个累计疾病严重程度的主要成分：住院和疾病持续时间。住院成分包含了住院治疗强度的信息，而疾病持续时间成分则基于疾病发作的持续时间和频率。我们发现患者住院成分评分与双侧海马灰质体积呈显著负相关。而疾病持续时间成分评分则没有发现这种关系。
与患者精神科住院史相关的变量似乎是重度抑郁症患者海马体体积的准确预测指标，也是患者累计疾病严重程度的可靠估计指标。未来的研究在研究重度抑郁症中海马体体积变化时应注意这些指标。
