Department of Clinical and Experimental Medicine, University of Catania, Catania, Italy.
Department of Banking and Insurance, Catholic University of Milan, Milan, Italy.
Eur Psychiatry. 2022 May 31;65(1):e30. doi: 10.1192/j.eurpsy.2022.20.
Subthreshold hypomania during a major depressive episode challenges the bipolar-unipolar dichotomy. In our study we employed a cross-diagnostic cluster analysis - to identify distinct subgroups within a cohort of depressed patients.
A k-means cluster analysis- based on the domain scores of the Mood Spectrum Self-Report (MOODS-SR) questionnaire-was performed on a data set of 300 adults with either bipolar or unipolar depression. After identifying groups, between-clusters comparisons were conducted on MOODS-SR domains and factors and on a set of sociodemographic, clinical and psychometric variables.
Three clusters were identified: one with intermediate depressive and poor manic symptomatology (Mild), one with severe depressive and poor manic symptomatology (Moderate), and a third one with severe depressive and intermediate manic symptomatology (Mixed). Across the clusters, bipolar patients were significantly less represented in the Mild one, while the DSM-5 "Mixed features" specifier did not differentiate the groups. When compared to the other patients, those of Mixed cluster exhibited a stronger association with most of the illness-severity, quality of life, and outcomes measures considered. After performing pairwise comparisons significant differences between "Mixed" and "Moderate" clusters were restricted to: current and disease-onset age, psychotic ideation, suicidal attempts, hospitalization numbers, impulsivity levels and comorbidity for Cluster B personality disorder.
In the present study, a clustering approach based on a spectrum exploration of mood symptomatology led to the identification of three transdiagnostic groups of patients. Consistent with our hypothesis, the magnitude of subthreshold (hypo)manic symptoms was related to a greater clinical severity, regardless of the main categorical diagnosis.
在重度抑郁发作期间出现亚阈值轻躁狂症，这对双相-单相二分法提出了挑战。在我们的研究中，我们采用了一种跨诊断聚类分析——在一组抑郁患者中识别不同的亚组。
基于心境谱自评量表（MOODS-SR）的领域评分，对 300 名双相或单相抑郁患者的数据进行了 k-均值聚类分析。在确定组后，对 MOODS-SR 各领域和因子以及一组社会人口学、临床和心理计量学变量进行了组间比较。
确定了三个聚类：一个具有中等抑郁和较差轻躁狂症状的聚类（轻度），一个具有严重抑郁和较差轻躁狂症状的聚类（中度），和一个具有严重抑郁和中等轻躁狂症状的聚类（混合）。在整个聚类中，轻度组中双相患者的比例明显较低，而 DSM-5“混合特征”特征并不能区分这些组。与其他患者相比，混合组的患者与大多数疾病严重程度、生活质量和预后指标的相关性更强。进行两两比较后，“混合”和“中度”聚类之间的显著差异仅限于：当前和发病年龄、精神病性思维、自杀企图、住院次数、冲动水平和 B 组人格障碍共病。
在本研究中，基于心境症状谱的探索的聚类方法导致了三种跨诊断患者亚组的识别。与我们的假设一致，亚阈值（轻）躁狂症状的严重程度与更大的临床严重程度相关，而与主要的分类诊断无关。
