Melbourne Neuropsychiatry Centre, Department of Psychiatry, University of Melbourne and Melbourne Health, Melbourne, Australia; Centre for Mental Health, Faculty of Health, Arts and Design, School of Health Sciences, Swinburne University, Melbourne, Australia.
Centre for Mental Health, Faculty of Health, Arts and Design, School of Health Sciences, Swinburne University, Melbourne, Australia; St Vincent's Mental Health, St Vincent's Hospital, VIC, Australia.
J Affect Disord. 2020 Apr 1;266:710-721. doi: 10.1016/j.jad.2020.01.123. Epub 2020 Jan 25.
Cognitive heterogeneity in schizophrenia spectrum disorders (SSD) and bipolar disorder (BD) has been explored using clustering analyses. However, the resulting subgroups have not been cognitively validated beyond measures used as clustering variables themselves. We compared the emergent cross-diagnostic subgroups of SSD and BD patients on measures used to classify them, and also across a range of alternative cognitive measures assessing some of the same constructs.
Domain scores from the Matrics Consensus Cognitive Battery were used in a cross-diagnostic clustering analysis of 86 patients with SSD (n = 45) and BD (n = 41). The emergent subgroups were then compared to each other and healthy controls (n = 76) on these and alternative measures of these domains, as well as on premorbid IQ, global cognition and a proxy of cognitive decline.
A three-cluster solution was most appropriate, with subgroups labelled as Globally Impaired, Selectively Impaired, and Superior/Near-Normal relative to controls. With the exception of processing speed performance, the subgroups were generally differentiated on the cognitive domain scores used as clustering variables. Differences in cognitive performance among these subgroups were not always statistically significant when compared on the alternative cognitive measures. There was evidence of global cognitive impairment and putative cognitive decline in the two cognitively impaired subgroups.
For clustering analysis, sample size was relatively small.
The overall pattern of findings tentatively suggest that emergent cross-diagnostic cognitive subgroups are not artefacts of the measures used to define them, but may represent the outcome of different cognitive trajectories.
精神分裂症谱系障碍（SSD）和双相情感障碍（BD）的认知异质性已通过聚类分析进行了探索。然而，除了用作聚类变量本身的测量之外，尚未对由此产生的亚组进行认知验证。我们比较了 SSD 和 BD 患者在用于对其进行分类的测量上以及在一系列评估相同结构的替代认知测量上出现的跨诊断亚组。
使用 Matrics 共识认知电池的领域分数对 86 名 SSD（n=45）和 BD（n=41）患者进行了跨诊断聚类分析。然后，将这些新兴的亚组与这些和替代领域的测量值以及与健康对照组（n=76）进行比较，以及与病前智商、整体认知和认知下降的替代指标进行比较。
三聚类解决方案最合适，与对照组相比，亚组分别标记为整体受损、选择性受损和优秀/接近正常。除了处理速度表现外，这些亚组通常在用作聚类变量的认知域分数上有所区分。当在替代认知测量上进行比较时，这些亚组之间的认知表现差异并不总是具有统计学意义。在两个认知受损的亚组中，存在整体认知受损和潜在认知下降的证据。
对于聚类分析，样本量相对较小。
总体研究结果表明，新兴的跨诊断认知亚组不是定义它们的测量的人为产物，而可能代表不同认知轨迹的结果。
