Alonso-Recio Laura, Martín-Plasencia Pilar, Ruiz Miguel, Serrano Juan Manuel
a Departamento de Psicología y Salud. Facultad de Ciencias de la Salud y de la Educación , Universidad a Distancia de Madrid , Madrid , Spain.
b Departamento de Psicología biológica y de la Salud. Facultad de Psicología , Universidad Autónoma de Madrid , Madrid , Spain.
J Clin Exp Neuropsychol. 2018 Oct;40(8):777-789. doi: 10.1080/13803395.2018.1432570. Epub 2018 Feb 12.
Cognitive impairments are common in Parkinson's disease (PD) patients without dementia. These deficits are quite heterogeneous, which makes it difficult to recognize and treat them. For this reason, many authors have attempted to classify patients into more homogeneous groups with diverse results. The present study was designed to analyze the cognitive heterogeneity in PD patients using a novel data-driven approach, latent profile analysis (LPA), to classify patients according to cognitive characteristics. This methodology, which has been used in previous studies focused on motor and psychiatric symptomatology, seems to be better than traditional cluster analysis for the establishment and comparison between different subgroups because it does not require prior decision making about some theoretical or methodological aspects.
LPA was applied to 71 PD patients evaluated with a broad neuropsychological battery including different memory and executive function tests. The clusters obtained from the analysis were described by making comparisons with a control group of 51 healthy subjects matched in age, sex, and educational level.
The LPA resulted in a four-cluster solution, which could be described as: (a) executive dysfunction (32.4%), (b) memory and executive dysfunction (28.2%), (c) memory dysfunction (23.9%), and (d) noncognitive dysfunction (15.5%). These four PD cluster differ in age and Mini-Mental State Examination (MMSE) score. However, there were no differences between clusters in disease duration, clinical impression of severity index, depression, and cognitive reserve.
LPA is a very interesting method for the establishment of more homogeneous groups of PD patients based on their neuropsychological characteristics. Moreover, the distinction between different cognitive profiles will allow us to design interventions better adapted to each patient.
认知障碍在无痴呆的帕金森病（PD）患者中很常见。这些缺陷非常异质，这使得识别和治疗它们变得困难。因此，许多作者试图将患者分为更同质的组，但结果各异。本研究旨在使用一种新的数据驱动方法——潜在类别分析（LPA）来分析PD患者的认知异质性，以便根据认知特征对患者进行分类。这种方法已用于先前关注运动和精神症状学的研究中，对于建立不同亚组并进行比较似乎比传统聚类分析更好，因为它不需要在一些理论或方法学方面预先做出决策。
对71名接受广泛神经心理测试电池评估的PD患者应用LPA，该测试电池包括不同的记忆和执行功能测试。通过与51名年龄、性别和教育水平相匹配的健康受试者对照组进行比较，描述从分析中获得的聚类。
LPA产生了一个四类解决方案，可描述为：（a）执行功能障碍（32.4%），（b）记忆和执行功能障碍（28.2%），（c）记忆功能障碍（23.9%），以及（d）非认知功能障碍（15.5%）。这四个PD聚类在年龄和简易精神状态检查表（MMSE）评分上存在差异。然而，聚类在病程、严重程度指数的临床印象、抑郁和认知储备方面没有差异。
LPA是一种基于神经心理特征建立更同质PD患者组的非常有趣的方法。此外，不同认知概况之间的区分将使我们能够设计更适合每个患者的干预措施。
