Mapping Actuarial Criteria for Parkinson's Disease-Mild Cognitive Impairment onto Data-Driven Cognitive Phenotypes.
Mapping Actuarial Criteria for Parkinson's Disease-Mild Cognitive Impairment onto Data-Driven Cognitive Phenotypes.
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DOI：
10.3390/brainsci12010054
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发表时间：
2021-12-30
期刊：
影响因子：
3.3
通讯作者：
Bowers D
中科院分区：
文献类型：
--
作者：
Kenney LE;Ratajska AM;Lopez FV;Price CC;Armstrong MJ;Bowers D
帕金森病（PD-MCI）中轻度认知障碍的患病率仍然不稳定，这模糊了诊断对更大痴呆风险的预测效用。这种可变性的一个主要因素是认知障碍的规范截断不一致的操作化。我们的目的是通过将分类与数据驱动的PD认知表型进行比较，确定将个体分类为PD- mci的最佳截止点。特发性PD患者（n = 494，平均年龄64.7±9岁）完成了全面的神经心理测试。聚类分析（K-means, Hierarchical）使用特定领域的复合材料确定认知表型。在一个域内进行≥2次试验时，使用单独的截止值（- 1,- 1.5,- 2 SD）评估PD-MCI标准。使用PD-MCI患病率、MCI亚型频率（单/多域、执行功能(EF)/非EF损伤）和针对集群衍生认知表型的有效性（使用卡方检验/二元逻辑回归）来比较截止值。聚类分析得出了类似的三聚类解决方案：认知平均（n = 154），低EF （n = 227）和显著EF/记忆障碍（n = 113）。- 1.5 SD截断产生了最佳的聚类隶属度模型（PD-MCI分类准确率= 87.9%），并导致PD-MCI分类与包含更大痴呆风险相关的损伤的经验认知特征之间的最佳一致性。与之前的阿尔茨海默病研究类似，这些研究结果强调了比较经验和精算方法来建立PD认知障碍并发有效性的效用。
Prevalence rates for mild cognitive impairment in Parkinson’s disease (PD-MCI) remain variable, obscuring the diagnosis’ predictive utility of greater dementia risk. A primary factor of this variability is inconsistent operationalization of normative cutoffs for cognitive impairment. We aimed to determine which cutoff was optimal for classifying individuals as PD-MCI by comparing classifications against data-driven PD cognitive phenotypes. Participants with idiopathic PD (n = 494; mean age 64.7 ± 9) completed comprehensive neuropsychological testing. Cluster analyses (K-means, Hierarchical) identified cognitive phenotypes using domain-specific composites. PD-MCI criteria were assessed using separate cutoffs (−1, −1.5, −2 SD) on ≥2 tests in a domain. Cutoffs were compared using PD-MCI prevalence rates, MCI subtype frequencies (single/multi-domain, executive function (EF)/non-EF impairment), and validity against the cluster-derived cognitive phenotypes (using chi-square tests/binary logistic regressions). Cluster analyses resulted in similar three-cluster solutions: Cognitively Average (n = 154), Low EF (n = 227), and Prominent EF/Memory Impairment (n = 113). The −1.5 SD cutoff produced the best model of cluster membership (PD-MCI classification accuracy = 87.9%) and resulted in the best alignment between PD-MCI classification and the empirical cognitive profile containing impairments associated with greater dementia risk. Similar to previous Alzheimer’s work, these findings highlight the utility of comparing empirical and actuarial approaches to establish concurrent validity of cognitive impairment in PD.
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DOI：
10.1002/mds.25062
发表时间：
2012-08
期刊：
Movement disorders : official journal of the Movement Disorder Society
影响因子：
--
作者：
Goldman JG;Weis H;Stebbins G;Bernard B;Goetz CG
通讯作者：
Goetz CG
影响因子：
8.6
作者：
Goldman, Jennifer G.;Holden, Samantha;Ouyang, Bichun;Bernard, Bryan;Goetz, Christopher G.;Stebbins, Glenn T.
通讯作者：
Stebbins, Glenn T.
影响因子：
14
作者：
Edmonds, Emily C.;McDonald, Carrie R.;Bondi, Mark W.
通讯作者：
Bondi, Mark W.
影响因子：
--
作者：
BENTON, AL;VARNEY, NR;HAMSHER, KD
通讯作者：
HAMSHER, KD
DOI：
10.3233/jpd-202166
发表时间：
2021
期刊：
Journal of Parkinson's disease
影响因子：
--
作者：
Crowley SJ;Banan G;Amin M;Tanner JJ;Hizel L;Nguyen P;Brumback B;Rodriguez K;McFarland N;Bowers D;Ding M;Mareci TA;Price CC
通讯作者：
Price CC