Division of Geriatric Psychiatry & Center of Excellence for Alzheimer's Disease, SUNY Downstate Health Sciences University, Brooklyn, NY, USA.
Emeritus, New York University Langone Health, New York, NY, USA.
Int Psychogeriatr. 2024 Mar;36(3):200-209. doi: 10.1017/S1041610222000047. Epub 2022 Mar 25.
The literature on Alzheimer's disease (AD) provides little data about long-term cognitive course trajectories. We identify global cognitive outcome trajectories and associated predictor variables that may inform clinical research and care.
Data derived from the National Alzheimer's Coordinating Center (NACC) Uniform Data Set were used to examine the cognitive course of persons with possible or probable AD, a Mini-Mental State Examination (MMSE) of ≥10, and complete annual assessments for 5 years.
Thirty-six Alzheimer's Disease Research Centers.
Four hundred and fourteen persons.
We used a hybrid approach comprising qualitative analysis of MMSE trajectory graphs that were operationalized empirically and binary logistic regression analyses to assess 19 variables' associations with each trajectory. MMSE scores of ±3 points or greater were considered clinically meaningful.
Five distinct cognitive trajectories were identified: fast decliners (32.6%), slow decliners (30.7%), zigzag stable (15.9%), stable (15.9%), and improvers (4.8%). The decliner groups had three subtypes: curvilinear, zigzag, and late decline. The fast decliners were associated with female gender, lower baseline MMSE scores, a shorter illness duration, or receiving a cognitive enhancer. An early MMSE decline of ≥3 points predicted a worse outcome. A higher rate of traumatic brain injury, the absence of an ApoE ϵ4 allele, and male gender were the strongest predictors of favorable outcomes.
Our hybrid approach revealed five distinct cognitive trajectories and a variegated pattern within the decliners and stable/improvers that was more consistent with real-world clinical experience than prior statistically modeled studies. Future investigations need to determine the consistency of the distribution of these categories across settings.
关于阿尔茨海默病(AD)的文献很少提供关于长期认知过程轨迹的数据。我们确定了整体认知结果轨迹和相关预测变量,这些信息可能为临床研究和护理提供依据。
使用国家阿尔茨海默病协调中心(NACC)统一数据集的数据来检查可能或可能患有 AD、简易精神状态检查(MMSE)≥10 分且完成 5 年完整年度评估的人的认知过程。
36 个阿尔茨海默病研究中心。
414 人。
我们使用混合方法,包括对 MMSE 轨迹图的定性分析,这些轨迹图是通过经验操作化的,以及二项逻辑回归分析,以评估 19 个变量与每个轨迹的关联。MMSE 评分相差±3 分被认为具有临床意义。
确定了五种不同的认知轨迹:快速下降者(32.6%)、缓慢下降者(30.7%)、曲折稳定者(15.9%)、稳定者(15.9%)和改善者(4.8%)。下降者群体有三种亚型:曲线型、曲折型和晚期下降型。快速下降者与女性性别、较低的基线 MMSE 评分、较短的病程或接受认知增强剂有关。早期 MMSE 下降≥3 分预示着更差的结果。较高的创伤性脑损伤发生率、缺乏 ApoE ϵ4 等位基因和男性性别是预后良好的最强预测因素。
我们的混合方法揭示了五种不同的认知轨迹,以及下降者和稳定/改善者中多样化的模式,这比之前的统计模型研究更符合现实临床经验。未来的研究需要确定这些类别在不同环境中的分布一致性。