Interplay of physical and recognition performance using hierarchical continuous-time dynamic modeling and a dual-task training regime in Alzheimer's patients.

IF 4 Q1 CLINICAL NEUROLOGY Alzheimer''s and Dementia: Diagnosis, Assessment and Disease Monitoring Pub Date : 2024-08-26 eCollection Date: 2024-07-01 DOI:10.1002/dad2.12629
Svenja Schwarck, Manuel C Voelkle, Andreas Becke, Nancy Busse, Wenzel Glanz, Emrah Düzel, Gabriel Ziegler
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Abstract

Training studies typically investigate the cumulative rather than the analytically challenging immediate effect of exercise on cognitive outcomes. We investigated the dynamic interplay between single-session exercise intensity and time-locked recognition speed-accuracy scores in older adults with Alzheimer's dementia (N = 17) undergoing a 24-week dual-task regime. We specified a state-of-the-art hierarchical Bayesian continuous-time dynamic model with fully connected state variables to analyze the bi-directional effects between physical and recognition scores over time. Higher physical performance was dynamically linked to improved recognition (-1.335, SD = 0.201, 95% Bayesian credible interval [BCI] [-1.725, -0.954]). The effect was short-term, lasting up to 5 days (-0.368, SD = 0.05, 95% BCI [-0.479, -0.266]). Clinical scores supported the validity of the model and observed temporal dynamics. Higher physical performance predicted improved recognition speed accuracy in a day-by-day manner, providing a proof-of-concept for the feasibility of linking exercise training and recognition in patients with Alzheimer's dementia.

Highlights: Hierarchical Bayesian continuous-time dynamic modeling approachA total of 72 repeated physical exercise (PP) and integrated recognition speed-accuracy (IRSA) measurementsPP is dynamically linked to session-to-session variability of IRSAHigher PP improved IRSA in subsequent sessions in subjects with Alzheimer's dementiaShort-term effect: lasting up to 4 days after training session.

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利用分层连续时间动态建模和双任务训练机制,研究阿尔茨海默氏症患者的体能和识别能力之间的相互作用。
训练研究通常调查的是运动对认知结果的累积效应,而不是具有分析挑战性的即时效应。我们研究了对阿尔茨海默氏症痴呆症老年人(17 人)进行为期 24 周的双任务训练后,单次运动强度与时间锁定识别速度-准确性得分之间的动态相互作用。我们建立了一个最先进的分层贝叶斯连续时间动态模型,该模型具有完全关联的状态变量,用于分析随时间变化的体能和识别得分之间的双向影响。较高的体能表现与较高的识别能力动态相关(-1.335,SD = 0.201,95% 贝叶斯可信区间 [BCI] [-1.725,-0.954])。该效应是短期的,可持续 5 天(-0.368,SD = 0.05,95% 贝叶斯可信区间 [-0.479, -0.266])。临床评分证明了模型和观察到的时间动态的有效性。较高的体能表现预示着逐日提高的识别速度准确性,为将阿尔茨海默氏症痴呆患者的运动训练与识别联系起来的可行性提供了概念证明:分层贝叶斯连续时间动态建模方法共进行了 72 次重复体育锻炼(PP)和综合识别速度-准确性(IRSA)测量PP 与 IRSA 每次训练之间的变化动态相关PP 越高,阿尔茨海默氏症痴呆症受试者在随后训练中的 IRSA 就越高短期效应:训练课程结束后最多持续 4 天。
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来源期刊
CiteScore
7.80
自引率
7.50%
发文量
101
审稿时长
8 weeks
期刊介绍: Alzheimer''s & Dementia: Diagnosis, Assessment & Disease Monitoring (DADM) is an open access, peer-reviewed, journal from the Alzheimer''s Association® that will publish new research that reports the discovery, development and validation of instruments, technologies, algorithms, and innovative processes. Papers will cover a range of topics interested in the early and accurate detection of individuals with memory complaints and/or among asymptomatic individuals at elevated risk for various forms of memory disorders. The expectation for published papers will be to translate fundamental knowledge about the neurobiology of the disease into practical reports that describe both the conceptual and methodological aspects of the submitted scientific inquiry. Published topics will explore the development of biomarkers, surrogate markers, and conceptual/methodological challenges. Publication priority will be given to papers that 1) describe putative surrogate markers that accurately track disease progression, 2) biomarkers that fulfill international regulatory requirements, 3) reports from large, well-characterized population-based cohorts that comprise the heterogeneity and diversity of asymptomatic individuals and 4) algorithmic development that considers multi-marker arrays (e.g., integrated-omics, genetics, biofluids, imaging, etc.) and advanced computational analytics and technologies.
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