运用系统动力学模拟阿尔茨海默病的多因果关系。
Simulating the multicausality of Alzheimer's disease with system dynamics.
机构信息
Department of Geriatric Medicine, Radboudumc Alzheimer Center, Donders Institute for Medical Neuroscience, Radboud University Medical Center, Nijmegen, The Netherlands.
Institute for Advanced Study, University of Amsterdam, Amsterdam, The Netherlands.
出版信息
Alzheimers Dement. 2023 Jun;19(6):2633-2654. doi: 10.1002/alz.12923. Epub 2023 Feb 16.
INTRODUCTION
In Alzheimer's disease (AD), cognitive decline is driven by various interlinking causal factors. Systems thinking could help elucidate this multicausality and identify opportune intervention targets.
METHODS
We developed a system dynamics model (SDM) of sporadic AD with 33 factors and 148 causal links calibrated with empirical data from two studies. We tested the SDM's validity by ranking intervention outcomes on 15 modifiable risk factors to two sets of 44 and 9 validation statements based on meta-analyses of observational data and randomized controlled trials, respectively.
RESULTS
The SDM answered 77% and 78% of the validation statements correctly. Sleep quality and depressive symptoms yielded the largest effects on cognitive decline with which they were connected through strong reinforcing feedback loops, including via phosphorylated tau burden.
DISCUSSION
SDMs can be constructed and validated to simulate interventions and gain insight into the relative contribution of mechanistic pathways.
简介
在阿尔茨海默病（AD）中，认知能力下降是由各种相互关联的因果因素驱动的。系统思维可以帮助阐明这种多因果关系，并确定适当的干预目标。
方法
我们使用来自两项研究的实证数据，开发了一个具有 33 个因素和 148 个因果关系的散发性 AD 的系统动力学模型（SDM）。我们通过对 15 个可改变的风险因素进行干预结果排名，对两个基于观察性数据和随机对照试验的荟萃分析的 44 个和 9 个验证语句的 SDM 进行了有效性测试。
结果
SDM 正确回答了 77%和 78%的验证语句。睡眠质量和抑郁症状对认知能力下降的影响最大，它们通过强大的增强反馈循环相互连接，包括通过磷酸化 tau 负担。
讨论
可以构建和验证 SDM 来模拟干预措施，并深入了解机制途径的相对贡献。
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