Multi-time-point data preparation robustly reveals MCI and dementia risk factors.
Multi-time-point data preparation robustly reveals MCI and dementia risk factors.
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多时间数据准备鲁棒性揭示了MCI和痴呆症风险因素。
DOI：
10.1002/dad2.12116
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发表时间：
2020
期刊：
影响因子：
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通讯作者：
McClean PL
中科院分区：
文献类型：
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作者：
Kaur D;Bucholc M;Finn DP;Todd S;Wong-Lin K;McClean PL
关于痴呆症风险因素的预测结果已经在多项研究中报告。我们推测，数据准备方法的变化可能部分导致这个问题。我们提出了一种全面的数据准备方法，将随着时间的推移诊断稳定的个体与进展为轻度认知障碍（MCI）/痴呆的个体进行比较。这与常用的“基线”分析进行了比较。采用多因素Logistic回归分析评价两种方法。从敏感性分析获得的结果与我们的多时间点数据准备方法一致，显示了其稳健性。与仅使用基线数据的分析相比，进展分析中确定的显著风险因素数量显著减少。此外，我们发现中度抑郁增加了健康到MCI/痴呆的风险，而高血压降低了MCI到痴呆的风险。总体而言，基于多时间点的数据准备方法可能为更好地了解痴呆症风险因素铺平道路，并解决该领域的一些可重复性问题。
Conflicting results on dementia risk factors have been reported across studies. We hypothesize that variation in data preparation methods may partially contribute to this issue. We propose a comprehensive data preparation approach comparing individuals with stable diagnosis over time to those who progress to mild cognitive impairment (MCI)/dementia. This was compared to the often‐used “baseline” analysis. Multivariate logistic regression was used to evaluate both methods. The results obtained from sensitivity analyses were consistent with those from our multi‐time‐point data preparation approach, exhibiting its robustness. Compared to analysis using only baseline data, the number of significant risk factors identified in progression analyses was substantially lower. Additionally, we found that moderate depression increased healthy‐to‐MCI/dementia risk, while hypertension reduced MCI‐to‐dementia risk. Overall, multi‐time‐point–based data preparation approaches may pave the way for a better understanding of dementia risk factors, and address some of the reproducibility issues in the field.