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Multi-time-point data preparation robustly reveals MCI and dementia risk factors.


ABSTRACT: Introduction: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. Methods: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. Results: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. Discussion: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.

SUBMITTER: Kaur D 

PROVIDER: S-EPMC7560502 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Multi-time-point data preparation robustly reveals MCI and dementia risk factors.

Kaur Daman D   Bucholc Magda M   Finn David P DP   Todd Stephen S   Wong-Lin KongFatt K   McClean Paula L PL  

Alzheimer's & dementia (Amsterdam, Netherlands) 20201014 1


<h4>Introduction</h4>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.<h4>Methods</h4>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 b  ...[more]

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