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Updated: Jun 23, 2025

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
Impact of Different Diagnostic Measures on Drug Class Association with Dementia Progression Risk: A Longitudinal
Daman Preet Kaur1, Magda Bucholc2, David P Finn3
1Personalised Medicine Centre, School of Medicine, Ulster University, Altnagelvin Hospital, Derry/Londonderry, Northern Ireland, UK.
Background:
The Clinical Dementia Rating Scale Sum of Boxes (CDRSOB) score is known to be highly indicative of cognitive-functional status and is regularly employed for clinical and research purposes.
Objective:
Our aim is to determine whether CDRSOB is consistent with clinical diagnosis in evaluating drug class associations with risk of progression to mild cognitive impairment (MCI) and dementia.
Methods:
We employed weighted Cox regression analysis on longitudinal NACC data, to identify drug classes associated with disease progression risk, using clinical diagnosis and CDRSOB as the outcome.
Results:
Aspirin (antiplatelet/NSAID), angiotensin II inhibitors (antihypertensive), and Parkinson's disease medications were significantly associated with reduced risk of progression to MCI/dementia and Alzheimer's disease medications were associated with increased MCI-to-Dementia progression risk with both clinical diagnosis and CDRSOB as the outcome. However, certain drug classes/subcategories, like anxiolytics, antiadrenergics, calcium (Ca2+) channel blockers, and diuretics (antihypertensives) were associated with reduced risk of disease progression, and SSRIs (antidepressant) were associated with increased progression risk only with CDRSOB. Additionally, metformin (antidiabetic medication) was associated with reduced MCI-to-Dementia progression risk only with clinical diagnosis as the outcome.
Conclusions:
Although the magnitude and direction of the effect were primarily similar for both diagnostic outcomes, we demonstrate that choice of diagnostic measure can influence the significance of risk/protection attributed to drug classes and consequently the conclusion of findings. A consensus must be reached within the research community with respect to the most accurate diagnostic outcome to identify risk and improve reproducibility.
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