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A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
Study protocol for identification of patients with risk of cognitive impairment in advanced pharmaceutical care in a
Zuzana Macekova1, Michaela Krivosova2, Nikola Hudakova3
1Department of Pharmacy and Social Pharmacy, University of Veterinary Medicine and Pharmacy in Kosice, Kosice, Slovakia.
Introduction:
Cognitive impairment (CI) is a growing public health problem. Our study is based on the fact that cognitive assessment in community pharmacy focused on early identification of undiagnosed CI has received limited attention. As pharmacists are the most accessible health professionals due to the availability of community pharmacies to the public, they have the potential to bring improvement in this area. Early identification of at-risk patients with CI by performing cognitive testing within advanced pharmaceutical care may improve the availability of targeted physician-indicated treatment.
Methods And Analysis:
The study is a multicentric study that will include cognitive screening within pharmaceutical care. We will use the Slovak version of the short form of the Montreal Cognitive Assessment (s-MoCA) test. Study participants will be at-risk patients undergoing cognitive screening in community pharmacies. Secondarily, we will evaluate the risk factors related to CI, such as at-risk medication use and modifiable dementia risk factors (e.g., cardiovascular and mental comorbidities, aging, and lifestyle habits).
Ethics And Dissemination:
This study was approved by the Ethics Committee of the Faculty of Pharmacy, Comenius University Bratislava (Ethics Committee Statement 01/2024). All procedures follow the relevant guidelines and regulations and the Declaration of Helsinki.
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