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A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
From biomarker expansion to equitable implementation in mild cognitive impairment
Mashal Khan1, Talha Khan2, Ayesha Tariq3
1Women Medical College, Abbottabad Affiliated with Khyber Medical University, Peshawar, Pakistan.
Abstract:
The expanding role of cerebrospinal fluid (CSF) biomarkers in Alzheimer's disease diagnosis represents a major shift toward biologically driven dementia care. In response to the article by Poli et al., we discuss important considerations regarding the broader implementation of CSF biomarker testing in patients with mild cognitive impairment (MCI), particularly in the era of emerging anti-amyloid therapies. While biomarker-guided approaches may improve identification of atypical or non-amnestic Alzheimer's disease presentations, widespread adoption remains limited by disparities in diagnostic infrastructure, standardized testing availability, expertise in lumbar puncture procedures, and longitudinal monitoring capacity across healthcare systems. In addition, expanded eligibility for anti-amyloid therapies introduces challenges related to patient selection, treatment accessibility, and equitable allocation of healthcare resources. Ethical considerations surrounding biomarker disclosure and prognostic uncertainty also warrant continued discussion. We emphasize the need for future studies evaluating accessibility, cost-effectiveness, and standardized patient selection frameworks to support equitable integration of biomarker-guided dementia care into routine neurological practice.
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