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Updated: Feb 12, 2026

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
[Disorders associated with mild cognitive impairment. Risk factors and predictors]
Manuel Antón Jiménez1, José Luis González Guerrero1
1Servicio de Geriatría, Hospital Ntra. Sra. de la Montaña, Complejo Hospitalario de Cáceres, Cáceres, España.
Abstract:
Traditionally, cognitive impairment has been associated not only with ageing itself but also with concomitant comorbidities that interact in the disease continuum from the prodromic phases. Notable among these are delirium, nutritional alterations, balance and gait, infections and even a progressive incidence of neoplasms. However, with regard to diagnosis and staging, clinicians should perhaps remain especially alert to the possibility of pharmacological iatrogeny, which is not limited to psychopharmacological treatment. Traditional risk factors for cognitive impairment and factors predictive of progression to dementia include hypertension, hyperglycaemia, hyperlipidaemia, smoking, alcohol, and metabolic syndrome. Emerging factors include atrial fibrillation, inflammation, hyperhomocysteinaemia, and heart failure. Paradoxically, prevention of risk factors such as hypotension, hypoglycaemia, bradycardia, low cardiac output and even malnutrition become more important at more advanced ages. Lastly, some cognitive variables such as memory, language and reading abilities, and some alterations in the affective sphere should also be assessed as predictive factors for mild cognitive impairment.
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