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Updated: Jul 15, 2026

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
Acurate diagnosis of delirium in elderly patients
Arturo Vilches Moraga1, Carlos Rodriguez-Pascual
1Hospital do Meixoeiro, Complejo Universitario de Vigo, Pontevedra, Spain. avilchesm@yahoo.co.uk
Purpose Of Review:
Delirium remains one of the most common complicating diagnoses in ailing elderly patients and a leading cause of morbidity, decreased quality of life, prolonged hospital stay, institutionalization and mortality. Despite its clinical importance and health-related costs, it often remains unrecognized or misdiagnosed. We evaluate currently available tools for the screening and diagnosis of delirium, their relevance and suitability for use in various clinical settings, as well as interobserver consistency amongst doctors and other nonclinician interviewers.
Recent Findings:
Extensive clinical trial evidence has been published recently concerning advances on the three fundamental elements of delirium assessment in elderly people: identification, severity assessment and reporting of existing predisposing and precipitating factors.
Summary:
Despite advances on the pathophysiology and recognition of delirium, its detection relies on individual clinical expertise, a high index of suspicion and repeated cognitive testing of high-risk patients. Delirium diagnosis remains a clearly underresearched area; particularly, more work is required to adapt cognitive screening tools for use by nonclinicians, to develop cost-effective biochemical and molecular diagnostic techniques and to assess the effects of divulging updated consensus guidelines.
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