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Updated: May 18, 2026

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
Tools to detect delirium superimposed on dementia: a systematic review
Alessandro Morandi1, Jessica McCurley, Eduard E Vasilevskis
1Department of Rehabilitation and Aged Care, Hospital Ancelle, Cremona, Italy. morandi.alessandro@gmail.com
Objectives:
To identify valid tools to diagnose delirium superimposed on dementia.
Design:
Systematic review of studies of delirium tools that explicitly included individuals with dementia.
Setting:
Hospital.
Participants:
Studies were included if delirium assessment tools were validated against standard criteria, and the presence of dementia was assessed according to standard criteria that used validated instruments.
Measurements:
PubMed, Embase, and Web of Science databases were searched for articles in English published between January 1960 and January 2012.
Results:
Nine studies fulfilled the selection criteria. Of 1,569 participants, 401 had dementia, and 50 had delirium superimposed on dementia. Six delirium tools were evaluated. One study using the Confusion Assessment Method (CAM) with 85% of participants with dementia had high specificity (96-100%) and moderate sensitivity (77%). Two intensive care unit studies that used the CAM for the Intensive Care Unit (CAM-ICU) reported 100% sensitivity and specificity for delirium in 23 individuals with dementia. One study using electroencephalography reported sensitivity of 67% and specificity of 91% in a population with a 100% prevalence of dementia. No studies examined potential effects of dementia severity or subtype on diagnostic accuracy.
Conclusions:
The evidence base on tools for detection of delirium superimposed on dementia is limited, although some existing tools show promise. Further studies of existing or refined tools with larger samples and more-detailed characterization of dementia are required to address the identification of delirium superimposed on dementia.
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