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Updated: Aug 19, 2025

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
Signs and symptoms method in neuropsychology: A standardized observational examination of cognitive functions can be
Pietro Davide Trimarchi1, Emma Sanfilippo2, Alessia Gallucci1
1Istituto di Ricerca e Cura a Carattere Scientifico, Fondazione Don Carlo Gnocchi.
Objective:
The present study aimed at investigating the sensitivity and specificity of the NeuroPsychological Examination (NPE), a systematic collection of cognitive signs and symptoms based on the observation of the patient's behavior during a clinical interview, in detecting Mild Cognitive Impairment (MCI).
Method:
475 participants, 208 suffering from MCI, 188 suffering from dementia and 79 subjective cognitive decline (SCD), have been assessed using NPE for the presence of signs and symptoms of cognitive impairment. Receiver operating characteristic (ROC) curve analysis and the Youden's test were used to determine the more appropriate cutoff points for the number of neuropsychological signs at the NPE that enabled to discriminate SCD from MCI, SCD from dementia and MCI from dementia. A sensitivity and specificity analysis and comparisons among the three groups were conducted.
Results:
The mean number of signs at the NPE were 1.73 for SCD, 7.98 for MCI and 12.82 for dementia. Pairwise comparisons among the three group of participants showed significant differences (SCD vs. MCI, p < .001, r = -0.66; SCD vs. dementia, p < .001, r = -0.76; MCI vs. dementia, p < .001, r = -0.44). The criterion of 3 signs at the NPE showed a sensitivity of 0.95 (95% CI [0.91, 0.97]) and a specificity of 0.76 (95% CI [0.65, 0.84]) in discriminating SCD from MCI participants.
Conclusions:
A signs and symptoms approach could be a useful tool for clinical neuropsychologists working in the field of MCI and dementia assessment. (PsycInfo Database Record (c) 2023 APA, all rights reserved).
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