Profiles of Mild Cognitive Impairment (MCI) in the Elderly

2015 ◽  
Vol 18 ◽  
Author(s):  
Herminia Peraita ◽  
José Chacón ◽  
Carmen Díaz-Mardomingo ◽  
Rosario Martínez-Arias
Keyword(s):  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Latent Class ◽  
The Elderly ◽  
Response Patterns ◽  
Cognitive Profiles ◽  
Group Assignment ◽  
Neuropsychological Assessments ◽  
The Stability

AbstractWe applied latent class analysis (LCA) to a set of neuropsychological data with the aim of corroborating the three cognitive profiles of mild cognitive impairment (MCI) described in the literature, namely: healthy, amnestic, non-amnestic, and multidomain. The ultimate purpose of the LCA was to try to find the underlying classification of MCI and related pathologies by means of the participants’ response patterns, rather than on more classical psychometric criteria, such as the standard deviation of the mean. We computed 547 neuropsychological assessments derived from 223 participants who were assessed annually for three consecutive years. The battery included tests of memory, language, executive function, and praxis. The results obtained by means of LCA, with a four-group solution and using the 40th percentile as the criterion, confirm prior classifications obtained with more questionable psychometric criteria, while providing longitudinal data on the course of MCI and the stability of group assignment over time.

Easy Screening for Mild Alzheimer's Disease and Mild Cognitive Impairment from Elderly Speech

2018 ◽  
Vol 15 (2) ◽  
pp. 104-110 ◽  
Author(s):  
Shohei Kato ◽  
Akira Homma ◽  
Takuto Sakuma
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Characteristic Curve ◽  
Linear Regression Analysis ◽  
Speech Sound ◽  
The Elderly ◽  
Speech Sounds ◽  
Mel Frequency Cepstral Coefficients

Objective: This study presents a novel approach for early detection of cognitive impairment in the elderly. The approach incorporates the use of speech sound analysis, multivariate statistics, and data-mining techniques. We have developed a speech prosody-based cognitive impairment rating (SPCIR) that can distinguish between cognitively normal controls and elderly people with mild Alzheimer's disease (mAD) or mild cognitive impairment (MCI) using prosodic signals extracted from elderly speech while administering a questionnaire. Two hundred and seventy-three Japanese subjects (73 males and 200 females between the ages of 65 and 96) participated in this study. The authors collected speech sounds from segments of dialogue during a revised Hasegawa's dementia scale (HDS-R) examination and talking about topics related to hometown, childhood, and school. The segments correspond to speech sounds from answers to questions regarding birthdate (T1), the name of the subject's elementary school (T2), time orientation (Q2), and repetition of three-digit numbers backward (Q6). As many prosodic features as possible were extracted from each of the speech sounds, including fundamental frequency, formant, and intensity features and mel-frequency cepstral coefficients. They were refined using principal component analysis and/or feature selection. The authors calculated an SPCIR using multiple linear regression analysis. Conclusion: In addition, this study proposes a binary discrimination model of SPCIR using multivariate logistic regression and model selection with receiver operating characteristic curve analysis and reports on the sensitivity and specificity of SPCIR for diagnosis (control vs. MCI/mAD). The study also reports discriminative performances well, thereby suggesting that the proposed approach might be an effective tool for screening the elderly for mAD and MCI.

scholarly journals Using a Digital Neuro Signature to measure longitudinal individual-level change in Alzheimer’s disease: the Altoida large cohort study

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Irene B. Meier ◽  
Max Buegler ◽  
Robbert Harms ◽  
Azizi Seixas ◽  
Arzu Çöltekin ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Disease Risk ◽  
Intraindividual Variability ◽  
Cognitive Test ◽  
Individual Level ◽  
Level Change ◽  
Neuropsychological Assessments

AbstractConventional neuropsychological assessments for Alzheimer’s disease are burdensome and inaccurate at detecting mild cognitive impairment and predicting Alzheimer’s disease risk. Altoida’s Digital Neuro Signature (DNS), a longitudinal cognitive test consisting of two active digital biomarker metrics, alleviates these limitations. By comparison to conventional neuropsychological assessments, DNS results in faster evaluations (10 min vs 45–120 min), and generates higher test-retest in intraindividual assessment, as well as higher accuracy at detecting abnormal cognition. This study comparatively evaluates the performance of Altoida’s DNS and conventional neuropsychological assessments in intraindividual assessments of cognition and function by means of two semi-naturalistic observational experiments with 525 participants in laboratory and clinical settings. The results show that DNS is consistently more sensitive than conventional neuropsychological assessments at capturing longitudinal individual-level change, both with respect to intraindividual variability and dispersion (intraindividual variability across multiple tests), across three participant groups: healthy controls, mild cognitive impairment, and Alzheimer’s disease. Dispersion differences between DNS and conventional neuropsychological assessments were more pronounced with more advanced disease stages, and DNS-intraindividual variability was able to predict conversion from mild cognitive impairment to Alzheimer’s disease. These findings are instrumental for patient monitoring and management, remote clinical trial assessment, and timely interventions, and will hopefully contribute to a better understanding of Alzheimer’s disease.

scholarly journals Mild Cognitive Impairment in Clinical Practice: A Review Article

2018 ◽  
Vol 33 (8) ◽  
pp. 500-507 ◽  
Author(s):  
Sukanya Jongsiriyanyong ◽  
Panita Limpawattana
Keyword(s):  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Cognitive Decline ◽  
Preventive Intervention ◽  
Lifestyle Modification ◽  
The Elderly ◽  
Vascular Cognitive Impairment ◽  
Review Article ◽  
Subjective Cognitive Impairment ◽  
Rate Of Progression

The spectrum of cognitive decline in the elderly ranges from what can be classified as normal cognitive decline with aging to subjective cognitive impairment to mild cognitive impairment (MCI) to dementia. This article reviewed the up-to-date evidence of MCI including the diagnostic criteria of MCI due to Alzheimer’s disease, vascular cognitive impairment and MCI due to Parkinson disease, management and preventive intervention of MCI. There are various etiologies of MCI, and a large number of studies have been conducted to ascertain the practical modalities of preserving cognition in predementia stages. Lifestyle modification, such as aerobic exercise, is an approved modality to preserve cognitive ability and decrease the rate of progression to dementia, as well as being recommended for frailty prevention.

scholarly journals Cognitive Profiles and Atrophy Ratings on MRI in Senior Patients With Mild Cognitive Impairment

2018 ◽  
Vol 10 ◽  
Author(s):  
Marianne M. Flak ◽  
Haakon R. Hol ◽  
Susanne S. Hernes ◽  
Linda Chang ◽  
Thomas Ernst ◽  
...  
Keyword(s):  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Cognitive Profiles ◽  
Senior Patients
Sign in / Sign up

Export Citation Format

Share Document