Educational bias in the assessment of severe dementia: Brazilian cutoffs for severe Mini-Mental State Examination.

Arq Neuropsiquiatr

Departamento de Medicina Comportamental, Departamento de Neurologia e Neurocirurgia, Universidade Federal de São Paulo, São Paulo, Brazil.

Published: April 2014

Unlabelled: Cognitive assessment in advanced stages of Alzheimer's disease (AD) is limited by the imprecision of most instruments.

Objective: To determine objective cognitive responses in moderate and severe AD patients by way of the Severe Mini-Mental State Examination (SMMSE), and to correlate performances with Mini-Mental State Examination (MMSE) scores.

Method: Consecutive outpatients in moderate and severe stages of AD (Clinical Dementia Rating 2.0 or 3.0) were evaluated and compared according to MMSE and SMMSE scores.

Results: Overall 400 patients were included, 67.5% females, mean age 76.6±6.7 years-old. There was no significant impact of age or gender over MMSE or SMMSE scores. Mean schooling was 4.4±2.5 years, impacting SMMSE scores (p=0.008). Scores on MMSE and SMMSE were significantly correlated (F-ratio=690.6325, p<0.0001).

Conclusion: The SMMSE is influenced by schooling, but not by age or gender, and is an accurate test for assessment of moderate and severe AD.

Download full-text PDF

Source
http://dx.doi.org/10.1590/0004-282x20140002DOI Listing

Publication Analysis

Top Keywords

mini-mental state
12
state examination
12
mmse smmse
12
severe mini-mental
8
moderate severe
8
smmse scores
8
severe
5
smmse
5
educational bias
4
bias assessment
4

Similar Publications

Disruptions in cognitive function have been reported in individuals undergoing haemodialysis and those with chronic kidney disease. This pilot study protocol primarily assesses the feasibility and acceptability of using mobile cognitive gaming apps for patient-led cognitive training during haemodialysis sessions. The protocol consists of three phases: (1) reviewing and evaluating available cognitive gaming apps, (2) conducting focus groups/interviews with people with kidney disease to determine app preferences, and (3) undertaking a quasi-experimental randomised controlled trial to compare cognitive outcomes between a patient-led app intervention group and a standard care control group over four months.

View Article and Find Full Text PDF

Rapid Cognitive Deterioration in Progressive Supranuclear Palsy: A 1-Year Follow-Up Study.

Mov Disord Clin Pract

December 2024

Department of Neurology, National Clinical Research Center for Aging and Medicine, & National Center for Neurological Disorders, Huashan Hospital, Fudan University, Shanghai, China.

Background: Nowadays, cognitive impairment has been characterized as one of the most vital clinical symptoms in progressive supranuclear palsy (PSP).

Objectives: Based on a relatively large cohort, we aimed to show the cognitive deterioration in different PSP subtypes during 1-year follow-up and investigate potential contributors for disease prognosis.

Methods: One hundred seventeen patients from Progressive Supranuclear Palsy Neuroimage Initiative (PSPNI) cohort underwent neuropsychological tests and 1-year follow-up, with 73 diagnosed as PSP-Richardson syndrome (PSP-RS) and 44 as PSP-non-RS.

View Article and Find Full Text PDF

Background The maintenance of cognitive health depends on thyroid hormones, and it is becoming more widely acknowledged that thyroid hormone issues may be a factor in cognitive decline in the aged. Objective This study aimed to investigate the association between thyroid hormone levels and cognitive decline among elderly individuals, considering the influence of age-related factors and comorbidities. Methodology Over the course of two years, 218 adults 60 years of age and older with clinically diagnosed hypothyroidism or subclinical thyroid disease were included in a prospective observational research.

View Article and Find Full Text PDF

Explainable machine learning on clinical features to predict and differentiate Alzheimer's progression by sex: Toward a clinician-tailored web interface.

J Neurol Sci

December 2024

Computational and Translational Neuroscience Laboratory, Institute of Cognitive Sciences and Technologies, National Research Council (CTNLab-ISTC-CNR), Via Gian Domenico Romagnosi 18A, Rome 00196, Italy; AI2Life s.r.l., Innovative Start-Up, ISTC-CNR Spin-Off, Via Sebino 32, Rome 00199, Italy. Electronic address:

Alzheimer's disease (AD), the most common neurodegenerative disorder world-wide, presents sex-specific differences in its manifestation and progression, necessitating personalized diagnostic approaches. Current procedures are often costly and invasive, lacking consideration of sex-based differences. This study introduces an explainable machine learning (ML) system to predict and differentiate the progression of AD based on sex, using non-invasive, easily collectible predictors such as neuropsychological test scores and sociodemographic data, enabling its application in every day clinical settings.

View Article and Find Full Text PDF

Aim: The overarching aim of this study was to explore patients' falls risk awareness in hospitals using section A of the validated Self Awareness of Falls Risk Measure (SAFRM).

Design: Descriptive cross-sectional study design.

Setting: Three rural/regional hospitals in the State of Victoria, Australia.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!