Awareness of Self and Disease Assessment: Development and Validation of a Subjective Measure in People with Alzheimer’s Disease

2019 ◽  
Vol 71 (3) ◽  
pp. 841-850 ◽  
Author(s):  
Amandine Mayelle ◽  
Mohamad El Haj ◽  
Pascal Antoine
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Disease Assessment ◽  
Subjective Measure ◽  
Assessment Development ◽  
Development And Validation

Alzheimer's Disease Assessment Scale

1984 ◽  
Author(s):  
Wilma G. Rosen ◽  
Richard C. Mohs ◽  
Kenneth L. Davis
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Assessment Scale ◽  
Disease Assessment

Validation of the Hungarian version of Alzheimer’s Disease Assessment Scale – Cognitive Subscale

2012 ◽  
Vol 153 (12) ◽  
pp. 461-466 ◽  
Author(s):  
Magdolna Pákáski ◽  
Gergely Drótos ◽  
Zoltán Janka ◽  
János Kálmán
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Mental State ◽  
Mini Mental State Examination ◽  
Assessment Scale ◽  
Disease Assessment ◽  
Control Subjects ◽  
Cognitive Subscale ◽  
State Examination ◽  
Hungarian Version

The cognitive subscale of the Alzheimer’s Disease Assessment Scale is the most widely used test in the diagnostic and research work of Alzheimer’s disease. Aims: The aim of this study was to validate and investigate reliability of the Hungarian version of the Alzheimer’s Disease Assessment Scale in patients with Alzheimer’s disease and healthy control subjects. Methods: syxty-six patients with mild and moderate Alzheimer’s disease and 47 non-demented control subjects were recruited for the study. The cognitive status was established by the Hungarian version of the Alzheimer’s Disease Assessment Scale and Mini Mental State Examination. Discriminative validity, the relation between age and education and Alzheimer’s Disease Assessment Scale, and the sensitivity and specificity of the test were determined. Results: Both the Mini Mental State Examination and the Alzheimer’s Disease Assessment Scale had significant potential in differentiating between patients with mild and moderate stages of Alzheimer’s disease and control subjects. A very strong negative correlation was established between the scores of the Mini Mental State Examination and the Alzheimer’s Disease Assessment Scale in the Alzheimer’s disease group. The Alzheimer’s Disease Assessment Scale showed slightly negative relationship between education and cognitive performance, whereas a positive correlation between age and Alzheimer’s Disease Assessment Scale scores was detected only in the control group. According to the analysis of the ROC curve, the values of sensitivity and specificity of the Alzheimer’s Disease Assessment Scale were high. Conclusions: The Hungarian version of the Alzheimer’s Disease Assessment Scale was found to be highly reliable and valid and, therefore, the application of this scale can be recommended for the establishment of the clinical stage and follow-up of patients with Alzheimer’s disease. However, the current Hungarian version of the Alzheimer’s Disease Assessment Scale is not sufficient; the list of words and linguistic elements should be selected according to the Hungarian standard in the future. Orv. Hetil., 2012, 153, 461–466.

Deformation-based Statistical Shape Analysis of the Corpus Callosum in Mild Cognitive Impairment and Alzheimer’s Disease

2018 ◽  
Vol 15 (12) ◽  
pp. 1151-1160 ◽  
Author(s):  
Zihan Jiang ◽  
Huilin Yang ◽  
Xiaoying Tang
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Corpus Callosum ◽  
Shape Analysis ◽  
Disease Assessment ◽  
Statistical Shape Analysis ◽  
Superior Part ◽  
Statistical Shape

Objective: In this study, we investigated the influence that the pathology of Alzheimer’s disease (AD) exerts upon the corpus callosum (CC) using a total of 325 mild cognitive impairment (MCI) subjects, 155 AD subjects, and 185 healthy control (HC) subjects. Method: Regionally-specific morphological CC abnormalities, as induced by AD, were quantified using a large deformation diffeomorphic metric curve mapping based statistical shape analysis pipeline. We also quantified the association between the CC shape phenotype and two cognitive measures; the Mini Mental State Examination (MMSE) and the Alzheimer’s Disease Assessment Scale-Cognitive Behavior Section (ADAS-cog). To identify AD-relevant areas, CC was sub-divided into three subregions; the genu, body, and splenium (gCC, bCC, and sCC). Results: We observed significant shape compressions in AD relative to that in HC, mainly concentrated on the superior part of CC, across all three sub-regions. The HC-vs-MCI shape abnormalities were also concentrated on the superior part, but mainly occurred on bCC and sCC. The significant MCI-vs-AD shape differences, however, were only detected in part of sCC. In the shape-cognition association, significant negative correlations to ADAS-cog were detected for shape deformations at regions belonging to gCC and sCC and significant positive correlations to MMSE at regions mainly belonging to sCC. Conclusion: Our results suggest that the callosal shape deformation patterns, especially those of sCC, linked tightly to the cognitive decline in AD, and are potentially a powerful biomarker for monitoring the progression of AD.

A Biomarker Combining Imaging and Neuropsychological Assessment for Tracking Early Alzheimer's Disease in Clinical Trials

2018 ◽  
Vol 15 (5) ◽  
pp. 429-442 ◽  
Author(s):  
Nishant Verma ◽  
S. Natasha Beretvas ◽  
Belen Pascual ◽  
Joseph C. Masdeu ◽  
Mia K. Markey ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Clinical Trials ◽  
Cognitive Impairment ◽  
Latent Variable ◽  
Brain Regions ◽  
Disease Assessment ◽  
Latent Variable Analysis ◽  
The Relationship ◽  
Selection Of

Background: Combining optimized cognitive (Alzheimer's Disease Assessment Scale- Cognitive subscale, ADAS-Cog) and atrophy markers of Alzheimer's disease for tracking progression in clinical trials may provide greater sensitivity than currently used methods, which have yielded negative results in multiple recent trials. Furthermore, it is critical to clarify the relationship among the subcomponents yielded by cognitive and imaging testing, to address the symptomatic and anatomical variability of Alzheimer's disease. Method: Using latent variable analysis, we thoroughly investigated the relationship between cognitive impairment, as assessed on the ADAS-Cog, and cerebral atrophy. A biomarker was developed for Alzheimer's clinical trials that combines cognitive and atrophy markers. Results: Atrophy within specific brain regions was found to be closely related with impairment in cognitive domains of memory, language, and praxis. The proposed biomarker showed significantly better sensitivity in tracking progression of cognitive impairment than the ADAS-Cog in simulated trials and a real world problem. The biomarker also improved the selection of MCI patients (78.8±4.9% specificity at 80% sensitivity) that will evolve to Alzheimer's disease for clinical trials. Conclusion: The proposed biomarker provides a boost to the efficacy of clinical trials focused in the mild cognitive impairment (MCI) stage by significantly improving the sensitivity to detect treatment effects and improving the selection of MCI patients that will evolve to Alzheimer’s disease.

scholarly journals Disease progression modelling from preclinical Alzheimer’s disease (AD) to AD dementia

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Soo Hyun Cho ◽  
Sookyoung Woo ◽  
Changsoo Kim ◽  
Hee Jin Kim ◽  
Hyemin Jang ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Disease Progression ◽  
Disease Assessment ◽  
Time Interval ◽  
Disease Course ◽  
Preclinical Alzheimer’S Disease ◽  
Apoe Ε4 ◽  
Preclinical Ad ◽  
Cognitive Subscale

AbstractTo characterize the course of Alzheimer’s disease (AD) over a longer time interval, we aimed to construct a disease course model for the entire span of the disease using two separate cohorts ranging from preclinical AD to AD dementia. We modelled the progression course of 436 patients with AD continuum and investigated the effects of apolipoprotein E ε4 (APOE ε4) and sex on disease progression. To develop a model of progression from preclinical AD to AD dementia, we estimated Alzheimer’s Disease Assessment Scale-Cognitive Subscale 13 (ADAS-cog 13) scores. When calculated as the median of ADAS-cog 13 scores for each cohort, the estimated time from preclinical AD to MCI due to AD was 7.8 years and preclinical AD to AD dementia was 15.2 years. ADAS-cog 13 scores deteriorated most rapidly in women APOE ε4 carriers and most slowly in men APOE ε4 non-carriers (p < 0.001). Our results suggest that disease progression modelling from preclinical AD to AD dementia may help clinicians to estimate where patients are in the disease course and provide information on variation in the disease course by sex and APOE ε4 status.

scholarly journals Quantitative Longitudinal Predictions of Alzheimer’s Disease by Multi-Modal Predictive Learning

2021 ◽  
Vol 79 (4) ◽  
pp. 1533-1546
Author(s):  
Mithilesh Prakash ◽  
Mahmoud Abdelaziz ◽  
Linda Zhang ◽  
Bryan A. Strange ◽  
Jussi Tohka ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Prediction Models ◽  
Predictive Performance ◽  
Absolute Error ◽  
Disease Stage ◽  
Disease Assessment ◽  
Disease Category ◽  
Modal Data ◽  
Predictive Learning

Background: Quantitatively predicting the progression of Alzheimer’s disease (AD) in an individual on a continuous scale, such as the Alzheimer’s Disease Assessment Scale-cognitive (ADAS-cog) scores, is informative for a personalized approach as opposed to qualitatively classifying the individual into a broad disease category. Objective: To evaluate the hypothesis that the multi-modal data and predictive learning models can be employed for future predicting ADAS-cog scores. Methods: Unimodal and multi-modal regression models were trained on baseline data comprised of demographics, neuroimaging, and cerebrospinal fluid based markers, and genetic factors to predict future ADAS-cog scores for 12, 24, and 36 months. We subjected the prediction models to repeated cross-validation and assessed the resulting mean absolute error (MAE) and cross-validated correlation (ρ) of the model. Results: Prediction models trained on multi-modal data outperformed the models trained on single modal data in predicting future ADAS-cog scores (MAE12, 24 & 36 months= 4.1, 4.5, and 5.0, ρ12, 24 & 36 months= 0.88, 0.82, and 0.75). Including baseline ADAS-cog scores to prediction models improved predictive performance (MAE12, 24 & 36 months= 3.5, 3.7, and 4.6, ρ12, 24 & 36 months= 0.89, 0.87, and 0.80). Conclusion: Future ADAS-cog scores were predicted which could aid clinicians in identifying those at greater risk of decline and apply interventions at an earlier disease stage and inform likely future disease progression in individuals enrolled in AD clinical trials.

scholarly journals Saffron for mild cognitive impairment and dementia: a systematic review and meta-analysis of randomised clinical trials

2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Zahra Ayati ◽  
Guoyan Yang ◽  
Mohammad Hossein Ayati ◽  
Seyed Ahmad Emami ◽  
Dennis Chang
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Clinical Trials ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Cognitive Function ◽  
Daily Living ◽  
Randomised Clinical Trials ◽  
Disease Assessment ◽  
Significant Difference

Abstract Background Saffron (stigma of Crocus sativus L.) from Iridaceae family is a well-known traditional herbal medicine that has been used for hundreds of years to treat several diseases such as depressive mood, cancer and cardiovascular disorders. Recently, anti-dementia property of saffron has been indicated. However, the effects of saffron for the management of dementia remain controversial. The aim of the present study is to explore the effectiveness and safety of saffron in treating mild cognitive impairment and dementia. Methods An electronic database search of some major English and Chinese databases was conducted until 31st May 2019 to identify relevant randomised clinical trials (RCT). The primary outcome was cognitive function and the secondary outcomes included daily living function, global clinical assessment, quality of life (QoL), psychiatric assessment and safety. Rev-Man 5.3 software was applied to perform the meta-analyses. Results A total of four RCTs were included in this review. The analysis revealed that saffron significantly improves cognitive function measured by the Alzheimer’s Disease Assessment Scale-cognitive subscale (ADAS-cog) and Clinical Dementia Rating Scale-Sums of Boxes (CDR-SB), compared to placebo groups. In addition, there was no significant difference between saffron and conventional medicine, as measured by cognitive scales such as ADAS-cog and CDR-SB. Saffron improved daily living function, but the changes were not statistically significant. No serious adverse events were reported in the included studies. Conclusions Saffron may have the potential to improve cognitive function and activities of daily living in patients with Alzheimer’s disease and mild cognitive impairment (MCI). However, due to limited high-quality studies there is insufficient evidence to make any recommendations for clinical use. Further clinical trials on larger sample sizes are warranted to shed more light on its efficacy and safety.

Influence of Educational Attainment on Cognition-Based Intervention Programs for Persons with Mild Alzheimer’s Disease

2016 ◽  
Vol 22 (5) ◽  
pp. 577-582 ◽  
Author(s):  
Israel Contador ◽  
Bernardino Fernández-Calvo ◽  
Francisco Ramos ◽  
Javier Olazarán
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cognitive Decline ◽  
Effect Size ◽  
Study Groups ◽  
Total Sample ◽  
Cognitive Intervention ◽  
Potential Effect ◽  
Cognitive Status ◽  
Disease Assessment

AbstractObjectives: This research retrospectively analyzed the effect of education on cognitive interventions carried out in patients with mild Alzheimer’s disease (AD). Methods: The total sample consisted of 75 patients with mild AD receiving treatment with cholinesterase inhibitors. The participants were divided into two groups: cognitive intervention (IG; n=45) and waiting list (WLG; n=30). Patients in the IG received either the Big Brain Academy (n=15) or the Integrated Psychostimulation Program (n=30) during 12 weeks. The influence of education on intervention effect was analyzed comparing mean change scores of the two study groups in the cognitive subscale of the Alzheimer’s Disease Assessment Scale (ADAS-cog), stratified by educational level. The potential effect of age, sex, cognitive status, and type of intervention was examined using post hoc stratification analyses. Results: Higher education was associated with faster cognitive decline in the WLG (effect size=0.51; p<.01). However, cognitive evolution was not influenced by education in the IG (effect size=0.12; p=.42). Conclusions: Our results suggest that cognitive intervention might delay accelerated cognitive decline in higher educated individuals with mild AD. (JINS, 2016, 23, 1–6)

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