Dataset Information

Rate of decline in Alzheimer disease measured by a Dementia Severity Rating Scale.

ABSTRACT:

Objective

To measure clinically relevant change in Alzheimer disease (AD) using a family member-completed Dementia Severity Rating Scale (DSRS) questionnaire.

Background

Measuring rate of change provides important clinical information. Most neuropsychologic scores change nonlinearly, complicating their use as a predictor of change throughout the illness.

Methods

DSRS and Mini Mental State scores were prospectively collected on 702 patients with AD from first evaluation until they became too impaired to return to clinic.

Results

DSRS score increased an average of 4.48 points/y [95% confidence interval (CI): 4.14-4.82] throughout the entire range of severity. In contrast, the Mini Mental State declined an average of 2.15 points/y (95% CI: 1.85-2.46) during the first 2 years, accelerated to 3.83 points/y (95% CI: 3.28-4.38) during the subsequent 3 years, and then slowed to an annual decline of 1.63 points during the last 2 years (95% CI: 0.21-3.05). A younger age of symptom onset was associated with an increased rate of DSRS change (P=0.03).

Conclusions

The DSRS provides a clinical measure of functional impairment in AD that increases about 4.48 points/y from the earliest symptomatic stage until patients become too severely impaired to return to clinic.

SUBMITTER: Xie SX

PROVIDER: S-EPMC3014643 | biostudies-literature | 2009 Jul-Sep

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Rate of decline in Alzheimer disease measured by a Dementia Severity Rating Scale.

Xie Sharon X SX Ewbank Douglas C DC Chittams Jesse J Karlawish Jason H T JH Arnold Steven E SE Clark Christopher M CM

Alzheimer disease and associated disorders 20090701 3

<h4>Objective</h4>To measure clinically relevant change in Alzheimer disease (AD) using a family member-completed Dementia Severity Rating Scale (DSRS) questionnaire.<h4>Background</h4>Measuring rate of change provides important clinical information. Most neuropsychologic scores change nonlinearly, complicating their use as a predictor of change throughout the illness.<h4>Methods</h4>DSRS and Mini Mental State scores were prospectively collected on 702 patients with AD from first evaluation unti ...[more]

PMID: 19812470

Similar Datasets

Project description:Hub regions in the brain, recognized for their roles in ensuring efficient information transfer, are vulnerable to pathological alterations in neurodegenerative conditions, including Alzheimer Disease (AD). Given their essential role in neural communication, disruptions to these hubs have profound implications for overall brain network integrity and functionality. Hub disruption, or targeted impairment of functional connectivity at the hubs, is recognized in AD patients. Computational models paired with evidence from animal experiments hint at a mechanistic explanation, suggesting that these hubs may be preferentially targeted in neurodegeneration, due to their high neuronal activity levels-a phenomenon termed "activity-dependent degeneration". Yet, two critical issues were unresolved. First, past research hasn't definitively shown whether hub regions face a higher likelihood of impairment (targeted attack) compared to other regions or if impairment likelihood is uniformly distributed (random attack). Second, human studies offering support for activity-dependent explanations remain scarce. We applied a refined hub disruption index to determine the presence of targeted attacks in AD. Furthermore, we explored potential evidence for activity-dependent degeneration by evaluating if hub vulnerability is better explained by global connectivity or connectivity variations across functional systems, as well as comparing its timing relative to amyloid beta deposition in the brain. Our unique cohort of participants with autosomal dominant Alzheimer Disease (ADAD) allowed us to probe into the preclinical stages of AD to determine the hub disruption timeline in relation to expected symptom emergence. Our findings reveal a hub disruption pattern in ADAD aligned with targeted attacks, detectable even in pre-clinical stages. Notably, the disruption's severity amplified alongside symptomatic progression. Moreover, since excessive local neuronal activity has been shown to increase amyloid deposition and high connectivity regions show high level of neuronal activity, our observation that hub disruption was primarily tied to regional differences in global connectivity and sequentially followed changes observed in Aβ PET cortical markers is consistent with the activity-dependent degeneration model. Intriguingly, these disruptions were discernible 8 years before the expected age of symptom onset. Taken together, our findings not only align with the targeted attack on hubs model but also suggest that activity-dependent degeneration might be the cause of hub vulnerability. This deepened understanding could be instrumental in refining diagnostic techniques and developing targeted therapeutic strategies for AD in the future.

Project description:ObjectiveTo test the hypothesis that cortical and hippocampal volumes, measured in vivo from volumetric MRI (vMRI) scans, could be used to identify variant subtypes of Alzheimer disease (AD) and to prospectively predict the rate of clinical decline.MethodsAmyloid-positive participants with AD from the Alzheimer's Disease Neuroimaging Initiative (ADNI) 1 and ADNI2 with baseline MRI scans (n = 229) and 2-year clinical follow-up (n = 100) were included. AD subtypes (hippocampal sparing [HpSpMRI], limbic predominant [LPMRI], typical AD [tADMRI]) were defined according to an algorithm analogous to one recently proposed for tau neuropathology. Relationships between baseline hippocampal volume to cortical volume ratio (HV:CTV) and clinical variables were examined by both continuous regression and categorical models.ResultsWhen participants were divided categorically, the HpSpMRI group showed significantly more AD-like hypometabolism on 18F-fluorodeoxyglucose-PET (p < 0.05) and poorer baseline executive function (p < 0.001). Other baseline clinical measures did not differ across the 3 groups. Participants with HpSpMRI also showed faster subsequent clinical decline than participants with LPMRI on the Alzheimer's Disease Assessment Scale, 13-Item Subscale (ADAS-Cog13), Mini-Mental State Examination (MMSE), and Functional Assessment Questionnaire (all p < 0.05) and tADMRI on the MMSE and Clinical Dementia Rating Sum of Boxes (CDR-SB) (both p < 0.05). Finally, a larger HV:CTV was associated with poorer baseline executive function and a faster slope of decline in CDR-SB, MMSE, and ADAS-Cog13 score (p < 0.05). These associations were driven mostly by the amount of cortical rather than hippocampal atrophy.ConclusionsAD subtypes with phenotypes consistent with those observed with tau neuropathology can be identified in vivo with vMRI. An increased HV:CTV ratio was predictive of faster clinical decline in participants with AD who were clinically indistinguishable at baseline except for a greater dysexecutive presentation.

Dataset Information

Rate of decline in Alzheimer disease measured by a Dementia Severity Rating Scale.

Objective

Background

Methods

Results

Conclusions

Publications

Rate of decline in Alzheimer disease measured by a Dementia Severity Rating Scale.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets