Critical Comparison of Different Biomarkers for Alzheimer’s Disease in a Clinical Setting

2015 ◽  
Vol 48 (2) ◽  
pp. 425-432 ◽  
Author(s):  
David Weise ◽  
Solveig Tiepolt ◽  
Carolin Awissus ◽  
Karl-Titus Hoffmann ◽  
Donald Lobsien ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Clinical Setting ◽  
Critical Comparison

Intersite variability of CSF Alzheimer's disease biomarkers in clinical setting

2012 ◽  
Vol 9 (4) ◽  
pp. 406-413 ◽  
Author(s):  
Julien Dumurgier ◽  
Olivier Vercruysse ◽  
Claire Paquet ◽  
Stéphanie Bombois ◽  
Chloé Chaulet ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Clinical Setting ◽  
Disease Biomarkers

P4-314: Discordance Between Amyloid-PET and CSF Amyloid-β for Diagnosing Alzheimer’S Disease in a Clinical Setting

2016 ◽  
Vol 12 ◽  
pp. P1154-P1154
Author(s):  
Ellis Niemantsverdriet ◽  
Tobi Van den Bossche ◽  
Sara Van Mossevelde ◽  
Julie Ottoy ◽  
Jeroen Verhaeghe ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Clinical Setting ◽  
Amyloid Β ◽  
Amyloid Pet

Diagnosis of Preclinical Alzheimer's Disease in a Clinical Setting

2001 ◽  
Vol 13 (4) ◽  
pp. 411-423 ◽  
Author(s):  
Pieter Jelle Visser ◽  
Frans R. J. Verhey ◽  
Rudolf W. H. M. Ponds ◽  
Jellemer Jolles
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Clinical Setting ◽  
Global Deterioration Scale ◽  
Delayed Recall ◽  
Clinical Criteria ◽  
Preclinical Ad ◽  
State Examination

Introduction. The aim of the study was to investigate whether the preclinical stage of Alzheimer's disease (AD) can be diagnosed in a clinical setting. To this end we investigated whether subjects with preclinical AD could be differentiated from subjects with nonprogressive mild cognitive impairment and from subjects with very mild AD-type dementia. Methods. Twenty-three subjects with preclinical AD, 44 subjects with nonprogressive mild cognitive impairment, and 25 subjects with very mild AD-type dementia were selected from a memory clinic population. Variables that were used to differentiate the groups were demographic variables, the Mini-Mental State Examination score, performance on cognitive tests, measures of functional impairment, and measures of noncognitive symptomatology. Results. Age and the scores for the delayed recall task could best discriminate between subjects with preclinical AD and subjects with nonprogressive mild cognitive impairment. The overall accuracy was 87% The score on the Global Deterioration Scale and a measure of intelligence could best discriminate between subjects with preclinical AD and subjects with very mild AD-type dementia. The overall accuracy was 85% Conclusions. Subjects with preclinical AD can be distinguished from subjects with nonprogressive mild cognitive impairment and from subjects with very mild AD-type dementia. This means that preclinical AD is a diagnostic entity for which clinical criteria should be developed.

Donepezil in Alzheimer’s Disease: What to Expect after 3 Years of Treatment in a Routine Clinical Setting

2006 ◽  
Vol 23 (3) ◽  
pp. 150-160 ◽  
Author(s):  
Åsa K. Wallin ◽  
Niels Andreasen ◽  
Sture Eriksson ◽  
Stellan Båtsman ◽  
Birgitta Näsman ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Clinical Setting ◽  
Routine Clinical Setting

scholarly journals The Cerebrospinal Fluid Aβ1–42/Aβ1–40 Ratio Improves Concordance with Amyloid-PET for Diagnosing Alzheimer’s Disease in a Clinical Setting

2017 ◽  
Vol 60 (2) ◽  
pp. 561-576 ◽  
Author(s):  
Ellis Niemantsverdriet ◽  
Julie Ottoy ◽  
Charisse Somers ◽  
Ellen De Roeck ◽  
Hanne Struyfs ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cerebrospinal Fluid ◽  
Clinical Setting ◽  
Amyloid Pet

scholarly journals Inter-Cohort Validation of SuStaIn Model for Alzheimer’s Disease

2021 ◽  
Vol 4 ◽  
Author(s):  
Damiano Archetti ◽  
Alexandra L. Young ◽  
Neil P. Oxtoby ◽  
Daniel Ferreira ◽  
Gustav Mårtensson ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Clinical Setting ◽  
Neurodegenerative Disorder ◽  
Amyloid Β ◽  
Research Data ◽  
Training Set ◽  
Cross Sectional ◽  
Data Set ◽  
Test Sets

Alzheimer’s disease (AD) is a neurodegenerative disorder which spans several years from preclinical manifestations to dementia. In recent years, interest in the application of machine learning (ML) algorithms to personalized medicine has grown considerably, and a major challenge that such models face is the transferability from the research settings to clinical practice. The objective of this work was to demonstrate the transferability of the Subtype and Stage Inference (SuStaIn) model from well-characterized research data set, employed as training set, to independent less-structured and heterogeneous test sets representative of the clinical setting. The training set was composed of MRI data of 1043 subjects from the Alzheimer’s disease Neuroimaging Initiative (ADNI), and the test set was composed of data from 767 subjects from OASIS, Pharma-Cog, and ViTA clinical datasets. Both sets included subjects covering the entire spectrum of AD, and for both sets volumes of relevant brain regions were derived from T1-3D MRI scans processed with Freesurfer v5.3 cross-sectional stream. In order to assess the predictive value of the model, subpopulations of subjects with stable mild cognitive impairment (MCI) and MCIs that progressed to AD dementia (pMCI) were identified in both sets. SuStaIn identified three disease subtypes, of which the most prevalent corresponded to the typical atrophy pattern of AD. The other SuStaIn subtypes exhibited similarities with the previously defined hippocampal sparing and limbic predominant atrophy patterns of AD. Subject subtyping proved to be consistent in time for all cohorts and the staging provided by the model was correlated with cognitive performance. Classification of subjects on the basis of a combination of SuStaIn subtype and stage, mini mental state examination and amyloid-β1-42 cerebrospinal fluid concentration was proven to predict conversion from MCI to AD dementia on par with other novel statistical algorithms, with ROC curves that were not statistically different for the training and test sets and with area under curve respectively equal to 0.77 and 0.76. This study proves the transferability of a SuStaIn model for AD from research data to less-structured clinical cohorts, and indicates transferability to the clinical setting.

scholarly journals Apolipoprotein A1 in Cerebrospinal Fluid Is Insufficient to Distinguish Alzheimer’s Disease from Other Dementias in a Naturalistic, Clinical Setting

2020 ◽  
Vol 4 (1) ◽  
pp. 15-19 ◽  
Author(s):  
Nicolai Maximilian Stoye ◽  
Patrick Jung ◽  
Malena dos Santos Guilherme ◽  
Johannes Lotz ◽  
Andreas Fellgiebel ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cerebrospinal Fluid ◽  
Clinical Setting ◽  
Apolipoprotein A1
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