Diagnosing Alzheimer’s disease in clinical practice

2011 ◽  
Author(s):  
Gunhild Waldemar
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Substance Abuse ◽  
Cognitive Impairment ◽  
Clinical Practice ◽  
Clinical Diagnosis ◽  
Brain Diseases ◽  
Clinical Criteria ◽  
Metabolic Conditions ◽  
Symptoms And Signs

• In the current clinical criteria, the diagnosis of Alzheimer’s disease (AD) is a clinical diagnosis based on characteristic symptoms and signs, and the exclusion of other causes.• AD must be differentiated from cognitive impairment due to depression, metabolic conditions, substance abuse, and other neurodegenerative or vascular brain diseases...

Vascular Dementia: A Diagnostic Challenge

2003 ◽  
Vol 15 (S1) ◽  
pp. 111-114 ◽  
Author(s):  
Gabriel Gold
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Vascular Dementia ◽  
Clinical Diagnosis ◽  
Clinical Studies ◽  
Mixed Dementia ◽  
Diagnostic Challenge ◽  
Clinical Criteria ◽  
Clinicopathological Correlations ◽  
Broad Consensus

Although vascular dementia was described over a century ago, it remains a difficult and challenging diagnosis. Several sets of clinical criteria have been published in an effort to establish the presence or absence of vascular dementia in a standardized fashion. Clinical studies have demonstrated that they identify different groups of patients and are thus not interchangeable. Retrospective clinicopathological correlations have shown that most are insufficiently sensitive, although they are generally relatively specific. They accurately exclude pure Alzheimer's disease but may include 9% to 39% of mixed dementia cases (Alzheimer's disease and vascular dementia combined). Further studies are needed to develop better performing criteria that could lead to a broad consensus on the clinical diagnosis of vascular and mixed dementia.

scholarly journals HAVAs: Alzheimer’s Disease Detection using Normative and Pathological Lifespan Models

2021 ◽  
Author(s):  
Pierrick Coupé ◽  
José V. Manjón ◽  
Boris Mansencal ◽  
Thomas Tourdias ◽  
Gwenaëlle Catheline ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Deep Learning ◽  
Cognitive Impairment ◽  
Clinical Practice ◽  
State Of The Art ◽  
Brain Structures ◽  
Volumetric Analysis ◽  
Classification Performance

AbstractIn this paper, we present an innovative MRI-based method for Alzheimer’s Disease (AD) detection and mild cognitive impairment (MCI) prognostic, using lifespan trajectories of brain structures. After a full screening of the most discriminant structures between AD and normal aging based on MRI volumetric analysis of 3032 subjects, we propose a novel Hippocampal-Amygdalo-Ventricular Alzheimer score (HAVAs) based on normative lifespan models and AD lifespan models. During a validation on three external datasets on 1039 subjects, our approach showed very accurate detection (AUC ≥ 94%) of patients with AD compared to control subjects and accurate discrimination (AUC=78%) between progressive MCI and stable MCI (during a 3 years follow-up). Compared to normative modelling and recent state-of-the-art deep learning methods, our method demonstrated better classification performance. Moreover, HAVAs simplicity makes it fully understandable and thus well-suited for clinical practice or future pharmaceutical trials.

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.

scholarly journals New diagnostic concepts in Alzheimer's disease

2013 ◽  
Vol 19 (4) ◽  
pp. 242-249 ◽  
Author(s):  
Anna Watkin ◽  
Sudip Sikdar ◽  
Biswadeep Majumdar ◽  
Anna V. Richman
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cognitive Impairment ◽  
Clinical Practice ◽  
Mild Cognitive Impairment ◽  
Diagnostic Criteria ◽  
Current Clinical Practice ◽  
Amnestic Mci ◽  
Recent Developments

SummaryThis article gives an overview of the profile of Alzheimer's disease, its pathophysiology and recent developments in technology that enable better understanding of the mechanism of disease. The diagnostic criteria and role of biomarkers proposed are explained. The new subgroups described are outlined in table form for easy reference. Subtypes of mild cognitive impairment (MCI) are reviewed and the conversion of amnestic MCI to Alzheimer's disease is considered. The implications and change to current clinical practice form the basis of the conclusion of the article.

scholarly journals Views on Early Diagnosis of Alzheimer’s Disease Among Dutch Physicians: A Qualitative Interview Study

2020 ◽  
pp. 1-11
Author(s):  
Krista Tromp ◽  
Marthe Smedinga ◽  
Edo Richard ◽  
Marieke Perry ◽  
Maartje H.N. Schermer
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cognitive Impairment ◽  
Clinical Practice ◽  
Mild Cognitive Impairment ◽  
Early Diagnosis ◽  
Test Characteristics ◽  
Qualitative Interview Study ◽  
Diagnosis Of Dementia ◽  
Disease Concepts

Background: Hope for future treatments to prevent or slow down dementia motivates researchers to strive for ever-earlier diagnoses of Alzheimer’s disease (AD) based on biomarkers, even before symptoms occur. But is a biomarker-based early diagnosis desirable in clinical practice? Objective: This study explores the ethical considerations that shape current clinical practice regarding early AD diagnostics and the use of biomarkers. Methods: In this qualitative study, Dutch physicians were interviewed. Topics included physicians’ views concerning early AD diagnosis in persons with no or mild cognitive impairment, physicians’ considerations regarding current and expected future practices of early AD diagnosis, the use of biomarkers, and the use of the concepts preclinical and prodromal AD. We analyzed the transcripts using directed content analysis. Results: 15 general practitioners, neurologists, and geriatricians in the Netherlands were interviewed. Most of them interpreted an early AD diagnosis with an early diagnosis of dementia. We identified six clusters of considerations sometimes in favor but most often against pursuing an early AD diagnosis in people with no or mild cognitive impairment that influence physicians’ diagnostic decision-making: preferences and characteristics of persons, test characteristics, impact on care, type of setting, disease concepts, and issues on a societal level. Conclusion: The discussion concerning an early AD diagnosis based on biomarkers which is widely held in the scientific field, has not entered clinical practice structurally. A biomarker-based early diagnosis does not fit within Dutch physicians’ views on what good care for people with no, subjective, or mild cognitive impairment should entail.

scholarly journals Long-term Cognitive Impairment after Critical Illness – Definition, Incidence, Pathophysiology and Hypothesis of Neurotrophic Treatment

2015 ◽  
Vol 10 (2) ◽  
pp. 195
Author(s):  
Ignacio J Previgliano ◽  
Bader Andres ◽  
Pawel J Ciesielczyk ◽  
◽  
◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Intensive Care Unit ◽  
Intensive Care ◽  
Cognitive Impairment ◽  
Brain Injury ◽  
Critical Illness ◽  
Neurovascular Unit ◽  
Public Health Problem ◽  
Brain Diseases

Cognitive impairment after critical illness (CIACI) is a frequent consequence of serious disease or injury that has been reported in as many as 66 % of patients, 3 months after an illness requiring intensive care unit hospitalisation. The condition has been recognised only within the past 15 years and its pathological mechanisms are, as yet, incompletely understood. The neurological changes and cellular and inflammatory processes of CIACI overlap with those of stroke, traumatic brain injury and neurodegenerative disorders. Patients also show brain atrophy, which worsens with the duration of intensive care unit stay. Risk factors associated with CIACI include depression, biomarkers of Alzheimer’s disease (e.g. apolipoprotein E), delirium, exposure to some drugs (e.g. fentanyl, morphine and propofol) and intubation. Current strategies to prevent or treat CIACI include treatments to reduce agitation and delirium and physical and mental rehabilitation including cognitive therapy. Many brain diseases and injuries affect the functioning of the neurovascular unit (NVU), which constitutes the key cellular building block of the blood–brain barrier (BBB). CIACI is believed to affect the integrity of the NVU and it is among the potential targets for therapy. Neurotrophic factors (NTFs), such as brain-derived neurotrophic factor (BDNF) are known to play an important role in neurogenesis, maintenance of NVU structure and neuronal repair after disease and injury. This led to the development of strategies including the NTF-preparation (Cerebrolysin®), which is effective as a post-stroke therapy and has potential in the treatment of Alzheimer’s disease and brain injury as well as CIACI. There are currently no proven treatments for CIACI; improved understanding of the condition and further evaluation of NTFs may lead to effective treatments, which are vital to tackle this increasingly serious public health problem.

Cerebrospinal fluid inflammatory markers in Alzheimer’s disease: influence of comorbidities

2021 ◽  
Vol 18 ◽  
Author(s):  
Ying Wang ◽  
Ceren Emre ◽  
Helena Gyllenhammar-Schill ◽  
Karin Fjellman ◽  
Helga Eyjolfsdottir ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cerebrospinal Fluid ◽  
Cognitive Impairment ◽  
Clinical Diagnosis ◽  
Inflammatory Factors ◽  
Training Cohort ◽  
Amyloid A ◽  
Molecular Pattern ◽  
Novel Biomarkers

Background: Alzheimer's disease (AD) develops into dementia during several years and subjective cognitive impairment (SCI) and mild cognitive impairment (MCI) are used as intermediary diagnoses of increasing severity. Inflammation is an important part of AD pathology and provides potential novel biomarkers and treatment targets. Objective: To identify novel potential biomarkers of AD in cerebrospinal fluid (CSF) and create a molecular pattern of inflammatory factors providing differentiation between AD and SCI. Methods: We analyzed 43 inflammatory-related mediators in CSF samples from a cohort of SCI and AD cases vetted for confounding factors (Training cohort). Using multivariate analysis (MVA) a model for discrimination between SCI and AD was produced which we then applied to a larger non-vetted cohort (named Test cohort). The data were analyzed for factors showing differences between diagnostic groups and factors that differed between the vetted and non-vetted cohorts. The relationship of the factors to agreement between model and clinical diagnosis was investigated. Results: A good MVA model able to discriminate AD from SCI without including tangle and plaque biomarkers was produced from the Training cohort. The model showed 50% agreement with clinical diagnosis in the Test cohort. Comparison of the cohorts indicated different patterns of factors distinguishing SCI from AD. As an example, soluble interleukin (IL)-6R showed lower levels in AD cases in the Training cohort, whereas placental growth factor (PlGF) and serum amyloid A (SAA) levels were higher in AD cases of the Test cohort. The levels of p-tau were also higher in the Training cohort. Conclusion: This study provides new knowledge regarding the involvement of inflammation in AD by indicating different patterns of factors in CSF depending on if potential confounding comorbidities are present or not, and presents sIL-6R as a potential new biomarker for improved diagnosis of AD.

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