P1-303: ALZHEIMER'S DISEASE PREDICTION IN AT-RISK PATIENTS: STATISTICALLY PREDICTING DISEASE ONSET

2006 ◽  
Vol 14 (7S_Part_7) ◽  
pp. P406-P406
Author(s):  
Saloni Shah
CNS Spectrums ◽  
2008 ◽  
Vol 13 (S3) ◽  
pp. 7-10 ◽  
Author(s):  
Steven T. DeKosky

Alzheimer's disease (AD) is a progressive disorder in which neurodegeneration begins decades before clinical symptoms appear. Detecting AD during this preclinical phase presents both the enormous challenge of identifying at-risk patients prior to symptom onset and the potential reward of treating patients early enough to prevent or slow disease progression. Given that a 5-year delay in the onset of the clinical manifestations of AD could result in almost a 50% reduction in disease prevalence, early detection of AD is a major focus of clinical research. Several objective, measurable indicators of preclinical and clinical characteristics of AD are currently available or in development. These biomarkers are promising because they promote identification of individuals at risk for AD onset and disease progression; diagnostic accuracy and treatment during the early stages of AD; and the development of disease-modifying therapies that may potentially slow or prevent disease progression during the preclinical phase of AD.


Author(s):  
A.M. Fosnacht ◽  
S. Patel ◽  
C. Yucus ◽  
A. Pham ◽  
E. Rasmussen ◽  
...  

Background: Alzheimer’s disease and aging brain disorders are progressive, often fatal neurodegenerative diseases. Successful aging, modern lifestyles and behaviors have combined to result in an expected epidemic. Risks for these diseases include genetic, medical, and lifestyle factors; over 20 modifiable risks have been reported. Objectives: We aim to primarily prevent Alzheimer’s disease and related disorders through electronic medical record (EMR)-based screening, risk assessments, interventions, and surveillance. Design: We identified modifiable risks; developed human, systems and infrastructural resources; developed interventions; and targeted at-risk groups for the intervention. Setting: A Community Based Health System. Participants: In year one (June 2015 to May 2016), 133 at-risk patients received brain health services with the goal of delaying or preventing Alzheimer’s disease and related disorders. Measurements: We created mechanisms to identify patients at high risk of neurodegenerative disease; EMR-based structured clinical documentation support tools to evaluate risk factors and history; evidence-based interventions to modify risk; and the capacity for annual surveillance, pragmatic trials, and practice-based and genomic research using the EMR. Results: This paper describes our Center for Brain Health, our EMR tools, and our first year of healthy but at-risk patients. Conclusion: We are translating research into primary prevention of Alzheimer’s disease and related disorders in our health system and aim to shift the paradigm in Neurology from brain disease to brain health.


2021 ◽  
Vol 29 (4) ◽  
pp. S51
Author(s):  
Andrew Dissanayake ◽  
Cristopher R. Bowie ◽  
Meryl A. Butters ◽  
Alastair Flint ◽  
Damien Gallagher ◽  
...  

2012 ◽  
Vol 8 (4S_Part_9) ◽  
pp. P340-P340
Author(s):  
Marco Lorenzi ◽  
Giovanni Frisoni ◽  
Nicholas Ayache ◽  
Xavier Pennec

2012 ◽  
Vol 32 (1) ◽  
pp. 147-156 ◽  
Author(s):  
Whitney Wharton ◽  
James H. Stein ◽  
Claudia Korcarz ◽  
Jane Sachs ◽  
Sandra R. Olson ◽  
...  

2017 ◽  
Vol 37 (38) ◽  
pp. 9207-9221 ◽  
Author(s):  
Santiago V. Salazar ◽  
Christopher Gallardo ◽  
Adam C. Kaufman ◽  
Charlotte S. Herber ◽  
Laura T. Haas ◽  
...  

2000 ◽  
Vol 343 (7) ◽  
pp. 450-456 ◽  
Author(s):  
Susan Y. Bookheimer ◽  
Magdalena H. Strojwas ◽  
Mark S. Cohen ◽  
Ann M. Saunders ◽  
Margaret A. Pericak-Vance ◽  
...  

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