Predicting Alzheimer's Disease Progression by Combining Multiple Measures

2021 ◽  
Author(s):  
Nour Zawawi ◽  
Heba Gamal Saber ◽  
Mohamed Hashem ◽  
Tarek F.Gharib
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cell Death ◽  
Early Diagnosis ◽  
Nerve Cell ◽  
Neurological Examination ◽  
Medical Data ◽  
Complex Interactions ◽  
Dementia Patients ◽  
Nerve Cell Death

Alzheimer's disease (AD) is a degenerative brain ailment that affects millions worldwide. It is the most common form of dementia. Patients with an early diagnosis of Alzheimer's disease have a strong chance of preventing additional brain damage by halting nerve cell death. At the same time, it begins to progress several years before any symptoms appear. The variety of data is the biggest problem encountered during diagnosis. Neurological examination, brain imaging, and often asked questions from his connected closed relatives are the three forms of data that a neurologist or geriatrics employs to diagnose patients. One of the biggest questions which need answering is the choice of a convenient feature. The main objective of this paper is to help neurologists or geriatricians diagnose patient conditions. It proposes a new hybrid model for features extracted from medical data. It discusses AD's early diagnosis and progression for all features considered in the diagnosis and their complex interactions. It proves to have the best accuracy when compared with the state-ofthe-art algorithm. Also, it proves to be more accurate against some recent research ideas. It got 95% in all cases, considering this work focused more on increasing the number of instances in comparison.

scholarly journals Dementia Management Act and Death Toll by Dementia Drug

2021 ◽  
Author(s):  
Jong-hoon Lee
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
South Korea ◽  
Acetylcholinesterase Inhibitors ◽  
Medical Data ◽  
Death Toll ◽  
Dementia Patients ◽  
Psychotropic Medicines ◽  
All Cause Mortality

Abstract The Dementia Management Act (DMA) came into effect on August 04 2011, South Korea. Medical data on the correlation between Alzheimer's disease (AD) and anti-AD drugs (AAD) groups were observed from 2010 to 2019. This study investigated the increase and decrease of deaths and AAD used to treat AD. It is known that psychotropic medicines should not be administered for dementia patients because they increase all-cause mortality. This study demonstrated that acetylcholinesterase inhibitors also increase the death toll when used to treat dementia.

Is it All Said for NSAIDs in Alzheimer’s Disease? Role of Mitochondrial Calcium Uptake

2018 ◽  
Vol 15 (6) ◽  
pp. 504-510 ◽  
Author(s):  
Sara Sanz-Blasco ◽  
Maria Calvo-Rodríguez ◽  
Erica Caballero ◽  
Monica Garcia-Durillo ◽  
Lucia Nunez ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cell Death ◽  
Amyloid Β ◽  
Epidemiological Data ◽  
Amyloid Β Peptide ◽  
Aβ Oligomers ◽  
Mitochondrial Potential ◽  
Disease Modifying Drugs ◽  
Definitive Evidence

Objectives: Epidemiological data suggest that non-steroidal anti-inflammatory drugs (NSAIDs) may protect against Alzheimer's disease (AD). Unfortunately, recent trials have failed in providing compelling evidence of neuroprotection. Discussion as to why NSAIDs effectivity is uncertain is ongoing. Possible explanations include the view that NSAIDs and other possible disease-modifying drugs should be provided before the patients develop symptoms of AD or cognitive decline. In addition, NSAID targets for neuroprotection are unclear. Both COX-dependent and independent mechanisms have been proposed, including γ-secretase that cleaves the amyloid precursor protein (APP) and yields amyloid β peptide (Aβ). Methods: We have proposed a neuroprotection mechanism for NSAIDs based on inhibition of mitochondrial Ca2+ overload. Aβ oligomers promote Ca2+ influx and mitochondrial Ca2+ overload leading to neuron cell death. Several non-specific NSAIDs including ibuprofen, sulindac, indomethacin and Rflurbiprofen depolarize mitochondria in the low µM range and prevent mitochondrial Ca2+ overload induced by Aβ oligomers and/or N-methyl-D-aspartate (NMDA). However, at larger concentrations, NSAIDs may collapse mitochondrial potential (ΔΨ) leading to cell death. Results: Accordingly, this mechanism may explain neuroprotection at low concentrations and damage at larger doses, thus providing clues on the failure of promising trials. Perhaps lower NSAID concentrations and/or alternative compounds with larger dynamic ranges should be considered for future trials to provide definitive evidence of neuroprotection against AD.

A Transfer Learning Approach for Early Diagnosis of Alzheimer’s Disease on MRI Images

Neuroscience ◽  
2021 ◽  
Author(s):  
Atif Mehmood ◽  
Shuyuan yang ◽  
Zhixi feng ◽  
Min wang ◽  
AL Smadi Ahmad ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Early Diagnosis ◽  
Transfer Learning ◽  
Learning Approach

scholarly journals Classifying Non-Dementia and Alzheimer’s Disease/Vascular Dementia Patients Using Kinematic, Time-Based, and Visuospatial Parameters: The Digital Clock Drawing Test

2021 ◽  
Vol 82 (1) ◽  
pp. 47-57 ◽  
Author(s):  
Anis Davoudi ◽  
Catherine Dion ◽  
Shawna Amini ◽  
Patrick J. Tighe ◽  
Catherine C. Price ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Vascular Dementia ◽  
Area Under The Curve ◽  
Clock Drawing Test ◽  
Digital Clock ◽  
Clock Drawing ◽  
Drawing Test ◽  
Dementia Patients ◽  
Optimal Area

Background: Advantages of digital clock drawing metrics for dementia subtype classification needs examination. Objective: To assess how well kinematic, time-based, and visuospatial features extracted from the digital Clock Drawing Test (dCDT) can classify a combined group of Alzheimer’s disease/Vascular Dementia patients versus healthy controls (HC), and classify dementia patients with Alzheimer’s disease (AD) versus vascular dementia (VaD). Methods: Healthy, community-dwelling control participants (n = 175), patients diagnosed clinically with Alzheimer’s disease (n = 29), and vascular dementia (n = 27) completed the dCDT to command and copy clock drawing conditions. Thirty-seven dCDT command and 37 copy dCDT features were extracted and used with Random Forest classification models. Results: When HC participants were compared to participants with dementia, optimal area under the curve was achieved using models that combined both command and copy dCDT features (AUC = 91.52%). Similarly, when AD versus VaD participants were compared, optimal area under the curve was, achieved with models that combined both command and copy features (AUC = 76.94%). Subsequent follow-up analyses of a corpus of 10 variables of interest determined using a Gini Index found that groups could be dissociated based on kinematic, time-based, and visuospatial features. Conclusion: The dCDT is able to operationally define graphomotor output that cannot be measured using traditional paper and pencil test administration in older health controls and participants with dementia. These data suggest that kinematic, time-based, and visuospatial behavior obtained using the dCDT may provide additional neurocognitive biomarkers that may be able to identify and tract dementia syndromes.

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