Apolipoprotein E genotype predicts subarachnoid extension in spontaneous intracerebral haemorrhage

2021 ◽  
Author(s):  
Xiaodong Ye ◽  
Guo Li ◽  
Xiaoyan Liu ◽  
Guini Song ◽  
Yuchao Jia ◽  
...  
Keyword(s):  
Apolipoprotein E ◽  
Intracerebral Haemorrhage ◽  
Spontaneous Intracerebral Haemorrhage ◽  
Apolipoprotein E Genotype

Effect of apolipoprotein E genotype on in-hospital mortality following intracerebral haemorrhage

2003 ◽  
Vol 107 (2) ◽  
pp. 106-109 ◽  
Author(s):  
M. O. McCarron ◽  
C. J. Weir ◽  
K. W. Muir ◽  
K. L. Hoffmann ◽  
C. Graffagnino ◽  
...  
Keyword(s):  
Hospital Mortality ◽  
Apolipoprotein E ◽  
Intracerebral Haemorrhage ◽  
Apolipoprotein E Genotype

Early administration of low molecular weight heparin after spontaneous intracerebral haemorrhage: a safety analysis

2008 ◽  
Vol 35 (S 01) ◽  
Author(s):  
B Huttner ◽  
C Kanter ◽  
D Staykov ◽  
M Köhrmann ◽  
T Struffert ◽  
...  
Keyword(s):  
Molecular Weight ◽  
Intracerebral Haemorrhage ◽  
Low Molecular Weight Heparin ◽  
Safety Analysis ◽  
Low Molecular Weight ◽  
Early Administration ◽  
Spontaneous Intracerebral Haemorrhage

Age Modifies the Association Between Apolipoprotein E Genotype and Alzheimer's Disease: A CSF Biomarker-Based Multicentric Case-Control Study

2019 ◽  
Author(s):  
Hana Sadikki ◽  
Aurore Fayosse ◽  
Emmanuel Cognat ◽  
Séverine Sabia ◽  
Sebastiaan Engelborghs ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Apolipoprotein E ◽  
Case Control Study ◽  
Case Control ◽  
Csf Biomarker ◽  
Control Study ◽  
Apolipoprotein E Genotype

Endoscopic management of spontaneous intracerebral haemorrhage

2020 ◽  
Vol 0 (0) ◽  
pp. 0-0
Author(s):  
Raed Elabd ◽  
Hamdy Behairy ◽  
Sherif Ezzat
Keyword(s):  
Intracerebral Haemorrhage ◽  
Endoscopic Management ◽  
Spontaneous Intracerebral Haemorrhage

scholarly journals Risks of recurrent stroke and all serious vascular events after spontaneous intracerebral haemorrhage: pooled analyses of two population-based studies

2021 ◽  
Vol 20 (6) ◽  
pp. 437-447 ◽  
Author(s):  
Linxin Li ◽  
Michael T C Poon ◽  
Neshika E Samarasekera ◽  
Luke A Perry ◽  
Tom J Moullaali ◽  
...  
Keyword(s):  
Intracerebral Haemorrhage ◽  
Recurrent Stroke ◽  
Population Based ◽  
Vascular Events ◽  
Spontaneous Intracerebral Haemorrhage

scholarly journals Cerebrospinal fluid biomarkers and apolipoprotein E genotype in cerebral amyloid angiopathy. A narrative review

2021 ◽  
Vol 2 ◽  
pp. 100010
Author(s):  
Aikaterini Theodorou ◽  
Ioanna Tsantzali ◽  
Elisabeth Kapaki ◽  
Vasilios C. Constantinides ◽  
Konstantinos Voumvourakis ◽  
...  
Keyword(s):  
Cerebrospinal Fluid ◽  
Apolipoprotein E ◽  
Cerebral Amyloid Angiopathy ◽  
Narrative Review ◽  
Amyloid Angiopathy ◽  
Cerebrospinal Fluid Biomarkers ◽  
Cerebral Amyloid ◽  
Apolipoprotein E Genotype

Machine Learning for the Prediction of Amyloid Positivity in Amnestic Mild Cognitive Impairment

2021 ◽  
pp. 1-15
Author(s):  
Sung Hoon Kang ◽  
Bo Kyoung Cheon ◽  
Ji-Sun Kim ◽  
Hyemin Jang ◽  
Hee Jin Kim ◽  
...  
Keyword(s):  
Machine Learning ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Apolipoprotein E ◽  
Cross Validation ◽  
Good Accuracy ◽  
External Validation ◽  
Amnestic Mild Cognitive Impairment ◽  
Temporal Region ◽  
Apolipoprotein E Genotype

Background: Amyloid (Aβ) evaluation in amnestic mild cognitive impairment (aMCI) patients is important for predicting conversion to Alzheimer’s disease. However, Aβ evaluation through amyloid positron emission tomography (PET) is limited due to high cost and safety issues. Objective: We therefore aimed to develop and validate prediction models of Aβ positivity for aMCI using optimal interpretable machine learning (ML) approaches utilizing multimodal markers. Methods: We recruited 529 aMCI patients from multiple centers who underwent Aβ PET. We trained ML algorithms using a training cohort (324 aMCI from Samsung medical center) with two-phase modelling: model 1 included age, gender, education, diabetes, hypertension, apolipoprotein E genotype, and neuropsychological test scores; model 2 included the same variables as model 1 with additional MRI features. We used four-fold cross-validation during the modelling and evaluated the models on an external validation cohort (187 aMCI from the other centers). Results: Model 1 showed good accuracy (area under the receiver operating characteristic curve [AUROC] 0.837) in cross-validation, and fair accuracy (AUROC 0.765) in external validation. Model 2 led to improvement in the prediction performance with good accuracy (AUROC 0.892) in cross validation compared to model 1. Apolipoprotein E genotype, delayed recall task scores, and interaction between cortical thickness in the temporal region and hippocampal volume were the most important predictors of Aβ positivity. Conclusion: Our results suggest that ML models are effective in predicting Aβ positivity at the individual level and could help the biomarker-guided diagnosis of prodromal AD.

scholarly journals Interaction between apolipoprotein E genotype and hypertension on cognitive function in older women in the Nurses’ Health Study

PLoS ONE ◽  
2019 ◽  
Vol 14 (11) ◽  
pp. e0224975 ◽  
Author(s):  
Iris Y. Kim ◽  
Francine Grodstein ◽  
Peter Kraft ◽  
Gary C. Curhan ◽  
Katherine C. Hughes ◽  
...  
Keyword(s):  
Cognitive Function ◽  
Apolipoprotein E ◽  
Older Women ◽  
Health Study ◽  
Apolipoprotein E Genotype

Association of apolipoprotein E genotype with brain levels of apolipoprotein E and apolipoprotein J (clusterin) in Alzheimer disease

1995 ◽  
Vol 33 (1) ◽  
pp. 174-178 ◽  
Author(s):  
Philippe Bertrand ◽  
Judes Poirier ◽  
Tomiichiro Oda ◽  
Caleb E. Finch ◽  
Giulio Maria Pasinetti
Keyword(s):  
Alzheimer Disease ◽  
Apolipoprotein E ◽  
Brain Levels ◽  
Apolipoprotein J ◽  
Apolipoprotein E Genotype
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