VALUE OF ENDOTHELIUM DYSFUNCTION AND INFLAMMATORY MARKERS LEVEL FOR PREDICTING RISK ASSESSMENT IN UNFAVORABLE COURSE OF ISCHEMIC HEART DISEASE

2019 ◽  
Vol 15 (67) ◽  
pp. 017
Author(s):  
L. A. Vozniuk ◽  
I. O. Doroshkevych ◽  
O. O. Klekоt ◽  
O. V. Kyrychenko
Keyword(s):  
Risk Assessment ◽  
Heart Disease ◽  
Ischemic Heart Disease ◽  
Inflammatory Markers ◽  
Ischemic Heart ◽  
Endothelium Dysfunction

Inflammatory markers and long-term risk of ischemic heart disease in men

2005 ◽  
Vol 182 (2) ◽  
pp. 315-321 ◽  
Author(s):  
Annie C. St-Pierre ◽  
Bernard Cantin ◽  
Jean Bergeron ◽  
Matteo Pirro ◽  
Gilles R. Dagenais ◽  
...  
Keyword(s):  
Heart Disease ◽  
Ischemic Heart Disease ◽  
Inflammatory Markers ◽  
Ischemic Heart

scholarly journals Opportunistic Assessment of Ischemic Heart Disease Risk Using Abdominopelvic Computed Tomography and Medical Record Data: a Multimodal Explainable Artificial Intelligence Approach

2021 ◽  
Author(s):  
Juan M Zambrano Chaves ◽  
Akshay S Chaudhari ◽  
Andrew L Wentland ◽  
Arjun D Desai ◽  
Imon Banerjee ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Risk Assessment ◽  
Heart Disease ◽  
Ischemic Heart Disease ◽  
Medical Record ◽  
Disease Risk ◽  
Tissue Level ◽  
Ischemic Heart ◽  
Risk Scores ◽  
Imaging Biomarkers

AbstractCurrent risk scores for predicting ischemic heart disease (IHD) risk—the leading cause of global mortality—have limited efficacy. While body composition (BC) imaging biomarkers derived from abdominopelvic computed tomography (CT) correlate with IHD risk, they are impractical to measure manually. Here, in a retrospective cohort of 8,197 contrast-enhanced abdominopelvic CT examinations undergoing up to 5 years of follow-up, we developed improved multimodal opportunistic risk assessment models for IHD by automatically extracting BC features from abdominal CT images and integrating these with features from each patient’s electronic medical record (EMR). Our predictive methods match and, in some cases, outperform clinical risk scores currently used in IHD risk assessment. We provide clinical interpretability of our model using a new method of determining tissue-level contributions from CT along with weightings of EMR features contributing to IHD risk. We conclude that such a multimodal approach, which automatically integrates BC biomarkers and EMR data can enhance IHD risk assessment and aid primary prevention efforts for IHD.

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