Comparison of the relationship between multiple parameters of glycemic variability and coronary plaque vulnerability assessed by virtual histology-intravascular ultrasound.
Natsu Otowa-SuematsuKazuhiko SakaguchiHisako KomadaTomoaki NakamuraAnna SouYushi HirotaMasaru KurodaToshiro ShinkeKen-Ichi HirataWataru OgawaPublished in: Journal of diabetes investigation (2017)
The present data suggest that SD glucose and MAGE are more highly correlated with coronary plaque vulnerability than are CONGA-1 and MODD, and are thus likely better predictors of coronary artery disease.
Keyphrases
- coronary artery disease
- climate change
- percutaneous coronary intervention
- cardiovascular events
- coronary artery bypass grafting
- coronary artery
- type diabetes
- magnetic resonance imaging
- blood glucose
- big data
- ultrasound guided
- blood pressure
- machine learning
- data analysis
- artificial intelligence
- deep learning
- clinical evaluation
- insulin resistance