Rapid and automated risk stratification by determination of the aortic stiffness in healthy subjects and subjects with cardiovascular disease.
Julia LortzLennard HalfmannAmelie BurghardtMartin SteinmetzTobias RadeckeRolf Alexander JánosiTienush RassafChristos RammosPublished in: PloS one (2019)
Using a simple and rapid automated oscillometric method, we achieved good diagnostic accuracy for the determination of aortic stiffness through the PWV in both subjects with and without CVD. This method might be helpful in daily practice in terms of saving time and reducing procedural complexity for screening for cardiovascular morbidities and vascular damage in cases of atherosclerosis.
Keyphrases
- cardiovascular disease
- aortic valve
- deep learning
- machine learning
- solid phase extraction
- high throughput
- pulmonary artery
- left ventricular
- molecularly imprinted
- loop mediated isothermal amplification
- healthcare
- primary care
- aortic dissection
- oxidative stress
- type diabetes
- physical activity
- heart failure
- quality improvement
- cardiovascular events
- pulmonary hypertension
- pulmonary arterial hypertension
- cardiovascular risk factors
- atrial fibrillation
- single cell
- tandem mass spectrometry