An initial exploration of subtraction electrocardiography to detect myocardial ischemia in the prehospital setting.
Cornelia Cato Ter HaarRon J G PetersJan BoschAgnese SbrolliniSophia GripenstedtRob AdamsEduard BleijenbergCharles J H J KirchhofReza Alizadeh DehnaviLaura BurattiniRobbert J de WinterPeter W MacfarlanePieter G PostemaSumche ManRoderick W C ScherptongMartin J SchalijArie C MaanCees A SwennePublished in: Annals of noninvasive electrocardiology : the official journal of the International Society for Holter and Noninvasive Electrocardiology, Inc (2019)
In our initial exploration, the diagnostic performance of subtraction electrocardiography for the detection of acute myocardial ischemia proved equal to that of state-of-the-art automated single-ECG analysis by the Uni-G algorithm. Possibly, refinement of both algorithms, or even integration of the two, could surpass current electrocardiographic myocardial ischemia detection.
Keyphrases
- left ventricular
- machine learning
- deep learning
- loop mediated isothermal amplification
- label free
- real time pcr
- cardiac arrest
- liver failure
- respiratory failure
- heart rate
- heart rate variability
- high throughput
- heart failure
- mitral valve
- intensive care unit
- magnetic resonance imaging
- magnetic resonance
- atrial fibrillation
- single cell
- trauma patients
- emergency medical