Artificial intelligence-enabled phenotyping of patients with severe aortic stenosis: on the recovery of extra-aortic valve cardiac damage after transcatheter aortic valve replacement.
Mark LachmannElena RippenTibor SchusterErion XhepaMoritz von ScheidtTeresa TrenkwalderCostanza PellegriniTobias RheudeAmelie HesseAnja StundlGerhard HarmsenShinsuke YuasaHeribert SchunkertAdnan KastratiKarl-Ludwig LaugwitzMichael JonerChristian KupattPublished in: Open heart (2022)
This phenotyping approach preprocedurally identifies patients with severe AS, who will not recover from extra-aortic valve cardiac damage following TAVR and whose survival is therefore significantly reduced. Importantly, not the degree of pulmonary hypertension at initial presentation, but the irreversibility of right heart dysfunction determines prognosis.
Keyphrases
- aortic valve
- transcatheter aortic valve replacement
- aortic stenosis
- artificial intelligence
- aortic valve replacement
- transcatheter aortic valve implantation
- pulmonary hypertension
- oxidative stress
- machine learning
- big data
- left ventricular
- deep learning
- high throughput
- early onset
- heart failure
- pulmonary artery
- genome wide
- atrial fibrillation
- drug induced
- pulmonary arterial hypertension
- ejection fraction
- coronary artery disease