An artificial intelligence-derived risk score effectively stratifies outcomes in patients with severe tricuspid regurgitation undergoing T-TEER.
Does an artificial intelligence-derived risk score predict outcomes in patients with severe tricuspid regurgitation undergoing transcatheter edge-to-edge repair?
An artificial intelligence-derived risk score is proposed to assist in risk stratification and patient selection for transcatheter edge-to-edge repair in severe tricuspid regurgitation.
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Risk stratification for tricuspid valve transcatheter edge-to-edge repair (T-TEER) is paramount in the decision-making process to appropriately select patients with severe tricuspid regurgitation.
Hausleiter et al. (Sun,) reported a other. An artificial intelligence-derived risk score effectively stratifies outcomes in patients with severe tricuspid regurgitation undergoing T-TEER.