Herrero-Brocal Marta, Samper Raquel, Riquelme Jorge, Pineda Javier, Bordes Pascual, Torres-Mezcua Fernando, Valencia José, Torres-Saura Francisco, Manso María González, Ajo Raquel, Arenas Juan, Feliu Eloísa, Martínez Juan Gabriel, Ruiz-Nodar Juan Miguel
Cardiology Department, Dr Balmis General University Hospital, Alicante Institute for Health and Biomedical Research (ISABIAL), C/Maestro Alonso s/n, Alicante 03010, Spain.
Tucuvi Care SL, C. de Hermosilla, Madrid 28001, Spain.
Eur Heart J Digit Health. 2024 Nov 20;6(1):73-81. doi: 10.1093/ehjdh/ztae089. eCollection 2025 Jan.
Evidence regarding the safety of early discharge following transcatheter aortic valve implantation (TAVI) is limited. The aim of this study was to evaluate the safety of very early (<24) and early discharge (24-48 h) as compared to standard discharge (>48 h), supported by the implementation of a voice-based virtual assistant using artificial intelligence (AI) and natural language processing.
Single-arm prospective observational study that included consecutive patients who underwent TAVI in a tertiary hospital in 2023 and were discharged under an AI follow-up programme. Primary endpoint was a composite of death, pacemaker implantation, readmission for heart failure, stroke, acute myocardial infarction, major vascular complications, or major bleeding, at 30-day follow-up. A total of 274 patients were included. 110 (40.1%) patients were discharged very early (<24 h), 90 (32.9%) early (24-48 h), and 74 (27.0%) were discharged after 48 h. At 30-day follow-up, no significant differences were found among patients discharged very early, early, and those discharged after 48 h for the primary endpoint (very early 9.1% vs. early 11.1% vs. standard 9.5%; = 0.88). The AI platform detected complications that could be effectively addressed. The implementation of this follow-up system was simple and satisfactory for TAVI patients.
Early and very early discharge in patients undergoing TAVI, supported by close follow-up using AI, were shown to be safe. Patients with early and very early discharge had similar 30-day event rates compared to those with longer hospital stays. The AI system contributed to the early detection and resolution of complications.
关于经导管主动脉瓣植入术（TAVI）后早期出院安全性的证据有限。本研究的目的是评估与标准出院（>48小时）相比，极早期（<24小时）和早期出院（24 - 48小时）的安全性，并借助使用人工智能（AI）和自然语言处理的语音虚拟助手来提供支持。
单臂前瞻性观察性研究，纳入了2023年在一家三级医院接受TAVI并在AI随访计划下出院的连续患者。主要终点是在30天随访时死亡、起搏器植入、因心力衰竭再次入院、中风、急性心肌梗死、重大血管并发症或重大出血的复合终点。共纳入274例患者。110例（40.1%）患者极早期（<24小时）出院，90例（32.9%）早期（24 - 48小时）出院，74例（27.0%）在48小时后出院。在30天随访时，极早期出院、早期出院和48小时后出院的患者在主要终点方面未发现显著差异（极早期9.1% vs. 早期11.1% vs. 标准9.5%；P = 0.88）。AI平台检测到了可以有效处理的并发症。该随访系统的实施对TAVI患者来说简单且令人满意。
在AI密切随访支持下，TAVI患者的早期和极早期出院被证明是安全的。与住院时间较长的患者相比，早期和极早期出院的患者30天事件发生率相似。AI系统有助于并发症的早期检测和解决。
