{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,24]],"date-time":"2026-09-24T07:59:07Z","timestamp":1790236747690,"version":"4.1.0"},"reference-count":36,"publisher":"Oxford University Press (OUP)","issue":"5","license":[{"start":{"date-parts":[[2025,10,15]],"date-time":"2025-10-15T00:00:00Z","timestamp":1760486400000},"content-version":"vor","delay-in-days":510,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"},{"start":{"date-parts":[[2024,5,23]],"date-time":"2024-05-23T00:00:00Z","timestamp":1716422400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2024,10,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Aims<\/jats:title>\n                    <jats:p>Artificial intelligence (AI) has emerged as a potential useful tool to support clinical treatment of heart failure, including the setting of mechanical circulatory support (MCS). Modern Impella pumps are equipped with advanced technology (SmartAssist), enabling real-time acquisition and display of data related to both pump performance and the patient's haemodynamic status. These data emerge as an \u2018ideal\u2019 source for data-driven AI applications to predict the clinical course of an ongoing therapeutic protocol. Yet, no evidence of effective application of AI tools in the setting of Impella support is available. On this background, we aimed at identifying possible future applications of AI-based tools in the setting of temporary MCS with an Impella device.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>We explored the state of research and development at the intersection of AI and Impella support and derived future potential applications of AI in routine Impella clinical management.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>We identified different areas where the future implementation of AI tools may contribute to addressing important clinical challenges in the setting of Impella support, including (i) early identification of the best suited pathway of care according to patients' conditions at presentation and intention to treat, (ii) prediction of therapy outcomes according to different possible therapeutic actions, (iii) optimization of device implantation procedures and evaluation of proper pump position over the whole course of support and (iv) prevention and\/or rationale management of haemocompatibility-related adverse events. For each of those areas, we discuss the potential advantages, challenges and implications of harnessing AI-driven insights in the setting of MCS with an Impella device.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>Temporary MCS with an Impella device has great potential to benefit from the integration of AI-based tools. Such tools may indeed translate into groundbreaking innovation supporting clinical decision-making and therapy regulation, in particular in complex scenarios such as the multidevice MCS strategy.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1002\/ehf2.14865","type":"journal-article","created":{"date-parts":[[2024,5,24]],"date-time":"2024-05-24T00:44:31Z","timestamp":1716511471000},"page":"2933-2940","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":25,"title":["The\n                    <i>Intelligent<\/i>\n                    Impella: Future Perspectives of Artificial Intelligence in the Setting of Impella Support"],"prefix":"10.1093","volume":"11","author":[{"given":"Filippo","family":"Consolo","sequence":"first","affiliation":[{"name":"Universit\u00e0 Vita Salute San Raffaele , Milan ,","place":["Italy"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jacopo","family":"D'Andria Ursoleo","sequence":"additional","affiliation":[{"name":"Department of Anesthesia and Intensive Care, IRCCS San Raffaele Scientific Institute , Milan ,","place":["Italy"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4101-800X","authenticated-orcid":false,"given":"Marina","family":"Pieri","sequence":"additional","affiliation":[{"name":"Universit\u00e0 Vita Salute San Raffaele , Milan ,","place":["Italy"]},{"name":"Department of Anesthesia and Intensive Care, IRCCS San Raffaele Scientific Institute , Milan ,","place":["Italy"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Pasquale","family":"Nardelli","sequence":"additional","affiliation":[{"name":"Department of Anesthesia and Intensive Care, IRCCS San Raffaele Scientific Institute , Milan ,","place":["Italy"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lorenzo","family":"Cianfanelli","sequence":"additional","affiliation":[{"name":"Department of Cardiology, IRCCS San Raffaele Scientific Institute , Milan ,","place":["Italy"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Vittorio","family":"Pazzanese","sequence":"additional","affiliation":[{"name":"Department of Cardiology, IRCCS San Raffaele Scientific Institute , Milan ,","place":["Italy"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Silvia","family":"Ajello","sequence":"additional","affiliation":[{"name":"Department of Cardiology, IRCCS San Raffaele Scientific Institute , Milan ,","place":["Italy"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Anna Mara","family":"Scandroglio","sequence":"additional","affiliation":[{"name":"Department of Anesthesia and Intensive Care, IRCCS San Raffaele Scientific Institute , Milan 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