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Monitoring LVAD parameters to detect flow-and power-impacting complications: A proof-of-concept

Moazeni, M; Numan, L; Szymanski, MK; Van der Kaaij, NP; Asselbergs, FW; van Laake, LW; Aarts, E; (2023) Monitoring LVAD parameters to detect flow-and power-impacting complications: A proof-of-concept. European Heart Journal - Digital Health 10.1093/ehjdh/ztad062. (In press). Green open access

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Abstract

The number of patients on left ventricular assist device (LVAD) support increases due to the growing number of patients with end-stage heart failure and the limited number of donor hearts. Despite improving survival rates, patients frequently suffer from adverse events such as cardiac arrythmia and major bleeding. Telemonitoring is a potentially powerful tool to early detect deteriorations and may further improve outcome after LVAD implantation. Hence, we developed a personalized algorithm to remotely monitor HeartMate3 (HM3) pump parameters aiming to early detect unscheduled admissions due to cardiac arrythmia or major bleeding. The source code of the algorithm made publicly available. The algorithm was optimized and tested retrospectively using HM3 power and flow data of 120 patients, including 29 admissions due to cardiac arrythmia and 14 admissions due to major bleeding. Using a true alarm window of 14 days prior to the admission date, the algorithm detected 59% and 79% of unscheduled admissions due to cardiac arrythmia and major bleeding, respectively, with a false alarm rate of 2%. The proposed algorithm showed that the personalized algorithm is a viable approach to early identify cardiac arrythmia and major bleeding by monitoring HM3 pump parameters. External validation is needed and integration with other clinical parameters could potentially improve the predictive value. In addition, the algorithm can be further enhanced using continuous data.

Type: Article
Title: Monitoring LVAD parameters to detect flow-and power-impacting complications: A proof-of-concept
Open access status: An open access version is available from UCL Discovery
DOI: 10.1093/ehjdh/ztad062
Publisher version: https://doi.org/10.1093/ehjdh/ztad062
Language: English
Additional information: This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial License (https://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com.
Keywords: Patient-specific monitoring • LVAD • Intensive longitudinal data • Remote patient monitoring
UCL classification: UCL
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Institute of Health Informatics
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Institute of Health Informatics > Clinical Epidemiology
URI: https://discovery.ucl.ac.uk/id/eprint/10181017
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