{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,2]],"date-time":"2026-09-02T06:02:13Z","timestamp":1788328933189,"version":"build-2803163510"},"reference-count":24,"publisher":"Oxford University Press (OUP)","issue":"2","license":[{"start":{"date-parts":[[2021,10,3]],"date-time":"2021-10-03T00:00:00Z","timestamp":1633219200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"UK Research and Innovation\u2019s Industrial Strategy Challenge Fund"},{"name":"Digital Innovation Hub Programme","award":["MC_PC_18027"],"award-info":[{"award-number":["MC_PC_18027"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022,2,2]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Aims<\/jats:title>\n                    <jats:p>To determine if remotely monitored physiological data from cardiac implantable electronic devices (CIEDs) can be used to identify patients at high risk of mortality.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods and results<\/jats:title>\n                    <jats:p>This study evaluated whether a risk score based on CIED physiological data (Triage-Heart Failure Risk Status, \u2018Triage-HFRS\u2019, previously validated to predict heart failure (HF) events) can identify patients at high risk of death. Four hundred and thirty-nine adults with CIEDs were prospectively enrolled. Primary observed outcome was all-cause mortality (median follow-up: 702\u2009days). Several physiological parameters [including heart rate profile, atrial fibrillation\/tachycardia (AF\/AT) burden, ventricular rate during AT\/AF, physical activity, thoracic impedance, therapies for ventricular tachycardia\/fibrillation] were continuously monitored by CIEDs and dynamically combined to produce a Triage-HFRS every 24\u2009h. According to transmissions patients were categorized into \u2018high-risk\u2019 or \u2018never high-risk\u2019 groups. During follow-up, 285 patients (65%) had a high-risk episode and 60 patients (14%) died (50 in high-risk group; 10 in never high-risk group). Significantly more cardiovascular deaths were observed in the high-risk group, with mortality rates across groups of high vs. never-high 10.3% vs. &amp;lt;4.0%; P\u2009=\u20090.03. Experiencing any high-risk episode was associated with a substantially increased risk of death [odds ratio (OR): 3.07, 95% confidence interval (CI): 1.57\u20136.58, P\u2009=\u20090.002]. Furthermore, each high-risk episode \u226514 consecutive days was associated with increased odds of death (OR: 1.26, 95% CI: 1.06\u20131.48; P\u2009=\u20090.006).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>Remote monitoring data from CIEDs can be used to identify patients at higher risk of all-cause mortality as well as HF events. Distinct from other prognostic scores, this approach is automated and continuously updated.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1093\/europace\/euab160","type":"journal-article","created":{"date-parts":[[2021,6,17]],"date-time":"2021-06-17T15:11:15Z","timestamp":1623942675000},"page":"245-255","source":"Crossref","is-referenced-by-count":28,"title":["Remote monitoring data from cardiac implantable electronic devices predicts all-cause mortality"],"prefix":"10.1093","volume":"24","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9769-0180","authenticated-orcid":false,"given":"Fozia Zahir","family":"Ahmed","sequence":"first","affiliation":[{"name":"Division of Cardiovascular Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK"},{"name":"Department of Cardiology, Manchester University Hospitals NHS Foundation Trust, Oxford Rd, Manchester, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Camilla","family":"Sammut-Powell","sequence":"additional","affiliation":[{"name":"Division of Informatics, Imaging and Data Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Academic Health Science Centre, Manchester, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7047-1586","authenticated-orcid":false,"given":"Chun Shing","family":"Kwok","sequence":"additional","affiliation":[{"name":"School of Primary, Community and Social Care, Keele University, Stoke-on-Trent, UK"},{"name":"Department of Cardiology, University Hospitals of North Midlands NHS Trust, Stoke-on-Trent, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tricia","family":"Tay","sequence":"additional","affiliation":[{"name":"Division of Cardiovascular Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, 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