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Darabi F, Tan NS, Allan KS, Lin S, Angaran P, Dorian P. ICD Implantation Rates in Cardiac Arrest Survivors in Canada. CJC Open 2024; 6:699-707. [PMID: 38846442 PMCID: PMC11150952 DOI: 10.1016/j.cjco.2023.12.011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2023] [Accepted: 12/12/2023] [Indexed: 06/09/2024] Open
Abstract
Background Patients resuscitated from out-of-hospital cardiac arrest (OHCA) are at high risk of recurrence, posing a substantial burden on healthcare systems. Despite the established benefit of implantable cardioverter defibrillator (ICD) therapy in many such patients, and recommendations by guidelines, few studies have described the proportion of OHCA patients who receive guideline-concordant care. Methods The Canadian Institute for Health Information Discharge Abstract Database dataset was used to identify OHCA patients admitted to hospitals across Canada, excluding Quebec. We analyzed all patients without a probable ischemic or bradycardia etiology of cardiac arrest, who survived to discharge, to estimate the ICD implantation rates in patients who were potentially eligible to have an ICD. Results Between 2013 and 2017, a total of 10,435 OHCA patients who were admitted to the hospital were captured in the database; 4486 (43%) survived to hospital discharge, and 2580 survivors (57.5%) were potentially eligible to receive an ICD. Among these potentially eligible patients, 757 (29.3%) received an ICD during their index admission or within 30 days after discharge from the hospital. The ICD implantation rate during index admission increased from 13.8% in 2013 to 19.6% in 2017 (P-value for time trend < 0.05). The rate of ICD implantations in potentially eligible patients was higher in urban than in rural settings (19.5% vs 11.1%) and in teaching vs community hospitals (34.7% vs 9.8%). Conclusions Although ICD implantation rates show an increasing trend among patients with OHCA who are likely eligible for secondary prevention, significant underutilization of ICDs persists in these patients.
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Affiliation(s)
- Farzad Darabi
- Division of Cardiology, St. Michael’s Hospital, Toronto, Ontario, Canada
- Department of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Nigel S. Tan
- Division of Cardiology, St. Michael’s Hospital, Toronto, Ontario, Canada
- Department of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Katherine S. Allan
- Division of Cardiology, St. Michael’s Hospital, Toronto, Ontario, Canada
- Department of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Steve Lin
- Division of Cardiology, St. Michael’s Hospital, Toronto, Ontario, Canada
- Department of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Paul Angaran
- Division of Cardiology, St. Michael’s Hospital, Toronto, Ontario, Canada
- Department of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Paul Dorian
- Division of Cardiology, St. Michael’s Hospital, Toronto, Ontario, Canada
- Department of Medicine, University of Toronto, Toronto, Ontario, Canada
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Jennings JB. Can machine learning predict recurrent cardiac arrest? Resuscitation 2023; 184:109704. [PMID: 36708944 DOI: 10.1016/j.resuscitation.2023.109704] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2023] [Accepted: 01/18/2023] [Indexed: 01/26/2023]
Affiliation(s)
- Jason B Jennings
- Department of Emergency Medicine, VCU Health, 1250 E Marshall St, Richmond, VA 23298, United States.
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