Structured Rehabilitation for Patients with Atrial Fibrillation Based on an Integrated Care Approach: Protocol for a Prospective, Observational Cohort Study

Zhang, Hui, Jin, Zhigeng, Wang, Hao, Guo, Yutao and Lip, Gregory YH ORCID: 0000-0002-7566-1626 (2023) Structured Rehabilitation for Patients with Atrial Fibrillation Based on an Integrated Care Approach: Protocol for a Prospective, Observational Cohort Study. VASCULAR HEALTH AND RISK MANAGEMENT, 19. pp. 485-494.

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Official URL: http://dx.doi.org/10.2147/vhrm.s407974

Abstract

<h4>Background</h4>Guideline-recommended integrated care based on the ABC (Atrial fibrillation Better Care) pathway for "general" patients with atrial fibrillation (AF) improves clinical outcomes, as demonstrated in our prior mobile Atrial Fibrillation Application (mAFA)-II cluster randomized trial. The present study aims to investigate whether mAFA III-supported structured follow-up rehabilitation packages adapted to patient risk profiles and different treatment patterns (eg, for patients receiving drug treatment only, AF ablation, or left atrial appendage occlusion [LAAO]) will improve guideline adherence and reduce the risk of adverse cardiovascular events.<h4>Methods and analysis</h4>In this prospective, observational mAFA III pilot cohort study, patients with AF aged ≥ 18 years will be enrolled using the mAFA III App for self-management. Assuming an annual rate of composite outcome of "ischaemic stroke or systemic embolism, all-cause death and cardiovascular hospitalization" of 29.3% for non-ABC pathway compliance compared with 20.8% for ABC pathway compliance, at least 1475 patients would be needed to detect the outcome of the A, B and C components of the ABC pathway, assuming a withdrawal rate of 20% in the first year. The primary endpoint is adherence to guidelines regarding the A, B and C components of the ABC pathway. Ancillary analyses will be performed to determine the impact of the ABC pathway using smart technologies on the outcomes among the "high-risk" population (eg, ≥75 years old, with multimorbidities, with polypharmacy) and the application of artificial intelligence machine-learning AF risk prediction management in assessing AF recurrence. The individualised anticoagulants with AF burden will be monitored by smart devices.<h4>Trial registration number</h4>ISRCTN13724416.

Item Type:	Article
Uncontrolled Keywords:	atrial fibrillation, rehabilitation, mobile health
Divisions:	Faculty of Health and Life Sciences Faculty of Health and Life Sciences > Institute of Life Courses and Medical Sciences
Depositing User:	Symplectic Admin
Date Deposited:	12 Oct 2023 14:33
Last Modified:	12 Oct 2023 14:33
DOI:	10.2147/VHRM.S407974
Open Access URL:	https://doi.org/10.2147/VHRM.S407974
Related URLs:	Author Publisher
URI:	https://livrepository.liverpool.ac.uk/id/eprint/3173642