INtelligent MOniToring to PrEdict Atrial Fibrillation [NOTE-AF]: Clinical study 1 for the “Health virtual twins for the personalised management of stroke related to atrial fibrillation (TARGET)” project. A protocol for a prospective cohort analysis

Essa, H, Johnston, BW, Lip, GYH ORCID: 0000-0002-7566-1626, Ortega-Martorell, S ORCID: 0000-0001-9927-3209, Williams, K, Welters, ID and Consortium, TARGET INtelligent MOniToring to PrEdict Atrial Fibrillation [NOTE-AF]: Clinical study 1 for the “Health virtual twins for the personalised management of stroke related to atrial fibrillation (TARGET)” project. A protocol for a prospective cohort analysis. BMJ Open. ISSN 2044-6055 (Accepted)

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Abstract

Introduction: Atrial Fibrillation (AF) is the most common arrhythmia worldwide affecting an estimated 5% of people over the age of 65 and is a leading cause of stroke and heart failure. Identification of patients at risk allows preventative measures and treatment before these complications occur. Conventional risk prediction models are static, do not have flexibility to incorporate dynamic risk factors and possess only modest predictive value. Artificial intelligence and machine learning-powered health virtual twin technology offer transformative methods for risk prediction and guiding clinical decisions.
Methods and analysis: In this prospective observational study 1200 patients will be recruited in two tertiary centres. Patients hospitalised with acute illnesses (sepsis, heart failure, respiratory failure, stroke or critical illness) and patients having undergone high risk surgery (major vascular surgery, upper gastrointestinal surgery and emergency surgery) will be monitored with a patch-based remote wireless monitoring system for up-to fourteen days. Clinical and electrocardiographic data will be used for modelling the risk of new onset AF. The primary outcome are episodes of AF >30 sec and will be described as ratio of episodes/patient and as percentage of patients having episodes of AF. Secondary outcomes include 30- and 90-day readmission rates and complications of AF.

The aim of this study is to generate data for the development and validation of health virtual twins predicting onset of AF in an at-risk population. The NOTE-AF study is part of the TARGET project, a Horizon Europe funded programme which includes risk prediction, diagnosis and management of AF-related stroke (https://target-horizon.eu/).

Ethics and dissemination: The study has received approval by the Health Research Authority and the National Research Ethics Service (REC reference 24/NW/0170, IRAS project ID: 342528) in the UK and has been registered on clinicaltrials.gov (NCT06600620). Results will be disseminated as outlined in the TARGET protocol to communicate project ideas, activities, and results to diverse audiences.

Item Type:	Article
Additional Information:	This article has been accepted for publication in BMJ Open, 2025 following peer review.
Uncontrolled Keywords:	1103 Clinical Sciences; 1117 Public Health and Health Services; 1199 Other Medical and Health Sciences; 32 Biomedical and clinical sciences; 42 Health sciences; 52 Psychology
Subjects:	Q Science > QA Mathematics > QA75 Electronic computers. Computer science R Medicine > RA Public aspects of medicine > RA0421 Public health. Hygiene. Preventive Medicine R Medicine > RT Nursing
Divisions:	Computer Science and Mathematics Nursing and Advanced Practice
Publisher:	BMJ Publishing Group
Date of acceptance:	4 December 2025
Date of first compliant Open Access:	5 December 2025
Date Deposited:	05 Dec 2025 11:10
Last Modified:	05 Dec 2025 11:10
URI:	https://researchonline.ljmu.ac.uk/id/eprint/27673

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