Intelligent monitoring to predict atrial fibrillation (NOTE-AF): clinical study 1 - a protocol for a prospective cohort analysis

Sep 29, 2026

A prospective observational protocol evaluates intelligent, patch-based remote wireless monitoring to predict new-onset atrial fibrillation (AF) and support health virtual twin models within the TARGET project. The study recruits 1200 patients across two tertiary centres, monitoring individuals for up to 14 days, using continuous single-lead ECG and vital-sign data. The primary endpoint captures AF episodes longer than 30 seconds, with secondary outcomes covering 30- and 90-day readmissions and AF complications. Ethics approval supports dissemination through the TARGET protocol.

LanguageEnglish

CategoryHealthcare

FormatPDF

Pages9

Reading Time23 min

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Abstract

Methods and analysis

Ethics and dissemination

Strengths and limitations of this study

Introduction

Open access Protocol 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 Hani Essa ,1,2,3 Brian Johnston ,4 Gregory Y. H. Lip ,5,6 Sandra Ortega-Martorell ,1,3,7 Karen Williams ,8 Ingeborg D. Welters,1,2,7 TARGET Consortium To cite: Essa H, Johnston B, Lip GY. H, et al. 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 2026;16:e099658 . doi:10 . 1136/ bmjopen-2025-099658 ► Prepublication history and additional supplemental material for this paper are available online. To view these files, please visit the journal online ([https://doi.org/10.1136/](https://doi.org/10.1136/)[ ](https://doi.org/10.1136/)[bmjopen-2025-099658](bmjopen-2025-099658)) . Received 24 January 2025 Accepted 04 December 2025 © Author(s) (or their employer(s)) 2026. Re-use permitted under CC BY. Published by BMJ Group. For numbered affiliations see end of article. Correspondence to Dr Hani Essa; [hani.essa@liverpool.ac.uk](hani.essa@liverpool.ac.uk) 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 14 days. Clinical and electrocardiographic data will be used for modelling the risk of new-onset AF. The primary outcome is episodes of AF >30 s and will be described as ratio of episodes/patient and as percentage of patients having episodes of AF. Secondary outcomes include 30-day 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 intelligent monitoring to predict atrial fibrillation (NOTEAF) study is part of the TARGET project, a Horizon Europe funded programme which includes risk prediction, diagnosis and management of AF-related stroke ([https://](https://)[ ](https://)[target-horizon.eu/](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 STRENGTHS AND LIMITATIONS OF THIS STUDY ⇒ This is a prospective, multi-centre observational study with predefined inclusion and exclusion criteria. ⇒ The study uses continuous high-resolution recording of vital signs and ECG data, enabling detailed assessment of temporal physiological changes. ⇒ Continuous single-lead ECG and vital signs monitoring will be performed using medical grade wireless technology. ⇒ ECG data will be processed with automated, machine-learning–based analysis methods, which may reduce observer bias but are dependent on algorithm

FAQs

What is the purpose of the NOTE-AF clinical study?

To generate data for developing and validating health virtual twins that predict the onset of atrial fibrillation in an at-risk population.

Who will be recruited and how long will monitoring last?

A total of 1200 patients will be recruited in two tertiary centres and monitored for up to 14 days using a patch-based remote wireless system.

What is the primary outcome of the study?

The primary outcome is episodes of atrial fibrillation lasting more than 30 seconds, summarized as episodes per patient and the percentage of patients with such episodes.

Sep 29, 2026

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