Intelligent Monitoring to Predict Atrial Fibrillation (NOTE-AF)

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

Atrial Fibrillation (AF) is the commonest arrhythmia worldwide, affects 5% of people over the age of 65 and increases the risk of stroke and heart failure. The investigators aim to detect clinical and subclinical episodes of atrial fibrillation lasting >30 seconds to develop risk prediction models to identify patients at high risk for ischaemic stroke.

Study Overview

• Status: Suspended
• Conditions: Atrial Fibrillation; Atrial Fibrillation New Onset; Postoperative Cardiovascular Complications
• Intervention / Treatment: Device: Monitoring patients heart rythms with a wireless patch device

Detailed Description

Atrial Fibrillation (AF) is the commonest arrhythmia worldwide, affects 5% of people over the age of 65 and increases the risk of stroke and heart failure. Among acutely unwell patients; arrhythmias and myocardial injury are common and associated with increased mortality, morbidity, and healthcare costs. Cardiovascular comorbidities in these high-risk patients include hypertension (47%), dyslipidaemia (29%) and ischaemic heart disease (11%).

The investigators aim to detect clinical and subclinical episodes of atrial fibrillation lasting 30 seconds to develop risk prediction models to identify patients at high risk for ischaemic stroke. Data will serve to develop and validate bedside clinical decision support tools and digital twins. Patients who develop episodes of AF as part of acute illness, will suffer further episodes of AF within one year in over 20% of cases with 27% progressing to paroxysmal/permanent AF. The true incidence of AF is unknown in acutely unwell patients as a significant percentage of AF episodes remain undetected with conventional intermittent monitoring. Patients experiencing short self-terminating episodes of AF carry a 5-fold risk of developing continuous AF and double the risk of stroke and thromboembolic events. Patients suffering episodes of AF often remain asymptomatic but are at increased risk of heart failure and death at one year. Compared to routine intermittent manual measurement of vital signs, wireless continuous vital sign monitoring systems (wCVSM) detect deviations instantaneously with the option of alerting clinical staff in real time via mobile phone applications. Accurate categorization of alerts into false and true events is essential for developing intelligent software that can be embedded into monitoring systems. Continuous ECG and vital signs monitoring can detect AF episodes more reliable, trigger timely investigations and support longer term treatment plans.

Changes in patient pathways and introduction of novel devices to alert healthcare staff on the potential of clinical events require buy-in from all stakeholders. It is therefore essential to evaluate user acceptance and to determine perceptions of users before rolling out a novel patient pathways or implementation of a new device within an organization. The investigators therefore wish to explore users' views of the device, wearing the device and potential areas for improvement using questionnaires for patients and health care staff and by conducting semi-structured interviews with healthcare staff.

Primary objective To determine the true cardiovascular event rate (defined as at least one of the following criteria: episodes of AF, New Regional Wall Motion Abnormalities, raised cardiac biomarkers hs-troponin T and NT-pro-BNP) versus false cardiovascular events detected by continuous wireless remote monitoring.

Secondary objective To determine patient acceptability and usability for health care professionals of a novel remote monitoring device with automated alert function.

• Study Type: Observational
• Enrollment (Estimated): 1200

Contacts and Locations

Study Locations

• United Kingdom
  • Liverpool, United Kingdom
    • Liverpool university foundation trust
  • Liverpool, United Kingdom
    • Liverpool University hospital Foundation trust

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: Adult; Older Adult
• Accepts Healthy Volunteers: No

• Sampling Method: Non-Probability Sample

Study Population

Patients admitted to hospital with a variety of medical conditions

Description

Inclusion Criteria:

• Adult patients ≥50 years
• Estimated risk of developing new episodes of AF greater than 5%
• Sinus rhythm at presentation

• One of the following acute conditions:

  • Patients admitted or referred to Critical Care (NOTE-AF ICU)
  • Patients admitted to hospital with acute heart failure (NOTE-AF HF)
  • Patients admitted to Emergency Services with sepsis or infection (NOTE-AF Sepsis)
  • Patients post upper gastrointestinal surgery (NOTE-AF PULSE-GI)
  • Patients post vascular interventions (NOTE-AF Vasc)
  • Patients with acute respiratory failure (NOTE-AF Resp)
  • Patients admitted after acute stroke (NOTE-AF stroke)

Exclusion Criteria:

• Atrial fibrillation or atrial flutter at the time of screening
• Patients in atrial fibrillation or atrial flutter at time of preoperative assessment or admission to hospital
• Paced cardiac rhythm
• Inability to obtain consent
• Allergy to plaster or silicone
• Expected hospital stay less than 48 hours

Study Plan

How is the study designed?

Number of groups / cohorts

7

Cohorts and Interventions

Group / Cohort	Intervention / Treatment
Patients admitted or referred to Critical Care (NOTE-AF ICU); Patients admitted or referred to Critical Care	Device: Monitoring patients heart rythms with a wireless patch device; The investigators will collect data in patients at high risk of atrial fibrillation (AF) without a known history of AF to determine clinical predicators of AF. This data will be used to generate virtual digital twins to to predict clinical and subclinical episodes of AF
Patients admitted to hospital with acute heart failure (NOTE-AF HF); Patients admitted to hospital with acute heart failure	Device: Monitoring patients heart rythms with a wireless patch device; The investigators will collect data in patients at high risk of atrial fibrillation (AF) without a known history of AF to determine clinical predicators of AF. This data will be used to generate virtual digital twins to to predict clinical and subclinical episodes of AF
Patients admitted to Emergency Services with sepsis or infection (NOTE-AF Sepsis); Patients admitted to Emergency Services with sepsis or infection	Device: Monitoring patients heart rythms with a wireless patch device; The investigators will collect data in patients at high risk of atrial fibrillation (AF) without a known history of AF to determine clinical predicators of AF. This data will be used to generate virtual digital twins to to predict clinical and subclinical episodes of AF
Patients post upper gastrointestinal surgery (NOTE-AF PULSE-GI); Patients post upper gastrointestinal surgery	Device: Monitoring patients heart rythms with a wireless patch device; The investigators will collect data in patients at high risk of atrial fibrillation (AF) without a known history of AF to determine clinical predicators of AF. This data will be used to generate virtual digital twins to to predict clinical and subclinical episodes of AF
Patients post vascular interventions (NOTE-AF Vasc); Patients post vascular interventions	Device: Monitoring patients heart rythms with a wireless patch device; The investigators will collect data in patients at high risk of atrial fibrillation (AF) without a known history of AF to determine clinical predicators of AF. This data will be used to generate virtual digital twins to to predict clinical and subclinical episodes of AF
Patients with acute respiratory failure (NOTE-AF Resp); Patients with acute respiratory failure	Device: Monitoring patients heart rythms with a wireless patch device; The investigators will collect data in patients at high risk of atrial fibrillation (AF) without a known history of AF to determine clinical predicators of AF. This data will be used to generate virtual digital twins to to predict clinical and subclinical episodes of AF
Patients admitted after acute stroke (NOTE-AF stroke); Patients admitted after acute stroke	Device: Monitoring patients heart rythms with a wireless patch device; The investigators will collect data in patients at high risk of atrial fibrillation (AF) without a known history of AF to determine clinical predicators of AF. This data will be used to generate virtual digital twins to to predict clinical and subclinical episodes of AF

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
To determine the incidence of clinical and subclinical episodes of AF in acutely unwell patients and to generate data for the development and validation of virtual twins and clinical decision support tools.	1) Number of participants with device detected AF lasting greater than 30 seconds	48 months
To determine the incidence of clinical and subclinical episodes of AF in acutely unwell patients and to generate data for the development and validation of virtual twins and clinical decision support tools.	Number of episodes of AF and duration of each AF episode	48 months

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Length of hospital stay	As measured in days and hours	48 months
Hospital readmissions within 90 days	Number of readmissions and admission diagnosis of hospital readmissions	48 months
Recurrence of AF episodes	Recurrence of AF post discharge as gathered from primary care and secondary care records.	48 months
Hospital and 90-day Mortality	Inhospital and 90-day mortality	48 months
Time spent in AF	Length of time in AF whilst on monitoring device	48 months
Number of AF episodes	Number of AF episodes whilst on monitoring device	48 months
Complications of AF	Inhospital and 90 day complications of AF such as stroke, thromboembolic disease & heart failure	48 months
High sensitivity Troponin concentrations in patients with AF episodes	Troponin changes (measured by Hs-Trop T) in patients with episodes of AF	48 months
Echocardiographic changes in patients with AF episodes	As measured by advanced echocardiographic parameters including but not limited to left atrial conduit strain, left atrial booster strain, left atrial stiffness and left atrial strain	48 months
mHealth App Usability Questionnaire	MAUQ score of patients with wireless observations	48 months
Percentage change of troponin concentrations in patients with and without episodes of AF	Change in troponin levels in patients with and without episodes of AF	48 months
Time wireless continuous vital signs monitoring device is attached	Measured in hours and minutes	48 months
Number of cardiovascular alerts	Number of cardiovascular alerts registered by device	48 months
Number of non-cardiovascular alerts	Number of non-cardiovascular alerts registered by device	48 months
Number of alerts reflecting clinical changes	Number of alerts via continuous vital signs monitoring device	48 months
Number of alerts reflecting artefacts or non-clinical events	Number of alerts reflecting clinical deterriorations versus number of alerts reflecting clinical deterrioation	48 months
RWMA score, atrial size and volume, left ventricular strain rate, standard echocardiographic measurements as per british society of echocardiography recommendations	Echocardiographic predictors of AF	48 months
Change in inflammatory markers white cell count, C-reactive protein and procalcitonin over time	Change in blood tests in patients with and without new-onset AF	48 months

Collaborators and Investigators

• Sponsor: Liverpool University Hospitals NHS Foundation Trust
• Collaborators: University of Copenhagen; University of Liverpool; Liverpool John Moores University; Isansys Lifecare LTD

Study record dates

Study Major Dates

• Study Start (Actual): September 23, 2024
• Primary Completion (Estimated): July 31, 2028
• Study Completion (Estimated): August 1, 2028

Study Registration Dates

• First Submitted: September 12, 2024
• First Submitted That Met QC Criteria: September 16, 2024
• First Posted (Actual): September 19, 2024

Study Record Updates

• Last Update Posted (Estimated): September 15, 2025
• Last Update Submitted That Met QC Criteria: September 8, 2025
• Last Verified: June 1, 2025

More Information

Terms related to this study

• Keywords: atrial fibrillation
• Additional Relevant MeSH Terms: Cardiovascular Diseases; Pathologic Processes; Heart Diseases; Arrhythmias, Cardiac; Pathological Conditions, Signs and Symptoms; Atrial Fibrillation
• Other Study ID Numbers: JRO-0126

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: UNDECIDED
• IPD Plan Description: Undecided at this point in time

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No
• product manufactured in and exported from the U.S.: No