A Study to Assess the Effectiveness of an Atrial Fibrillation (AF) Risk Prediction Algorithm and Diagnostic Test in Identifying Patients With AF. (PULsE AI)

Bristol-Myers Squibb (BMS)

Status: Completed

Conditions: Atrial Fibrillation

Study type: Observational

Funder types: Industry

Identifiers

NCT04045639

CV185-703

Details and patient eligibility

About

This is a trial to assess the effectiveness of an atrial fibrillation (AF) risk prediction algorithm and diagnostic test for the identification of patients with atrial fibrillation

Enrollment: 260 patients

Sex: All

Ages: 30+ years old

Volunteers: No Healthy Volunteers

Inclusion criteria

Practice inclusion criteria for the trial are as follows;

• GP Practices within National Institute for Healthcare Research (NIHR) Clinical Research Network: West Midlands (CRN: WM) CRN: WM
• GP Practices using EMIS as their electronic medical record system of choice. Patient inclusion criteria for the trial are as follows;
• Patients registered at a participating practice, aged ≥30 years and without an AF diagnosis.
• Patients with a valid index date (see Section 3.3) Participant inclusion criteria for participation in the intervention arm are;
• As above, and who have provided written consent to: attend a research clinic, AF diagnosis check using a 12-lead ECG, and for access to medical records Participant inclusion criteria for participation in further AF remote diagnosis with an AliveCor Heart Monitor are;
• As above, and those with a negative or indeterminant ECG
• As above, and those with access to a smartphone

Exclusion criteria

• Patients <30 years
• Patients with an existing diagnosis of AF
• Patients for whom the healthcare professional feels the study is unsuitable

Trial design

260 participants in 2 patient groups

Intervention arm

Description:

The AF risk prediction algorithm will be run on patient records within the Egton Medical Information Systems (EMIS) data base, in order to identify patients at risk of developing AF

Control arm

Description:

Patients may be diagnosed with AF through routine clinical practice only