The use of AI-ECG to risk stratify patients in RACPC
Research type
Research Study
Full title
The use of artificial intelligence–enhanced electrocardiograms in the chest pain clinic to risk stratify patients, provide rapid reassurance and enable a low-cost clinical pathway
IRAS ID
352261
Contact name
Jamil Mayet
Contact email
Sponsor organisation
Imperial College Healthcare NHS Trust
Clinicaltrials.gov Identifier
Clinicaltrials.gov Identifier
TBC, TBC
Duration of Study in the UK
2 years, 0 months, 1 days
Research summary
Our current pathway for investigating patients with chest pain differs depending on if the pain is cardiac sounding or not. Despite national guidelines advising us that patients with non-cardiac chest pain do not need further tests beyond seeing a clinician and having an electrocardiogram (ECG), very often unnecessary additional investigations do take place. Some of the tests we do involve invasive procedures or radiation, which have associated risks. We have recently developed an artificial intelligence (AI) ECG technology, which has been shown in various studies on millions of real-patient ECGs to reliably predict risk of heart disease, including heart attacks and death, from just one reading. This is a test that is fast, painless and with no risks or radiation. We have shown that this AI-ECG is more accurate at predicting outcomes than the standard risk prediction models we use now.We propose investigating whether this new technology helps clinicians to more closely follow the national guidelines and undertake fewer unnecessary investigations for patients at a very low risk of heart disease. We will randomly allocate our chest pain clinics to follow either their current practice, or the AI-ECG guided pathway, alternating on a week-week basis. On an AI-ECG guided week, patients with non-cardiac pain will receive an AI-ECG, which will determine which patients are low risk of heart disease and which are higher risk. Feedback from the analysis will be given to the assessing clinician, advising that patients determined to be low risk by the AI-ECG will be reassured and discharged from clinic, with patients identified as higher risk undergoing further investigation.
All patients’ clinical assessment and management plans will be assessed by a Consultant Cardiologist, who will not have access to the AI-ECG data, ensuring that all assigned management pathways are clinically safe and appropriate. We will compare the cost for each group at one year, as well as how quickly we can provide a diagnosis and management plan to patients. We will also assess the number of cardiac events, and the number of patients prescribed cholesterol and blood pressure lowering medications. We propose that this study will allow us to safely and rapidly reassure more patients with chest pain in alignment with national guidelines.
REC name
London - West London & GTAC Research Ethics Committee
REC reference
26/LO/0288
Date of REC Opinion
20 May 2026
REC opinion
Further Information Favourable Opinion