US-based AI healthcare company Tempus has announced its plans to conduct a multi-centre study to evaluate its investigational, AI-enabled, predictive tests in cardiology.

The study will be titled ‘Electrocardiogram-based Artificial Intelligence-Assisted Detection of Heart Disease’ (ECG-AID).

ECG-AID will focus on finding the test’s ability to identify patients who are at high risk of developing atrial fibrillation (AFib) or any of seven structural heart diseases (SHD).

SHDs include diseases of the mitral, aortic, and tricuspid valves, abnormal heart function, and abnormal heart thickening, among others.

The study will assess whether layering a machine learning model onto a clinically acquired electrocardiogram (ECG) can enhance it with new functionality, said the company.

Tempus clinical cardiology vice president John Pfeifer said: “As a practising cardiologist, I’m excited to be launching a study with the goal of finding treatable heart disease before it is too late.

“We owe it to patients to build technology like the Tempus ECG Analysis Platform to deliver on the promise of data-driven precision medicine.”

The ECG-AID study will be conducted in collaboration with an expanding network of providers and cardiologists, with plans to add more research sites in the coming months.

The participants in the study will receive a 12-lead ECG during routine clinical care, and the ECG data will be analysed using Tempus’ investigational ECG Analysis platform algorithms.

Developed in collaboration with Geisinger, the algorithmic tests will analyse the ECG data to identify which patients are at high risk of developing heart disease.

The study participants who are older than 65 years, with no known history of AFib, but identified to be at high-risk, will receive treatment using ZioXT.

ZioXT is a prescription-only, single-patient-use, continuously recording ECG monitor developed by iRhythm, used to assess for AFib and other abnormal heart rhythms.

Last year, the US FDA issued Breakthrough Device Designation for Tempus’ ECG Analysis Platform to help clinicians identify patients at elevated risk of developing AFib.