Clinical Research Directory

Artificial Intelligence Stress Echo (FINESSE) Project

Sponsor: Milton Keynes University Hospital NHS Foundation Trust

Summary

The goal of this observational study is to learn whether combining stress echocardiography (stress echo) results with routine clinical information can better predict important heart outcomes in adults (18+) with chest pain who were assessed for suspected coronary artery disease. The main questions it aims to answer are: Can an artificial intelligence / machine learning model using stress echo findings plus clinical factors (such as blood pressure, diabetes, smoking, other health conditions, medications, and body measurements) predict major heart-related events (such as heart attack, stroke, death related to heart disease, or the need for coronary procedures) more accurately than stress echo results alone? Can the model help identify which patients are most likely to benefit from further invasive assessment and possible coronary revascularisation (for example, a stent or bypass surgery)? Which combination of stress echo measurements and clinical factors contributes most to risk prediction? Participants will: Not be asked to attend extra visits or have additional tests for this study. Have their existing stress echo reports and routinely collected hospital record data analysed (approximately 3,000 people who previously had dobutamine stress echo at Milton Keynes University Hospital). In some cases, if outcomes are not fully available from hospital records, the research team may check additional sources (such as GP records, or contacting the patient if appropriate) to confirm whether a major heart-related event occurred.

Official title: Risk Prediction Model in Patients With Suspected Coronary Artery Disease Based on Contemporary Stress Echocardiography Data Using Artificial Intelligence

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