AHA 23: ORFAN: AI Technology to Improve Risk Stratification of Patients without CAD Undergoing CCTA

Published: 21 Nov 2023

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AHA 23 — In this brief interview, we are joined by Prof Charalambos Antoniades (Oxford University, UK) to discuss the ORFAN trial, sponsored by the University of Oxford.

ORFAN is a prospective, multicenter, observational study that collected CT scans, biological material and outcomes data to develop and validate biomarkers of cardiometabolic risk. The registry included 250000 unselected consecutive patients at participating centres. The study combines imaging data and patient demographics to improve new or existing image analysis algorithms and software tools.

Findings showed that in patients undergoing CTCA had 2x more heart attacks and cardiac deaths in those without obstructive CAD a compared to those with obstructive CAD. Measuring coronary inflammation predicts fatal and non-fatal cardiac events independent from clinical risk scores and CT interpretation. New AI-driven risk classification changes risk-driven management in 40% of patients.

Interview Questions:

  1. What is the aim of the ORFAN registry?
  2. Can you tell us about the AI algorithm used in this study?
  3. What was the study design and the baseline characteristics of the study cohort?
  4. What are the findings?
  5. What conclusions can be made? What are the limitations of this registry?
  6. What advancements can we expect in the next 5 years as AI continues to impact the field of medicine?

Recorded on-site at AHA Scientific Sessions 2023, Philadelphia.

For more content from #AHA23 head to the Late-Breaking or the CardioNerds Conference Scholars Collection.

Support: This is an independent interview conducted by Radcliffe Cardiology.

Interviewer: Mirjam Boros
Editor: Jordan Rance
Video Specialist: Daniel Brent


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