Utilising an artificial intelligence (AI) system which strictly follows guidelines could help prevent unnecessary diagnostic tests in patients with stable chest pain, suggests research presented at the International Conference on Nuclear Cardiology and Cardiac CT at the weekend.
Researchers performed a cost analysis of an AI decision support system (DSS) called ARTificial Intelligence for clinical Cardiac nAvigation (ARTICA) versus standard care (STD) in 982 patients with stable chest pain. Significant coronary artery disease (CAD) was defined as ≥50% coronary stenosis on computed tomography angiography (CTA; n=961) or on invasive coronary angiography (ICA; n=21).
While the DSS classified 658 (67%) patients as requiring "no further test (NFT)", STD labelled only 45 (4.6%) patients as NFT. After CTA or ICA, 639 (97%) of NFTs identified by DSS showed no significant CAD, meaning the decision was correct. The study also found avoiding these tests would save staff one hour per patient.
The authors said the AI DSS approach has the potential to save costs and staff time in the triage of stable chest pain patients. “Due to an earlier identification of patients without significant CAD, the use of unnecessary cardiac imaging tests may be reduced,” they added.