Cost-effectiveness of a novel AI technology to quantify coronary inflammation and cardiovascular risk in patients undergoing routine Coronary Computed Tomography Angiography.
Apostolos Tsiachristas, Kenneth Chan, Elizabeth Wahome, Ben Kearns, Parijat Patel, Maria Lyasheva, Nigar Syed, Sam Fry, Thomas Halborg, Henry West, Ed Nicol, David Adlam, Bhavik Modi, Attila Kardos, John P Greenwood, Nikant Sabharwal, Giovanni Luigi De Maria, Shahzad Munir, Elisa McAlindon, Yogesh Sohan, Pete Tomlins, Muhammad Siddique, Cheerag Shirodaria, Ron Blankstein, Milind Desai, Stefan Neubauer, Keith M Channon, John Deanfield, Ron Akehurst, Charalambos Antoniades
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引用次数: 0
Abstract
Aims: Coronary Computed Tomography Angiography (CCTA) is a first line investigation for chest pain in patients with suspected obstructive coronary artery disease (CAD). However, many acute cardiac events occur in the absence of obstructive CAD. We assessed the lifetime cost-effectiveness of integrating a novel artificial intelligence-enhanced image analysis algorithm (AI-Risk) that stratifies the risk of cardiac events by quantifying coronary inflammation, combined with the extent of coronary artery plaque and clinical risk factors, by analysing images from routine CCTA.
Methods and results: A hybrid decision-tree with population cohort Markov model was developed from 3,393 consecutive patients who underwent routine CCTA for suspected obstructive CAD and followed up for major adverse cardiac events over a median(IQR) of 7.7(6.4-9.1) years. In a prospective real-world evaluation survey of 744 consecutive patients undergoing CCTA for chest pain investigation, the availability of AI-Risk assessment led to treatment initiation or intensification in 45% of patients. In a further prospective study of 1,214 consecutive patients with extensive guideline recommended cardiovascular risk profiling, AI-Risk stratification led to treatment initiation or intensification in 39% of patients beyond the current clinical guideline recommendations. Treatment guided by AI-Risk modelled over a lifetime horizon could lead to fewer cardiac events (relative reductions of 4%, 4%, 11%, and 12% for myocardial infarction, ischaemic stroke, heart failure and cardiac death, respectively). Implementing AI-Risk classification in routine interpretation of CCTA is highly likely to be cost-effective (Incremental cost-effectiveness ratio £1,371-3,244), both in scenarios of current guideline compliance or when applied only to patients without obstructive CAD.
Conclusions: Compared with standard care, the addition of AI-Risk assessment in routine CCTA interpretation is cost effective, by refining risk guided medical management.
期刊介绍:
European Heart Journal - Quality of Care & Clinical Outcomes is an English language, peer-reviewed journal dedicated to publishing cardiovascular outcomes research. It serves as an official journal of the European Society of Cardiology and maintains a close alliance with the European Heart Health Institute. The journal disseminates original research and topical reviews contributed by health scientists globally, with a focus on the quality of care and its impact on cardiovascular outcomes at the hospital, national, and international levels. It provides a platform for presenting the most outstanding cardiovascular outcomes research to influence cardiovascular public health policy on a global scale. Additionally, the journal aims to motivate young investigators and foster the growth of the outcomes research community.