AI Algorithms in Prediction of ACS Based on Leukocyte Properties
NCT06384846
Summary
The goal of this observational study is to find out if artificial intelligence (AI) can accurately predict acute coronary syndrome (ACS) using data on white blood cells in adults. The main question it aims to answer is: \- Can AI algorithms based on white blood cell data predict ACS with accuracy comparable to that of high-sensitivity cardiac troponin (hs-cTn)? Researchers will look at how the AI model's predictions stack up against the standard hs-cTn blood tests to see which is more accurate in diagnosing ACS. Participants in this study will have already had blood tests as part of their usual care. Their previously collected health information and blood test results will be used to help train and test the AI algorithms. Participants will not undergo any new procedures for the study itself.
Eligibility
Inclusion Criteria: * Male or Female, aged 18 years or above * Participant is willing and able to give informed consent for participation in the study * Subjects presenting without chest pain or with stable angina pectoris but without indication for revascularization during coronary angiography; identical evaluation results by review board required * Exclusion of elevated hs-cTn * Criteria for timing of blood sampling for collection of WBC and hs-cTn data need to be fulfilled (see 5.14) o Subjects with no or stable angina pectoris must have provided WBC data and at least one hs-cTn value any time before start of coronary angiography. * Between initial blood sampling to collect WBC data and coronary angiography, the subject must not develop suspicion of ACS. Exclusion Criteria: * Age \< 18 years old * Subject refuses informed consent * Collection of WBC and hs-cTn data is not possible * Criteria for timing of blood sampling for collection of WBC and hs-cTn data cannot be fulfilled * Suspicion of ACS occurred in subjects with no or stable angina pectoris any time between initial blood sampling and start of coronary angiography
Conditions5
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NCT06384846