Using AI to predict acute coronary syndrome from white blood cell data
Diagnostic Performance of Artificial Intelligence Algorithms in Prediction of Acute Coronary Syndrome Based on White Blood Cell Properties (AI-ACS Trial)
This study is testing if artificial intelligence can predict acute coronary syndrome by looking at white blood cell data in adults, comparing it to standard blood tests.
Quick facts
| Study type | Observational |
|---|---|
| Enrollment | 2700 (estimated) |
| Ages | 18 Years and up |
| Sex | All |
| Sponsor | RobotDreams GmbH Industry-sponsored |
| Locations | 1 site (Graz, Styria / Steiermark) |
| Trial ID | NCT06384846 on ClinicalTrials.gov |
What this trial studies
This observational study aims to evaluate whether artificial intelligence (AI) can accurately predict acute coronary syndrome (ACS) by analyzing white blood cell (WBC) properties in adults. The study will compare the predictive accuracy of AI algorithms against traditional high-sensitivity cardiac troponin (hs-cTn) blood tests. Participants will have their previously collected health information and blood test results utilized to train and test the AI models, without undergoing any new procedures. The study is conducted at the Medical University of Graz and involves a prospective, observational case-control design.
Who should consider this trial
Good fit: Ideal candidates are adults aged 18 and older presenting with stable angina or without chest pain, who have provided necessary blood test data.
Not a fit: Patients under 18 years old or those who refuse informed consent will not benefit from this study.
Why it matters
Potential benefit: If successful, this study could lead to more accurate and timely diagnoses of acute coronary syndrome, potentially improving patient outcomes.
How similar studies have performed: While the use of AI in medical diagnostics is a growing field, this specific approach using WBC data for ACS prediction is relatively novel and has not been extensively tested in prior studies.
Eligibility criteria
Show full inclusion / exclusion criteria
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
Where this trial is running
Graz, Styria / Steiermark
- Landeskrankenhaus-Universitätsklinikum Graz — Graz, Styria / Steiermark, Austria (Recruiting)
Study contacts
- Study coordinator: Dimitrij Shulkin, M.Sc.
- Email: shulkin@robotdreams.co
- Phone: +43-676-5150578
How to participate
- Review the eligibility criteria above with your treating physician.
- Visit the official trial page on ClinicalTrials.gov for the most current contact information and recruitment status.
- Contact the listed study coordinator or principal investigator to request pre-screening. Pre-screening is free and never obligates you to enroll.