Diagnostic Performance of Artificial Intelligence Algorithms in Prediction of Acute Coronary Syndrome Based on White Blood Cell Properties

NCT06384846 | Recruiting DMC

• 1 other identifier: AI ACS
• Study Type: observational
• Target: 3,350
• Locations: 1 country
• Sites: 1

Brief Summary

The goal of this observational study is to evaluate whether artificial intelligence (AI) algorithms can predict or exclude acute coronary syndrome (ACS) in adults using data generated by routine hematology testing. The main questions the study aims to answer are:

• Can AI algorithms based on white blood cell (WBC) data predict or exclude ACS in subjects with suspected ACS?
• Can erythrocyte (EC) and/or thrombocyte (TC) data, where available, improve or complement WBC-based AI prediction of ACS?
• How does the diagnostic performance of the AI algorithms compare with high-sensitivity cardiac troponin (hs-cTn), and can the combination of AI algorithms and hs-cTn improve diagnostic performance? Participants will undergo clinical assessment and blood testing as part of usual clinical care. Their previously generated clinical information, hematology data, and hs-cTn results will be used to train and test the AI algorithms. Participation in the study does not determine the indication for coronary angiography or treatment, and no additional study-specific treatments are performed.

Conditions

Acute Coronary Syndrome; Angina Pectoris; Unstable Angina (UA); NSTEMI - Non-ST Segment Elevation MI; STEMI - ST Elevation Myocardial Infarction

Keywords

Artificial Intelligence; AI; hematology analyzer; ACS; white blood cell; Troponin; Machine learning

Outcome Measures

Primary Outcomes (2)

• Training of AI models

  Diagnostic performance of AI models in predicting ACS, evaluated by area under curve (AUC) under the receiver operating characteristic (ROC) curve

  36 months

• Testing of AI models

  Diagnostic performance of AI models in predicting ACS, evaluated by AUC under ROC curve ; Specificity and sensitivity of AI models to predict ACS in subjects with suspected ACS, calculated from AUC under ROC curve

  36 months

Secondary Outcomes (2)

• Training of AI models

  36 months

• Testing of AI models:

  36 months

Study Arms (5)

Control-Cohort

Subjects with suspected ACS but exclusion of a culprit lesion during coronary angiography.

Case-Cohort

Subjects with suspected ACS and identification of a culprit lesion during coronary angiography.

Supplementary cohort

Subjects with no or stable angina pectoris and no indication for revascularization during coronary angiography.

Rule Out

Subjects with suspected NSTE-ACS and STEMI Rule-Out that did not undergo coronary angiography \<72h.

All-comer cohort

Subjects presenting to the emergency department with suspected acute coronary syndrome (ACS). This cohort is used for testing the AI models. Clinical assessment, ECG, and high-sensitivity cardiac troponin (hs-cTn) measurements are performed according to current ESC guidelines. White blood cell (WBC) data are collected at the initial blood withdrawal after admission to the emergency department. If coronary angiography is performed, review board evaluation confirms the presence or absence of a culprit lesion.

Eligibility Criteria

• Age: 18 Years+
• Sex: all
• Healthy Volunteers: Yes
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

Patients recruited at LKH-Universitätsklinikum Graz / Medical University of Graz, including subjects presenting to the emergency department or facilities of the Department of Cardiology, including the cardiac catheter laboratory and outpatient facilities. The study population includes adults with suspected acute coronary syndrome as well as subjects with no or stable angina pectoris depending on cohort assignment.

You may qualify if:

• Male or female, aged 18 years or above.
• Participant is willing and able to give informed consent for participation in the study.
• Collection of WBC and hs-cTn data must be possible.
• Criteria for timing of blood sampling for collection of WBC and hs-cTn data must be fulfilled, where applicable.
• Case cohort:
• Suspicion of STEMI or NSTE-ACS according to current ESC guidelines.
• Coronary angiography must have been performed within 72 hours after initial suspicion of ACS.
• For patients qualifying for observation according to ESC guidelines, coronary angiography is not mandatory and time limits do not apply.
• Confirmation of STEMI or NSTE-ACS by identification of a culprit lesion using coronary angiography; identical evaluation results by review board required.
• For observation patients without coronary angiography, final discharge diagnosis is used to decide about the presence or absence of NSTEMI and/or ACS.
• Criteria for timing of blood sampling for collection of WBC and hs-cTn data must be fulfilled.
• Control cohort:
• Suspicion of STEMI or NSTE-ACS according to current ESC guidelines.
• Coronary angiography must have been performed within 72 hours after initial suspicion of ACS.
• No identification of a culprit lesion compatible with diagnosis of STEMI or NSTE-ACS during coronary angiography; identical evaluation results by review board required.

You may not qualify if:

• Age below 18 years.
• 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 occurs in subjects with no or stable angina pectoris any time between initial blood sampling and start of coronary angiography.

Sponsors & Collaborators

• RobotDreams GmbH: lead

Study Sites (1)

Landeskrankenhaus-Universitätsklinikum Graz

Graz, Styria / Steiermark, 8036, Austria

RECRUITING

MeSH Terms

Conditions

Acute Coronary Syndrome; Angina Pectoris; Non-ST Elevated Myocardial Infarction; ST Elevation Myocardial Infarction; Angina, Unstable

Condition Hierarchy (Ancestors)

Myocardial Ischemia; Heart Diseases; Cardiovascular Diseases; Vascular Diseases; Chest Pain; Pain; Neurologic Manifestations; Signs and Symptoms; Pathological Conditions, Signs and Symptoms; Myocardial Infarction; Infarction; Ischemia; Pathologic Processes; Necrosis

Central Study Contacts

Dimitrij Shulkin, M.Sc.

CONTACT

+43-676-5150578; shulkin@robotdreams.co

Johannes Gollmer, Dr. univ.

CONTACT

johannes.gollmer@medunigraz.at

Study Design

• Study Type: observational
• Observational Model: CASE CONTROL
• Time Perspective: PROSPECTIVE
• Sponsor Type: INDUSTRY
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: April 22, 2024
• First Posted: April 25, 2024
• Study Start: February 1, 2024
• Primary Completion: July 31, 2026
• Study Completion (Estimated): December 31, 2026
• Last Updated: June 24, 2026

Record last verified: 2026-06

Locations

AU (1)