Predict Arrhythmia Risk with Intelligent Software
Official title: Artificial Intelligence-based Prediction and Detection of Critical Arrhythmias in Acute Cardiac Illness.
Run by Catharina Ziekenhuis Eindhoven · NCT07792694 · Data updated 2026-11-12
Researchers are testing AI-powered predictions to see if clinicians can spot patients at risk for dangerous heart rhythms using bedside ECG data.
Quick facts
| Study type | Observational |
|---|---|
| Ages | 18 Years and up |
| Sex | All |
| Enrollment | 3000 (estimated) |
| Sponsor | Catharina Ziekenhuis Eindhoven Academic / other |
| Locations | 1 site (Eindhoven, North Brabant) |
| Status | Recruiting |
| Started | January 1, 2023 |
| Main results expected | April 1, 2029 |
| Study ends | April 1, 2029 |
| Registry record updated | August 28, 2026 |
| Trial ID | NCT07792694 on ClinicalTrials.gov |
Is this trial a fit for you?
✓Likely a good fit
Adults (18+) admitted for acute cardiac illness or after cardiac procedures and monitored with continuous ECG data in CCU, ICU, or ward where waveform data are routinely stored.
✕Probably not a fit
Patients without sustained VT/VF risk detectable by the chosen data set or with unavailable continuous ECG data may not benefit.
A plain-English reading of the study's rules. Only the study team can confirm whether you qualify.
What this trial studies
This observational study evaluates AI models that analyze real-time bedside ECGs to predict sustained ventricular tachycardia or ventricular fibrillation within 30 minutes and within 1 day. Secondary aims explore potential healthcare savings, such as shorter CCU and hospital stays, and cost reductions if the AI predictions are used in practice. Exploratory objectives include real-time alarm generation for events, prediction of other arrhythmias, and identification of clinical risk factors to support model development. The study uses continuous waveform ECG data collected in hospital units and assesses performance across timeframes and clinical inputs.
Why it matters
Potential benefit: If successful, the AI tool could improve early warning of life-threatening arrhythmias and reduce alarm fatigue for staff, potentially shortening hospital stays and lowering costs.
How similar studies have gone: Other studies have shown promise with AI in arrhythmia risk prediction, but this project addresses real-time bedside prediction and practical implementation in clinical care.
Who can join: the full rules
Show full inclusion / exclusion criteria
Inclusion criteria: * Patients admitted from 1/1/2023\* * Patients aged 18 years or older * Admitted for acute cardiac illness or after elective cardiac procedures * Who are on ECG monitoring in the CCU, ICU or ward * Patients for whom continuous waveform ECG data have been routinely stored. * Continuous waveform ECG data has been routinely stored in the CZE since 1/1/2023 on the ICU, since 1/12/2025 on the CCU and on the ward it has yet to be implemented. As our project utilizes this continuous ECG data, it will only include patients for whom this data is available. Exclusion Criteria: \- Patients who expressed their preference for not having their data used for scientific research or to improve quality of care in the opt-out program of the CZE.
Where it's running
-
Catharina Hospital Eindhoven
Eindhoven, North Brabant, Netherlands Recruiting
Study contacts
- Principal investigator: Luuk C Otterspoor, Dr. M.D. — Catharina Ziekenhuis Eindhoven
- Study coordinator: Maud E Kortman, M.D.
- Email: maud.kortman@catharinaziekenhuis.nl
- Phone: 040 239 9111
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How to take part
- Review the eligibility criteria above with your treating physician.
- Check the official listing on ClinicalTrials.gov for the latest contact details and recruitment status.
- Contact the study coordinator or principal investigator to ask for pre-screening. Pre-screening is free and never obligates you to enroll.