An observational study in Cardiac Arrhythmias, Acute Myocardial Infarction (AMI) and Ventricular Tachycardia (VT), sponsored by Catharina Ziekenhuis Eindhoven. Recruiting at 1 site in Netherlands. Open to participants aged 18 Years and older. Per ClinicalTrials.gov, last updated 2026-08-28.
Sponsored by Catharina Ziekenhuis Eindhoven · Observational
Cardiac arrhythmias frequently occur in patients admitted to the Coronary Care Unit (CCU). The majority of these patients are treated for an acute myocardial infarction, which carries an increased risk of life-threatening arrhythmias such as ventricular tachycardia (VT) or ventricular fibrillation (VF). This risk is one of the reasons these patients are monitored for 48 hours after a myocardial infarction, in accordance with the guidelines of the European Society of Cardiology (ESC) for acute coronary syndrome. Other arrhythmias, such as asystole, atrial fibrillation, or atrioventricular block, also occur in CCU patients. These arrhythmias are recorded on the electrocardiogram (ECG) monitor in the CCU and trigger an alarm for healthcare staff. However, in order to apply this alarming with sufficient sensitivity, many false positive alarms are also produced, which increases the workload for nurses (alarm fatigue) and undermines patient well-being.
This study will investigate whether Artificial Intelligence (AI) models, using continuous ECG data, can help improve the prediction of patients at risk of a life-threatening cardiac arrhythmia. Firstly, this study will aim to predict patients at risk of VT/VF in both the short term (30 minutes) and long term (1 day) in patients under continuous telemetric monitoring. This prediction facilitates timely intervention by the team in the short term, and in the long term, the safe transfer of a patient to a lower-complexity ward or earlier safe discharge of a patient. Secondly, this study will aim for improved detection to reduce the number of false negative alarms and thereby reduce alarm fatigue.
The performance of these AI models can be evaluated through this retrospective observational study. Patients aged 18 years or older who have been admitted with acute cardiac disease will be included. The primary objective of this study will be to evaluate the performance of AI models that detect and predict critical arrhythmias in the short and long term, using ECG data obtained via the monitoring system.
Primary objective:
Assessment of the performances of AI models in identifying patients at risk of sustained VT and VF from bedside monitor ECG in different timeframes:
Secondary objectives:
Exploratory objectives:
1,051 studies on the registry are indexed under Arrhythmias, Cardiac; 236 are open to participants now.
This study's planned enrollment of 3,000 is above the median of 200 across 467 observational studies indexed under Arrhythmias, Cardiac.
Browse Arrhythmias, Cardiac studies →Catharina Ziekenhuis Eindhoven is the lead sponsor of 85 studies on the registry; 16 are open to participants now.
Counted across the registry records on this site, refreshed daily.
Patients aged 18 years or older admitted to the Catharina hospital Eindhoven (CZE) with cardiac diseases from 1/1/2023.
Go through the criteria one by one — yes, no or not sure — and take the list to your doctor or the study team. Kept in this browser only.
Patients for whom continuous waveform ECG data have been routinely stored.
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.
Underlined terms in the criteria open these too. Explained by clinicaltrials.gg, not part of the registry record. The study team decides who can take part.
A recording of the heart’s electrical activity, taken with stickers on the chest, arms and legs. It takes a few minutes and does not hurt.
ECG (electrocardiogram)
A recording of the heart’s electrical activity, taken with stickers on the chest, arms and legs. It takes a few minutes and does not hurt.
Explained by clinicaltrials.gg, not part of the registry record. The study team decides who can take part.
Occurrence of sustained ventricular tachycardia or ventricular fibrillation
The primary outcome of the study is the occurrence of sustained ventricular tachycardia (VT) (monomorphic and polymorphic with a heartrate \> 100 bpm and duration \> 30 seconds or with hemodynamic compromise such as fainting or need for resuscitation) or ventricular fibrillation. (Binary outcome measure 0 = no event during admission, 1 = event during admission)
Time frame: During admission
Secondary outcome measure
\- A 'textbook' outcome (no adverse events) (Binary outcome measure 0 = no event during admission, 1 = event during admission)
Time frame: During admission
Secondary Outcome Measure
\- In-hospital onset and offset of cardiac arrhythmias (e.g. atrial fibrillation, atrio-ventricular block or severe tachy- or bradyarrhythmia, non-sustained VT). (Binary outcome measure 0 = no event during admission, 1 = event during admission)
Time frame: during admission
Secondary outcome measure
\- In hospital death/cardiovascular in-hospital death (include cause if available) (Binary outcome measure 0 = no event during admission, 1 = event during admission)
Time frame: During admission
Secondary outcome measure
\- Pulseless electrical activity (PEA) and asystole (Binary outcome measure 0 = no event during admission, 1 = event during admission)
Time frame: During admission
Performance of AI prediction model
Discrimination of AI prediction model expressed with Area Under the Receiver Operating Characteristic curve (AUROC), Area Under the Precision-Recall Curve (AUPRC), sensitivity, specificity, (Positive Predictive Value) PPV and (Negative Predictive Value) NPV
Time frame: During admission
Plan to share: No — Sensitive patient information, no permission to share outside of hospital
No publications or documents are linked to this record.
Started Jan 2023 (actual). Primary completion is estimated for Apr 2029, 75 months after the start.
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Catharina Ziekenhuis Eindhoven