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Predict Arrhythmia Risk Using Intelligent Software (PARIS)

26. august 2026 opdateret af: Luuk Otterspoor, Catharina Ziekenhuis Eindhoven

Artificial Intelligence-based Prediction and Detection of Critical Arrhythmias in Acute Cardiac Illness.

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.

Studieoversigt

Status

Rekruttering

Betingelser

Detaljeret beskrivelse

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:

  • 30-minute prediction model
  • 1-day prediction model

Secondary objectives:

• Assessment of potential healthcare savings if the AI model in would be used in clinical practice, such as CCU length-of-stay (CCU-LOS), hospital length-of-stay and associated costs

Exploratory objectives:

  • Real time and continuous detection of events for alarming
  • Prediction of other types of arrhythmias (e.g., Atrial fibrillation (AF), atrioventricular block, severe brady-arrhythmia) using in hospital ECG monitoring.
  • Identification of clinical risk factors for sustained VT and/or VF
  • Exploration of development and assessment of new AI models using new (clinical) input

Undersøgelsestype

Observationel

Tilmelding (Anslået)

3000

Kontakter og lokationer

Dette afsnit indeholder kontaktoplysninger for dem, der udfører undersøgelsen, og oplysninger om, hvor denne undersøgelse udføres.

Studiekontakt

Undersøgelse Kontakt Backup

Studiesteder

  • Holland
    • North Brabant
      • Eindhoven, North Brabant, Holland, 5623 EJ
        • Rekruttering
        • Catharina Hospital Eindhoven
        • Kontakt:
        • Ledende efterforsker:
          • Luuk C Otterspoor, Dr. M.D.

Deltagelseskriterier

Forskere leder efter personer, der passer til en bestemt beskrivelse, kaldet berettigelseskriterier. Nogle eksempler på disse kriterier er en persons generelle helbredstilstand eller tidligere behandlinger.

Berettigelseskriterier

Aldre berettiget til at studere

  • Voksen
  • Ældre voksen

Tager imod sunde frivillige

Ingen

Prøveudtagningsmetode

Ikke-sandsynlighedsprøve

Studiebefolkning

Patients aged 18 years or older admitted to the Catharina hospital Eindhoven (CZE) with cardiac diseases from 1/1/2023.

Beskrivelse

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.

Studieplan

Dette afsnit indeholder detaljer om studieplanen, herunder hvordan undersøgelsen er designet, og hvad undersøgelsen måler.

Hvordan er undersøgelsen tilrettelagt?

Design detaljer

Kohorter og interventioner

Gruppe / kohorte
Adult patients admitted for acute cardiac illness/elective cardiac procedures on ECG monitoring

Hvad måler undersøgelsen?

Primære resultatmål

Resultatmål
Foranstaltningsbeskrivelse
Tidsramme
Occurrence of sustained ventricular tachycardia or ventricular fibrillation
Tidsramme: During admission
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)
During admission

Sekundære resultatmål

Resultatmål
Foranstaltningsbeskrivelse
Tidsramme
Secondary outcome measure
Tidsramme: During admission
- A 'textbook' outcome (no adverse events) (Binary outcome measure 0 = no event during admission, 1 = event during admission)
During admission
Secondary Outcome Measure
Tidsramme: during admission
- 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)
during admission
Secondary outcome measure
Tidsramme: During admission
- In hospital death/cardiovascular in-hospital death (include cause if available) (Binary outcome measure 0 = no event during admission, 1 = event during admission)
During admission
Secondary outcome measure
Tidsramme: During admission
- Pulseless electrical activity (PEA) and asystole (Binary outcome measure 0 = no event during admission, 1 = event during admission)
During admission
Performance of AI prediction model
Tidsramme: During admission
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
During admission

Samarbejdspartnere og efterforskere

Det er her, du vil finde personer og organisationer, der er involveret i denne undersøgelse.

Sponsor

Catharina Ziekenhuis Eindhoven

Efterforskere

  • Ledende efterforsker: Luuk C Otterspoor, Dr. M.D., Catharina Ziekenhuis Eindhoven

Datoer for undersøgelser

Disse datoer sporer fremskridtene for indsendelser af undersøgelsesrekord og resumeresultater til ClinicalTrials.gov. Studieregistreringer og rapporterede resultater gennemgås af National Library of Medicine (NLM) for at sikre, at de opfylder specifikke kvalitetskontrolstandarder, før de offentliggøres på den offentlige hjemmeside.

Studer store datoer

Studiestart (Faktiske)

1. januar 2023

Primær færdiggørelse (Anslået)

1. april 2029

Studieafslutning (Anslået)

1. april 2029

Datoer for studieregistrering

Først indsendt

12. august 2026

Først indsendt, der opfyldte QC-kriterier

26. august 2026

Først opslået (Faktiske)

28. august 2026

Opdateringer af undersøgelsesjournaler

Sidste opdatering sendt (Faktiske)

28. august 2026

Sidste opdatering indsendt, der opfyldte kvalitetskontrolkriterier

26. august 2026

Sidst verificeret

1. august 2026

Mere information

Begreber relateret til denne undersøgelse

Nøgleord

Yderligere relevante MeSH-vilkår

Andre undersøgelses-id-numre

  • nWMO-2025.186
  • project code 24PPS046 (Andet bevillings-/finansieringsnummer: National collaboration: Holland High Tech, Eindhoven University of Technology, Catharina Hospital Eindhoven, Philips)

Plan for individuelle deltagerdata (IPD)

Planlægger du at dele individuelle deltagerdata (IPD)?

INGEN

IPD-planbeskrivelse

Sensitive patient information, no permission to share outside of hospital

Lægemiddel- og udstyrsoplysninger, undersøgelsesdokumenter

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Ingen

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