Ta strona została przetłumaczona automatycznie i dokładność tłumaczenia nie jest gwarantowana. Proszę odnieść się do angielska wersja za tekst źródłowy.

Predict Arrhythmia Risk Using Intelligent Software (PARIS)

26 sierpnia 2026 zaktualizowane przez: 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.

Przegląd badań

Status

Rekrutacyjny

Warunki

Szczegółowy opis

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

Typ studiów

Obserwacyjny

Zapisy (Szacowany)

3000

Kontakty i lokalizacje

Ta sekcja zawiera dane kontaktowe osób prowadzących badanie oraz informacje o tym, gdzie badanie jest przeprowadzane.

Kontakt w sprawie studiów

Nazwa: Maud E Kortman, M.D.
Numer telefonu: 040 239 9111
E-mail: maud.kortman@catharinaziekenhuis.nl

Kopia zapasowa kontaktu do badania

Nazwa: Luuk C Otterspoor, Dr. M.D.
E-mail: luuk.otterspoor@catharinaziekenhuis.nl

Lokalizacje studiów

Holandia
- North Brabant
  - Eindhoven, North Brabant, Holandia, 5623 EJ
    - Rekrutacyjny
    - Catharina Hospital Eindhoven
    - Kontakt:
      
      Maud E Kortman, M.D.
      
      Numer telefonu: 040 239 9111
      
      E-mail: maud.kortman@catharinaziekenhuis.nl
    - Główny śledczy:
      
      Luuk C Otterspoor, Dr. M.D.

Kryteria uczestnictwa

Badacze szukają osób, które pasują do określonego opisu, zwanego kryteriami kwalifikacyjnymi. Niektóre przykłady tych kryteriów to ogólny stan zdrowia danej osoby lub wcześniejsze leczenie.

Kryteria kwalifikacji

Wiek uprawniający do nauki

Dorosły
Starszy dorosły

Akceptuje zdrowych ochotników

Nie

Metoda próbkowania

Próbka bez prawdopodobieństwa

Badana populacja

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

Opis

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.

Plan studiów

Ta sekcja zawiera szczegółowe informacje na temat planu badania, w tym sposób zaprojektowania badania i jego pomiary.

Jak projektuje się badanie?

Szczegóły projektu

Liczba grup / kohort

Kohorty i interwencje

Grupa / Kohorta
Adult patients admitted for acute cardiac illness/elective cardiac procedures on ECG monitoring

Co mierzy badanie?

Podstawowe miary wyniku

Miara wyniku	Opis środka	Ramy czasowe
Occurrence of sustained ventricular tachycardia or ventricular fibrillation Ramy czasowe: 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

Miary wyników drugorzędnych

Miara wyniku	Opis środka	Ramy czasowe
Secondary outcome measure Ramy czasowe: 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 Ramy czasowe: 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 Ramy czasowe: 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 Ramy czasowe: 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 Ramy czasowe: 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

Współpracownicy i badacze

Tutaj znajdziesz osoby i organizacje zaangażowane w to badanie.

Sponsor

Catharina Ziekenhuis Eindhoven

Śledczy

Główny śledczy: Luuk C Otterspoor, Dr. M.D., Catharina Ziekenhuis Eindhoven

Daty zapisu na studia

Daty te śledzą postęp w przesyłaniu rekordów badań i podsumowań wyników do ClinicalTrials.gov. Zapisy badań i zgłoszone wyniki są przeglądane przez National Library of Medicine (NLM), aby upewnić się, że spełniają określone standardy kontroli jakości, zanim zostaną opublikowane na publicznej stronie internetowej.

Główne daty studiów

Rozpoczęcie studiów (Rzeczywisty)

1 stycznia 2023

Zakończenie podstawowe (Szacowany)

1 kwietnia 2029

Ukończenie studiów (Szacowany)

1 kwietnia 2029

Daty rejestracji na studia

Pierwszy przesłany

12 sierpnia 2026

Pierwszy przesłany, który spełnia kryteria kontroli jakości

26 sierpnia 2026

Pierwszy wysłany (Rzeczywisty)

28 sierpnia 2026

Aktualizacje rekordów badań

Ostatnia wysłana aktualizacja (Rzeczywisty)