Automated Cardiac Arrest Detection and Alerting in Daily Life

NCT ID: NCT06692374

Last Updated: 2024-11-18

Basic Information

• Recruitment Status: NOT_YET_RECRUITING
• Total Enrollment: 200 participants
• Study Classification: OBSERVATIONAL
• Study Start Date: 2025-01-01
• Study Completion Date: 2028-01-01

Brief Summary

Surviving a cardiac arrest that happens outside the hospital depends on quickly recognizing the event and immediately starting CPR. Survival rates have improved when cardiac arrest is witnessed, but when it isn't, help often arrives too late. Wearable biosensors, like special wristbands, could detect cardiac arrest automatically and alert emergency responders, providing faster help.

In the already finished DETECT-1 study, the investigators developed a system that uses wrist-worn sensors to identify cardiac arrest. The goal of the current study is to test how well this system works in people who have an implantable cardioverter defibrillator (ICD). An ICD is a device that monitors and treats dangerous heart rhythms. Study participants will wear a medical wristband with sensors that monitor the heartrate and movement during their daily activities to see if the system accurately detects cardiac arrest.

Detailed Description

Survival from out-of-hospital cardiac arrest (OHCA) depends on fast recognition of cardiac arrest and immediate initiation of cardiopulmonary resuscitation (CPR). While survival chances for witnessed OHCA have increased, unwitnessed cases still often receive help too late. Wearable biosensor technology with the functionality of automated cardiac arrest detection and activation of the emergency medical chain would offer a potential solution to provide early help. In the recently published DETECT-1 study, an algorithm for automated cardiac arrest detection using wrist-derived photoplethysmography (PPG) was recently developed.

The current study is a prospective multicenter observational cohort study to validate the sensitivity of the developed cardiac arrest detection algorithm in patients with an implantable cardioverter defibrillator (ICD) during daily life. The study population includes patients with an ICD. Study participants will wear a medical wristband with PPG and accelerometer sensors during daily life.

Conditions

Cardiac Arrest (CA); Sudden Death, Cardiac

Study Design

• Observational Model Type: COHORT
• Study Time Perspective: PROSPECTIVE

Eligibility Criteria

Inclusion Criteria

• Patients with an implantable cardioverter defibrillator (ICD)
• Age 18 years or older
• Fitting the wristband
• In possession of a smartphone that is compatible with the wristband

Exclusion Criteria

• Known hemodynamically relevant bilateral subclavian artery stenosis
• Medical issues that interfere with wearing of the wristband (e.g. skin disorders)
• Insufficient skills to operate with the device/app

• Minimum Eligible Age: 18 Years
• Eligible Sex: ALL
• Accepts Healthy Volunteers: No

Sponsors

Corsano Health

UNKNOWN

Sponsor Role: collaborator

Radboud University Medical Center

OTHER

Sponsor Role: lead

Responsible Party

Responsibility Role: SPONSOR

Locations

RadboudUMC

Nijmegen, Gelderland, Netherlands

Countries

Netherlands

Facility Contacts

Judith J Bonnes, MD PhD

Role: primary

judith.bonnes@radboudumc.nl

+31 (0)24 3616785

References

Edgar R, Scholte NTB, Ebrahimkheil K, Brouwer MA, Beukema RJ, Mafi-Rad M, Vernooy K, Yap SC, Ronner E, van Mieghem N, Boersma E, Stas PC, van Royen N, Bonnes JL. Automated cardiac arrest detection using a photoplethysmography wristband: algorithm development and validation in patients with induced circulatory arrest in the DETECT-1 study. Lancet Digit Health. 2024 Mar;6(3):e201-e210. doi: 10.1016/S2589-7500(23)00249-2.

Reference Type: RESULT

PMID: 38395540 (View on PubMed)

Related Links

https://detect-study.com/en/

Related Info

Other Identifiers

116424

Identifier Type: -

Identifier Source: org_study_id