Cardiac Arrest (CA), Sudden Death, Cardiac
Conditions
Keywords
Automated cardiac arrest detection, Wearable, Photoplethysmography, Sudden Cardiac Death
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.
Interventions
None listed
Sponsors
Corsano Health
Radboud University Medical Center
Study design
Observational model
COHORT
Time perspective
PROSPECTIVE
Eligibility
Sex/Gender
ALL
Age
18 Years to No maximum
Healthy volunteers
No
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
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Sensitivity for cardiac arrest detection | From the time of enrollment to the end of the wearing period of the wristband (maximal two years) | The number of correctly identified cardiac arrest events by the algorithm devided by the total number of cardiac arrest events. |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Positive predictive value for cardiac arrest detection | From the time of enrollment to the end of the wearing period of the wristband (maximal two years) | The number of true positives devided by the sum of the true positives and false positive cardiac arrest alarms |
| False positive alarm rate | From the time of enrollment to the end of the wearing period of the wristband (maximal two years) | Expressed as the number of false positive non-cancelled cardiac arrest alarms per user year |
Countries
Netherlands
Outcome results
None listed