Logo

American Heart Association

  15
  0


Final ID: Or103

Automated cardiac arrest detection incorporated into a wristband: validation in patients with induced ventricular fibrillation

Abstract Body: Background
Survival from unwitnessed out-of-hospital cardiac arrest is poor, often due to delayed activation of the emergency medical chain. Wearable technology capable of automated cardiac arrest detection and alerting could trigger rapid medical assistance. In a previous study, we developed an algorithm for cardiac arrest detection based on photoplethysmography (PPG) data from patients with induced circulatory arrest, achieving 98% sensitivity. The next step is validation of the algorithm in patients with shockable cardiac arrest.

Goal
To study the performance of the developed PPG-algorithm in patients with cardiac arrest based on induced ventricular fibrillation (VF).

Methods
From the prospective multicenter study DETECT-1, we selected all adult patients who underwent short-lasting VF induction as standard practice during subcutaneous implantable cardioverter defibrillator (S-ICD). Patients wore a PPG-wristband (CardioWatch) during the entire procedure. A cardiac arrest event was defined as induced VF. Continuous electrocardiogram (ECG) and arterial blood pressure were monitored as a reference standard. The primary endpoint was the sensitivity for the detection of cardiac arrest, as assessed using the previously developed PPG-algorithm. This PPG-based algorithm detects the absence of pulsations based on signal amplitude and waveform characteristics.

Results
In total, 14 patients were included with a median age of 46 years (IQR 33-54), of whom four where female. Fifteen VF inductions were performed, see Figure 1. The sensitivity for cardiac arrest detection was 100% (95% confidence interval [CI] 75%-100%). No false positive cardiac arrest alerts occurred in 15 hours of PPG data, resulting in a positive predictive value of 100% (95% CI 75%-100%). Return of PPG pulsations after the S-ICD shock were detected successfully in all patients.

Conclusions
The PPG-algorithm for cardiac arrest detection performs excellent in the detection of induced VF. As a next step, the algorithm needs to be validated in non-shockable cardiac arrest and potential false positive alarms during daily life use need to be studied.
  • Edgar, Roos  ( Radboud University Medical Center , Nijmegen , Netherlands )
  • Ronner, Eelko  ( Reinier de Graaf hospital , Delft , Netherlands )
  • Cetinyurek Yavuz, Aysun  ( Radboud University Medical Center , Nijmegen , Netherlands )
  • Vernooy, Kevin  ( Maastricht UMC , Maastricht , Netherlands )
  • Boersma, Eric  ( Erasmus MC , Rotterdam , Netherlands )
  • Stas, Peter  ( Corsano Health , The Hague , Netherlands )
  • Royen, Niels  ( Radboud University Medical Center , Nijmegen , Netherlands )
  • Bonnes, Judith  ( Radboud University Medical Center , Nijmegen , Netherlands )
  • Scholte, Niels  ( Erasmus Medical Center , Rotterdam , Netherlands )
  • Ebrahimkheil, Kambiz  ( Corsano Health , The Hague , Netherlands )
  • Jansen, Catharina  ( Radboud University Medical Center , Nijmegen , Netherlands )
  • Beukema, Rypko  ( Radboud University Medical Center , Nijmegen , Netherlands )
  • Brouwer, Marc  ( Radboud University Medical Center , Nijmegen , Netherlands )
  • Yap, Sing-chien  ( Erasmus MC , Rotterdam , Netherlands )
  • Mafi-rad, Masih  ( Maastricht UMC , Maastricht , Netherlands )
  • Knops, Reinoud  ( Amsterdam University Medical Center , Amsterdam , Netherlands )
  • Author Disclosures:
    Roos Edgar: DO NOT have relevant financial relationships | Eelko Ronner: No Answer | Aysun Cetinyurek Yavuz: No Answer | Kevin Vernooy: No Answer | Eric Boersma: No Answer | Peter Stas: DO NOT have relevant financial relationships | Niels Royen: No Answer | Judith Bonnes: No Answer | Niels Scholte: No Answer | Kambiz Ebrahimkheil: No Answer | Catharina Jansen: DO NOT have relevant financial relationships | Rypko Beukema: No Answer | Marc Brouwer: No Answer | Sing-Chien Yap: DO have relevant financial relationships ; Consultant:Boston Scientific:Active (exists now) ; Speaker:Boston Scientific:Past (completed) ; Research Funding (PI or named investigator):Biotronik:Past (completed) ; Research Funding (PI or named investigator):Medtronic:Past (completed) ; Research Funding (PI or named investigator):Boston Scientific:Active (exists now) ; Research Funding (PI or named investigator):J&J:Active (exists now) | Masih Mafi-Rad: DO NOT have relevant financial relationships | Reinoud Knops: No Answer
Meeting Info:

Resuscitation Science Symposium 2025

2025

New Orleans, Louisiana

Session Info:

Best of the Best Abstract Oral Session

Saturday, 11/08/2025 , 04:15PM - 05:15PM

ReSS25 Abstract Oral Session

More abstracts on this topic:
Active Decompression during Automated Head-up Cardiopulmonary Resuscitation

Pourzand Pouria, Metzger Anja, Moore Johanna, Suresh Mithun, Salverda Bayert, Hai Hamza, Kaizer Alexander, Duval Sue, Bachista Kerry, Lurie Keith

Agency Epinephrine Dosing Intervals and Patient Characteristics in Out-of-Hospital Cardiac Arrest: A National EMS Study

Defilippo Michael, Braude Darren, Root Christopher, Covert Harold, Fisher Benjamin, Huebinger Ryan

More abstracts from these authors:
Automated cardiac arrest detection incorporated in a wristband: First experience with spontaneous cardiac arrest detection

Edgar Roos, Van Mieghem Nicolas, Boersma Eric, Cetinyurek Yavuz Aysun, Stas Peter, Royen Niels, Bonnes Judith, Scholte Niels, Ebrahimkheil Kambiz, Brouwer Marc, Beukema Rypko, Mafi-rad Masih, Vernooy Kevin, Yap Sing, Ronner Eelko

Automated cardiac arrest detection using a photoplethysmography wristband: Evaluation of the time to detection of the circulatory arrest event

Edgar Roos, Van Mieghem Nicolas, Boersma Eric, Cetinyurek Yavuz Aysun, Stas Peter, Royen Niels, Bonnes Judith, Scholte Niels, Ebrahimkheil Kambiz, Brouwer Marc, Beukema Rypko, Mafi-rad Masih, Vernooy Kevin, Yap Sing, Ronner Eelko

You have to be authorized to contact abstract author. Please, Login
Not Available