Automated cardiac arrest DETECTion incorporated into a wristband: validation of a photoplethysmography algorithm in patients with spontaneous and induced cardiac arrest
Authors: Edgar R , Scholte N T B , Ebrahimkheil K , Brouwer M A , Beukema R J , Mafi-Rad M , Vernooy K , Yap S C , Ronner E , Van Mieghem N M , Boersma E , Cetinyurek-Yavuz A , Stas P C , Van Royen N , Bonnes J L 
Published: October 2024

Abstract

Background
Although survival from out-of-hospital cardiac arrest (OHCA) has improved, this does not apply to unwitnessed cases, as the arrest is often recognized too late. Automated cardiac arrest detection and alarming using a wristband is a promising technology to facilitate early assistance after cardiac arrest in a home setting. In the DETECT-1 study, a photoplethysmography(PPG) algorithm for circulatory arrest detection has been developed in patients with induced circulatory arrest.

Purpose
To assess the performance of the developed PPG algorithm for circulatory arrest detection in: 1) patients with spontaneous cardiac arrest; 2) subjects with induced circulatory arrest using blood pressure cuff inflation.

Methods
We selected patients with episodes of spontaneous cardiac arrest who participated in the DETECT-1 study and patients/healthy subjects with short-lasting induced circulatory arrest using blood pressure cuff inflations from the DETECT-1 and DETECT-2 studies. The DETECT-1 study included patients who underwent transcatheter aortic valve implantation (TAVI), subcutaneous ICD implantation, or ventricular tachycardia ablation. Included patients wore the PPG-wristband during the procedure. Continuous ECG and invasive blood pressure data were collected as reference standard. The DETECT-2 study included healthy volunteers who wore the PPG-wristband during physical exercise. Sensitivity for spontaneous and induced circulatory arrest and false positive alarms were assessed using the previously developed algorithm for circulatory arrest detection. All episodes were analyzed as individual events.

Results
A total of 39 individuals were included; nine patients with spontaneous cardiac arrests during TAVI and 20 subjects with 116 induced circulatory arrests. Of the patients with spontaneous cardiac arrest, two had ventricular fibrillation, five had pulseless electrical activity (figure), and two had asystole. Eight out of nine cardiac arrest events were detected by the circulatory arrest detection algorithm (sensitivity 89% [95% CI 51-99%]). Of the subjects with induced circulatory arrests, the PPG algorithm detected 114 induced circulatory arrests, yielding a sensitivity of 98% (95% CI 93-100%). In the entire group, there were no false positive alarms during 60 recording hours.

Conclusions
Automated cardiac arrest detection using a PPG-wristband is feasible with excellent sensitivity for both spontaneous and induced circulatory arrest. False positive alarms were absent in this controlled setting. Further study is warranted to assess algorithm performance in a larger sample of spontaneous cardiac arrests, and false positive alarms during daily life use. If available, automated cardiac arrest detection and alarming has the potential to markedly increase survival from OHCA in a home setting.Episode of spontaneous cardiac arrest