Automated cardiac arrest detection using a photoplethysmography wristband:algorithm development and validation in patients with induced circulatory arrest in the DETECT-1 study

Background: Unwitnessed out-of-hospital cardiac arrest is associated with low survival chances because of the delayed activation of the emergency medical system in most cases. Automated cardiac arrest detection and alarming using biosensor technology would offer a potential solution to provide early help. We developed and validated an algorithm for automated circulatory arrest detection using wrist-derived photoplethysmography from patients with induced circulatory arrests. Methods: In this prospective multicentre study in three university medical centres in the Netherlands, adult patients (aged 18 years or older) in whom short-lasting circulatory arrest was induced as part of routine practice (transcatheter aortic valve implantation, defibrillation testing, or ventricular tachycardia induction) were eligible for inclusion. Exclusion criteria were a known bilateral significant subclavian artery stenosis or medical issues interfering with the wearing of the wristband. After providing informed consent, patients were equipped with a photoplethysmography wristband during the procedure. Invasive arterial blood pressure and electrocardiography were continuously monitored as the reference standard. Development of the photoplethysmography algorithm was based on three consecutive training cohorts. For each cohort, patients were consecutively enrolled. When a total of 50 patients with at least one event of circulatory arrest were enrolled, that cohort was closed. Validation was performed on the fourth set of included patients. The primary outcome was sensitivity for the detection of circulatory arrest. Findings: Of 306 patients enrolled between March 14, 2022, and April 21, 2023, 291 patients were included in the data analysis. In the development phase (n=205), the first training set yielded a sensitivity for circulatory arrest detection of 100% (95% CI 94–100) and four false positive alarms; the second training set yielded a sensitivity of 100% (94–100), with six false positive alarms; and the third training set yielded a sensitivity of 100% (94–100), with two false positive alarms. In the validation phase (n=86), the sensitivity for circulatory arrest detection was 98% (92–100) and 11 false positive circulatory arrest alarms. The positive predictive value was 90% (95% CI 82–94). Interpretation: The automated detection of induced circulatory arrests using wrist-derived photoplethysmography is feasible with good sensitivity and low false positives. These promising findings warrant further development of this wearable technology to enable automated cardiac arrest detection and alarming in a home setting. Funding: Dutch Heart Foundation (Hartstichting).</p

Rationale and Design of the ISOLATION Study: A Multicenter Prospective Cohort Study Identifying Predictors for Successful Atrial Fibrillation Ablation in an Integrated Clinical Care and Research Pathway

Introduction: Continuous progress in atrial fibrillation (AF) ablation techniques has led to an increasing number of procedures with improved outcome. However, about 30–50% of patients still experience recurrences within 1 year after their ablation. Comprehensive translational research approaches integrated in clinical care pathways may improve our understanding of the complex pathophysiology of AF and improve patient selection for AF ablation. Objectives: Within the “IntenSive mOlecular and eLectropathological chAracterization of patienTs undergoIng atrial fibrillatiOn ablatioN” (ISOLATION) study, we aim to identify predictors of successful AF ablation in the following domains: (1) clinical factors, (2) AF patterns, (3) anatomical characteristics, (4) electrophysiological characteristics, (5) circulating biomarkers, and (6) genetic background. Herein, the design of the ISOLATION study and the integration of all study procedures into a standardized pathway for patients undergoing AF ablation are described. Methods: ISOLATION (NCT04342312) is a two-center prospective cohort study including 650 patients undergoing AF ablation. Clinical characteristics and routine clinical test results will be collected, as well as results from the following additional diagnostics: determination of body composition, pre-procedural rhythm monitoring, extended surface electrocardiogram, biomarker testing, genetic analysis, and questionnaires. A multimodality model including a combination of established predictors and novel techniques will be developed to predict ablation success. Discussion: In this study, several domains will be examined to identify predictors of successful AF ablation. The results may be used to improve patient selection for invasive AF management and to tailor treatment decisions to individual patients