Technical design and performance of the NEMO3 detector

The development of the NEMO3 detector, which is now running in the Frejus Underground Laboratory (L.S.M. Laboratoire Souterrain de Modane), was begun more than ten years ago. The NEMO3 detector uses a tracking-calorimeter technique in order to investigate double beta decay processes for several isotopes. The technical description of the detector is followed by the presentation of its performance.Comment: Preprint submitted to Nucl. Instrum. Methods A Corresponding author: Corinne Augier ([email protected]

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