U.S., Sept. 1 -- ClinicalTrials.gov registry received information related to the study (NCT07794007) titled 'Automated Apnoea Detection in Preterms on Non-invasive Ventilation' on Aug. 25.
Brief Summary: The aim of this study is to monitor the frequency of apnoeas (pauses in breathing) on various methods of non-invasive respiratory support that are detected by an automated machine-learning (ML) model based on diaphragmatic electromyography (dEMG), in infants born at less than 32 weeks of gestation.
Our hypothesis is that the ML algorithm will improve identification of apnoeic episodes and their classification to central or obstructive.
The study will measure outcomes including the number of apnoeic episodes during the monitoring period, ...