Altair medical has developed a pre-commercial investigational wearable (chest-worn) biosensor which can measure continuous respiratory rate and respiratory events. This sensor has been verified to have good correlation with reference impedance plethysmography data.~Inclusion criteria:~All inpatients in the QEUH with respiratory failure from any cause.~Exclusion criteria:~Lack of capacity to consent~Physiology data will be correlated with event time-course data including oxygen and breathing support requirements, deterioration, hospital discharge and status at 28 days and 90 days post discharge.~A small subset of patients will have further investigations - parasternal EMG; thoracic electrical impedance tomography; forced oscillometry and post discharge Altair and Fitbit data.~Study analysis will include machine learning model development with the objective of developing risk-predictions for clinically significant deteriorations.
The anticipated second wave of COVID-19 cases will present healthcare system challenges, including requirement to monitor large numbers of patients for deteriorating respiratory failure. Rising respiratory rate can identify deterioration requiring escalation of care. However constant monitoring of respiratory rate can be challenging outwith critical care units due to feasibility and inaccuracy of intermittent measurements.~Wearable biosensors which allows for remote patient monitoring of RR is therefore attractive, particularly when combined in a dashboard with clinical summary data. This would establish source data and infrastructure for the training and validation of machine-learning models, with decision support risk-predictions prioritising alerts and clinician reviews.