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.

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.

Inclusion Criteria:

• Inclusion criteria

  • Adult patients with respiratory failure of any cause requiring hospital admission, oxygen therapy and routine NEWS-2 physiology observations.
  • CARP detailed sub-study Adult patients with respiratory failure who are suitable for opportunistically acquired serial detailed physiology measurements taken alongside routine clinical care by study team.
  • CARP follow-up remote-monitoring sub-study Adult patients with respiratory failure who have provided informed consent and have a smartphone to connect to Fitbit and Lenus accounts for postdischarge wearable device data capture.

Exclusion Criteria:

• Exclusion criteria • Lack of capacity or inability to comprehend informed consent.

Potential participants with respiratory failure will be identified by the clinical teams in the emergency departments, admissions units, respiratory wards or high dependency units of the study sites. Patient information sheets would be provided to potential participants. Study team will liase with clinical staff to identify potential participants and maintain a screening and recruitment log. Based on this information, a member of the team delivering the trial with appropriate knowledge will assess eligibility against inclusion and exclusion criteria. No additional tests are required to determine eligibility.