Respiratory Insufficiency Clinical Trial
Official title:
ARM-ED: Advanced Respiratory Monitoring Events in Drug Toxicity - An Emergency Department Feasibility Study of the Utilisation of a Wearable Device in Patients With Sedative Effects of Drugs
There is a drug-related death crisis in Scotland. The majority of these deaths have involved the misuse of opiates (e.g. heroin) and benzodiazepines (e.g. valium) which cause an individual to stop breathing. The Advanced Respiratory Monitoring Events in Drug Toxicity (ARM-ED) study is a study investigating whether a wearable sensor can help detect problems with breathing in patients who have had drugs or medications that may cause this effect. The study will span a year and will study two groups of patients - those who attend with actual or expected respiratory depression secondary to acute drug toxicity and individuals who have undergone procedural sedation and analgaesia in the Emergency Department.
This study aims to assess if it is feasible to collect respiratory waveform data using an advanced respiratory monitoring device named Pneumowave and whether the device is user friendly in terms of nurse, clinician, and patient. This is an observational cohort study which utilises passive non-invasive data collection. The device, Pneumowave, will be studied in two distinct groups of patients: those who attend with actual or expected respiratory depression secondary to acute drug toxicity (Group 1) and individuals who have undergone procedural sedation and analgaesia (PSA) in the ED (Group 2). Participants will be studied for the duration of their ED attendance or in the case of PSA for the duration of their sedation and recovery period. They will be followed up via electronic notes 28 days later to identify adverse outcome and to link cases to available toxicology screens performed. The target number of participants in this study is 100. 50 patients who fit group 1 characteristics and 50 patients who fit group 2 characteristics. Data from Pneumowave will be analysed in parallel with de-identified clinical and vital sign observational data to inform artificial intelligence driven predictive modelling algorithms. This study will inform on the utilisation and usability of a wearable device for monitoring an individual's respiratory patterns following the effects of sedative drug use. It will add understanding to potential use of such a device to predict the respiratory compromise in the wearer and alert appropriate stakeholders for timely intervention and ultimately prevention of the wearer's morbidity and mortality. ;
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