Use of a novel smartphone-based application tool for enrolment and randomisation in pre-hospital clinical trials.

The effective recruitment and randomisation of patients in pre-hospital clinical trials presents unique challenges. Owing to the time critical nature of many pre-hospital emergencies and limited resourcing, the use of traditional methods of randomisation that may include centralised telephone or web-based systems are often not practicable or feasible. Previous technological limitations have necessitated that pre-hospital trialists strike a compromise between implementing pragmatic, deliverable study designs, with robust enrolment and randomisation methodologies. In this commentary piece, we present a novel smartphone-based solution that has the potential to align pre-hospital clinical trial recruitment processes to that of best-in-practice in-hospital and ambulatory care based studies.

Bayesian adaptive clinical trial designs for respiratory medicine.

The use of Bayesian adaptive designs for clinical trials has increased in recent years, particularly during the COVID-19 pandemic. Bayesian adaptive designs offer a flexible and efficient framework for conducting clinical trials and may provide results that are more useful and natural to interpret for clinicians, compared to traditional approaches. In this review, we provide an introduction to Bayesian adaptive designs and discuss its use in recent clinical trials conducted in respiratory medicine. We illustrate this approach by constructing a Bayesian adaptive design for a multi-arm trial that compares two non-invasive ventilation treatments to standard oxygen therapy for patients with acute cardiogenic pulmonary oedema. We highlight the benefits and some of the challenges involved in designing and implementing Bayesian adaptive trials.