The use of artificial intelligence (AI) is rapidly growing across many domains, of which the medical field is no exception. AI is an umbrella term defining the practical application of algorithms to generate useful output, without the need of human cognition. Owing to the expanding volume of patient information collected, known as ‘big data’, AI is showing promise as a useful tool in healthcare research and across all aspects of patient
To assess the variation in pre-fracture quality of life (QoL) within the UK hip fracture population, and quantify the nature and strength of associations between QoL and other routinely collected patient characteristics and treatment choices. The World Hip Trauma Evaluation (WHiTE) study, an observational cohort study of UK hip fracture patients, collects a range of routine data and a health-related QoL score (EuroQol five-dimension questionnaire (EQ-5D)). Pre-fracture QoL data are summarized and statistical models fitted to understand associations between QoL, patient characteristics, fracture types, and operations.Aims
Methods
A rigorous approach to developing, delivering and documenting
rehabilitation within randomised controlled trials of surgical interventions
is required to underpin the generation of reliable and usable evidence.
This article describes the key processes used to ensure provision
of good quality and comparable rehabilitation to all participants
of a multi-centre randomised controlled trial comparing surgery
with conservative treatment of proximal humeral fractures in adults. These processes included the development of a patient information
leaflet on self-care during sling immobilisation, the development
of a basic treatment physiotherapy protocol that received input
and endorsement by specialist physiotherapists providing patient
care, and establishing an expectation for the provision of home
exercises. Specially designed forms were also developed to facilitate
reliable reporting of the physiotherapy care that patients received.Objectives
Methods
