Predictions for functional outcome and mortality in acute ischaemic stroke following successful endovascular thrombectomy.

Background: Accurate outcome predictions for patients who had ischaemic stroke with successful reperfusion after endovascular thrombectomy (EVT) may improve patient treatment and care. Our study developed prediction models for key clinical outcomes in patients with successful reperfusion following EVT in an Australian population.

Methods: The study included all patients who had ischaemic stroke with occlusion in the proximal anterior cerebral circulation and successful reperfusion post-EVT over a 7-year period.

The use of natural language processing in detecting and predicting falls within the healthcare setting: a systematic review.

Falls are a common problem associated with significant morbidity, mortality, and economic costs. Current fall prevention policies in local healthcare settings are often guided by information provided by fall risk assessment tools, incident reporting, and coding data. This review was conducted with the aim of identifying studies which utilized natural language processing (NLP) for the automated detection and prediction of falls in the healthcare setting.

Falls and fractures in the acute care setting: A retrospective cohort study.

Objectives: Falls with fracture in hospitalised patients remain a common occurrence with significant morbidity and mortality. Our objectives were to determine the characteristics of patients who suffer falls with fractures in hospital, and to examine whether outcomes in this cohort differ from those of patients who fall without sustaining a fracture.

Methods: Coding data pertaining to a 6-year period (2012-2017) were interrogated.