Which unmet social care needs have the biggest impact on healthy ageing? An analysis of data from the English Longitudinal Study of Ageing.

Background And Aim: Unmet need for social care is linked to numerous adverse health outcomes. Understanding which unmet needs have the biggest impact on healthy ageing could help resource-stretched services prioritise care. To address this evidence gap, our analysis aimed to explore the association between selected individual unmet care needs and an indicator of healthy ageing.

Ecological study of the association between the English national vaccination programme and area deprivation inequalities in COVID-19 mortality.

Objective: To understand how area deprivation inequalities in COVID-19 mortality changed during the national vaccination programme in England and to identify the extent to which these inequalities might be explained by unequal vaccination uptake.

Design: Ecological study.

Setting: 307 Lower Tier Local Authorities in England, March 2020 - December 2022.

iSurgARy: A mobile augmented reality solution for ventriculostomy in resource-limited settings.

Global disparities in neurosurgical care necessitate innovations addressing affordability and accuracy, particularly for critical procedures like ventriculostomy. This intervention, vital for managing life-threatening intracranial pressure increases, is associated with catheter misplacement rates exceeding 30% when using a freehand technique. Such misplacements hold severe consequences including haemorrhage, infection, prolonged hospital stays, and even morbidity and mortality.

Clinical validation of an artificial intelligence-based decision support system for diagnosis and risk stratification of heart failure (STRATIFYHF): a protocol for a prospective, multicentre longitudinal study.

Introduction: Heart failure (HF) is a complex clinical syndrome. Accurate risk stratification and early diagnosis of HF are challenging as its signs and symptoms are non-specific. We propose to address this global challenge by developing the STRATIFYHF artificial intelligence-driven decision support system (DSS), which uses novel analytical methods in determining the risk, diagnosis and prognosis of HF.