"I didn't realise they had such a key role." Impact of medical education curriculum change on medical student interactions with nurses: a qualitative exploratory study of student perceptions.

Interprofessional teamwork between healthcare professionals is integral to the delivery of safe high-quality patient care in all settings. Recent reforms of medical education curricula incorporate specific educational opportunities that aim to foster successful interprofessional collaboration and teamwork. The aim of this study was to explore the impact of curriculum reform on medical students' perceptions of their interactions and team-working with nurses. We gathered data from 12 semi-structured individual narrative interviews with a purposive sample of male (n = 6) and female (n = 6) medical students from fourth year (n = 6 following an integrated curriculum) and fifth year (n = 6 following a traditional curriculum). Data were subject to narrative analysis which was undertaken using NVivo software. Overall, there was no notable difference in the responses of the participants on the traditional and integrated curricula about their interactions and team work with nurses. However, the introduction of an integrated medical curriculum was viewed positively but a lack of interprofessional education with nursing students, removal of a nursing placement and shorter clinical placements were perceived as lost opportunities for the development of educationally beneficial relationships. The participants reported that nurses play a number of roles in clinical practice which underpin patient safety including being medical educators who provide a valuable source of support for medical students. The participants highlighted different factors that could hinder or foster effective working relationships such as a lack of understanding of nurses' different professional roles and mutual respect. Medical education needs to provide students with more structured opportunities to work with and learn from nurses in clinical practice. Further research could explore how to foster positive relationships between medical students and nurses.

Modifications in Macular Perfusion and Neuronal Loss After Acute Traumatic Brain Injury.

Purpose: Traumatic brain injury (TBI) causes structural damage and functional impairment in the visual system, often with retinal ganglion cell (RGC) degeneration occurring without visual symptoms. RGC degeneration is associated with reduced retinal blood-flow, however, it is not known whether reductions in perfusion precede or are secondary to neurodegeneration. Methods: We conducted a prospective observational single-center case series. Patients were included if they were admitted to the hospital after acute TBI and underwent ophthalmic clinical examination, including optical coherence tomography (OCT) and OCT angiography (OCTA) acutely and at follow-up. Ganglion cell layer thickness (GCL) thickness, vascular density in the superficial vascular plexus (SVP), and intermediate capillary plexus (ICP) were quantified. Results: Twenty-one patients aged 20 to 65 years (mean = 38 years) including 16 men and 5 women were examined less than 14 days after moderate to severe TBI, and again after 2 to 6 months. Macular structure and perfusion were normal at baseline in all patients. Visual function was abnormal at baseline in three patients and subsequent neurodegeneration and loss of perfusion corresponded to baseline visual function abnormalities. Nine patients (43%) had reduced macular GCL thickness at follow up. Perfusion in the SVP strongly associated with local GCL thickness. The strongest association of the SVP metrics was the sum of vessel density (P < 0.0001). Conclusions: In cases of reduced visual function after TBI, macular perfusion remained normal until reductions in GCL thickness occurred, indicating that perfusion changes were secondary to local GCL loss.

The value of standards for health datasets in artificial intelligence-based applications.

Artificial intelligence as a medical device is increasingly being applied to healthcare for diagnosis, risk stratification and resource allocation. However, a growing body of evidence has highlighted the risk of algorithmic bias, which may perpetuate existing health inequity. This problem arises in part because of systemic inequalities in dataset curation, unequal opportunity to participate in research and inequalities of access. This study aims to explore existing standards, frameworks and best practices for ensuring adequate data diversity in health datasets. Exploring the body of existing literature and expert views is an important step towards the development of consensus-based guidelines. The study comprises two parts: a systematic review of existing standards, frameworks and best practices for healthcare datasets; and a survey and thematic analysis of stakeholder views of bias, health equity and best practices for artificial intelligence as a medical device. We found that the need for dataset diversity was well described in literature, and experts generally favored the development of a robust set of guidelines, but there were mixed views about how these could be implemented practically. The outputs of this study will be used to inform the development of standards for transparency of data diversity in health datasets (the STANDING Together initiative).