The development of a C5.0 machine learning model in a limited data set to predict early mortality in patients with ARDS undergoing an initial session of prone positioning.

Background: Acute Respiratory Distress Syndrome (ARDS) has a high morbidity and mortality. One therapy that can decrease mortality is ventilation in the prone position (PP). Patients undergoing PP are amongst the sickest, and there is a need for early identification of patients at particularly high risk of death.

Fluid management of acute kidney injury.

Purpose Of Review: Acute kidney injury (AKI) is commonly encountered in critical care medicine as is intravenous fluid therapy. It is accepted that there is interplay between fluid use and AKI, both potentially positive and negative. An understanding of the physiological rationale for fluid is important to help clinicians when considering fluid therapy in patients with, or at risk for AKI; this includes understanding choice of fluid, method of monitoring, administration and clinical sequelae.

Barriers to female leadership in intensive care medicine: insights from an ESICM NEXT & Diversity Monitoring Group Survey.

Background: The underrepresentation of women in leadership remains a pervasive issue, prompting a critical examination of support mechanisms within professional settings. Previous studies have identified challenges women face, ranging from limited visibility to barriers to career advancement. This survey aims to investigate perceptions regarding the effectiveness of women's leadership programs, mentoring initiatives, and a specialized communication course.

A pilot feasibility study comparing large language models in extracting key information from ICU patient text records from an Irish population.

Background: Artificial intelligence, through improved data management and automated summarisation, has the potential to enhance intensive care unit (ICU) care. Large language models (LLMs) can interrogate and summarise large volumes of medical notes to create succinct discharge summaries. In this study, we aim to investigate the potential of LLMs to accurately and concisely synthesise ICU discharge summaries.