BACKGROUND: Acinetobacter baumanni infection is a leading cause of morbidity and mortality in the Intensive Care Unit (ICU). Early recognition of patients at risk for infection allows early proper treatment and is associated with improved outcomes. T...
Early recognition of risk factors for prolonged mechanical ventilation (PMV) could allow for early clinical interventions, prevention of secondary complications such as nosocomial infections, and effective triage of hospital resources. This study tes...
Clinics and research in hepatology and gastroenterology
Nov 30, 2024
OBJECTIVE: Critically ill patients with liver cirrhosis generally have a poor prognosis due to complications such as multiple organ failure. This study aims to develop a machine learning-based prediction model to forecast short-term mortality in crit...
BACKGROUND: New or worsening cognitive impairment or dementia is common in older adults following an episode of critical illness, and screening post-discharge is recommended for those at increased risk. There is a need for prediction models of post-I...
Stroke is a neurological complication that can occur in patients admitted to the intensive care unit (ICU) for non-neurological conditions, leading to increased mortality and prolonged hospital stays. The incidence of stroke in ICU settings is notabl...
BACKGROUND: The burden of atrial fibrillation (AF) in the intensive care unit (ICU) remains heavy. Glycaemic control is important in the AF management. Glycaemic variability (GV), an emerging marker of glycaemic control, is associated with unfavourab...
OBJECTIVES: Cardiac surgery is associated with perioperative complications, some of which might be attributable to hypotension. The Hypotension Prediction Index (HPI), a machine-learning-derived early warning tool for hypotension, has only been evalu...
Sepsis, a life-threatening condition triggered by the body's response to infection, remains a significant global health challenge, annually affecting millions in the United States alone with substantial mortality and healthcare costs. Early predictio...
This study aims to develop a Machine Learning model to assess the risks faced by COVID-19 patients in a hospital setting, focusing specifically on predicting the complications leading to Intensive Care Unit (ICU) admission or mortality, which are min...
OBJECTIVE: The objective was to establish a machine learning-based model for predicting the occurrence and mortality of nonpulmonary sepsis-associated ARDS.
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