AIMC Topic: Critical Illness

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Reliability of Robotic Telemedicine for Assessing Critically Ill Patients with the Full Outline of UnResponsiveness Score and Glasgow Coma Scale.

Telemedicine journal and e-health : the official journal of the American Telemedicine Association
PURPOSE: Telemedicine is increasingly utilized in the evaluation of critically ill patients, including those with decreased level of consciousness (LOC) or coma. Improving access to providers with neurologic expertise affords earlier triage and direc...

Ultrasound-Assessed Gastric Antral Area Correlates With Aspirated Tube Feed Volume in Enterally Fed Critically Ill Patients.

Nutrition in clinical practice : official publication of the American Society for Parenteral and Enteral Nutrition
BACKGROUND: Enteral tube feed (ETF) intolerance occurs frequently in hospitalized patients and more so in critically ill patients. Most critical care nurses continue to assess gastric residual volume (GRV), especially among those with a history of ET...

Causal Phenotype Discovery via Deep Networks.

AMIA ... Annual Symposium proceedings. AMIA Symposium
The rapid growth of digital health databases has attracted many researchers interested in using modern computational methods to discover and model patterns of health and illness in a research program known as computational phenotyping. Much of the wo...

Influence of the central venous site on the transpulmonary thermodilution parameters in critically ill burn patients.

Burns : journal of the International Society for Burn Injuries
The aim of this study was to verify the measurement concordance of cardiac index (CI), extra-vascular lung water index (EVLWI) and global end diastolic volume index (GEDVI) with transpulmonary thermodilution (TPTD) between the jugular and femoral acc...

Predictive modelling of survival and length of stay in critically ill patients using sequential organ failure scores.

Artificial intelligence in medicine
INTRODUCTION: The length of stay of critically ill patients in the intensive care unit (ICU) is an indication of patient ICU resource usage and varies considerably. Planning of postoperative ICU admissions is important as ICUs often have no nonoccupi...

Propofol-associated Hypertriglyceridemia: Development and Multicenter Validation of a Machine-Learning-Based Prediction Tool.

Journal of intensive care medicine
To develop and validate an explainable machine learning (ML) tool to help clinicians predict the risk of propofol-associated hypertriglyceridemia in critically ill patients receiving propofol sedation. Patients from 11 intensive care units (ICUs) a...

Understanding deep learning models for Length of Stay prediction on critically ill patients through latent space visualization.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Continuous, real-time monitoring of Length of Stay (LoS) for critically ill patients in Intensive Care Units (ICUs) is essential for anticipating patient needs, reduce the risk of adverse events, optimize resource allocation...

Technology advances in the placement of naso-enteral tubes and in the management of enteral feeding in critically ill patients: A narrative study.

Clinical nutrition ESPEN
Enteral feeding needs secure access to the upper gastrointestinal tract, an evaluation of the gastric function to detect gastrointestinal intolerance, and a nutritional target to reach the patient's needs. Only in the last decades has progress been a...

A comprehensive review of ICU readmission prediction models: From statistical methods to deep learning approaches.

Artificial intelligence in medicine
The prediction of Intensive Care Unit (ICU) readmission has become a crucial area of research due to the increasing demand for ICU resources and the need to provide timely interventions to critically ill patients. In recent years, several studies hav...