AIMC Topic: Intensive Care Units, Pediatric

Clear Filters Showing 31 to 40 of 51 articles

Interhospital Transfer of Children in Septic Shock: A Clinician Interview Qualitative Study.

Journal of intensive care medicine Dec 14, 2016
OBJECTIVE:: To determine the factors that influence the decision to transfer children in septic shock from level II to level I pediatric intensive care unit (PICU) care.
Vasoconstrictor Agents Patient Transfer Fluid Therapy Male Intensive Care Units, Pediatric Extracorporeal Membrane Oxygenation Humans Qualitative Research Shock, Septic Combined Modality Therapy Adolescent Renal Replacement Therapy Catheterization, Central Venous Clinical Decision-Making
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The predictive value of soluble endothelial selectin plasma levels in children with acute lung injury.

Journal of critical care Dec 23, 2015
UNLABELLED: The study aimed to evaluate the value of soluble endothelial selectin (sE-selectin) plasma level measurement in predicting acute lung injury (ALI) outcome in children.
Acute Lung Injury Selectins Predictive Value of Tests C-Reactive Protein Egypt Prospective Studies Biomarkers Prognosis Humans Adolescent Child, Preschool Child Female Intensive Care Units, Pediatric Male Respiration, Artificial
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Heart Rate and Body Temperature Relationship in Children Admitted to PICU: A Machine Learning Approach.

IEEE transactions on bio-medical engineering Aug 1, 2025
UNLABELLED: Vital signs are crucial clinical measures, with body temperature (BT) and heart rate (HR) being particularly significant. While their association has been studied in adults and children, research in Pediatric Intensive Care Unit (PICU) se...
Infant, Newborn Male Infant Humans Machine Learning Female Intensive Care Units, Pediatric Signal Processing, Computer-Assisted Heart Rate Body Temperature Adolescent Child, Preschool Child
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Diagnostic Stewardship of Blood Cultures in the Pediatric ICU Using Machine Learning.

Hospital pediatrics Jun 1, 2025
OBJECTIVE: The medical community recently experienced a severe shortage of blood culture media bottles. Rates of blood stream infection (BSI) among critically ill children are low. We sought to design a machine learning (ML) model able to identify ch...
Infant Adolescent Child, Preschool Bacteremia Blood Culture Child Intensive Care Units, Pediatric Retrospective Studies Humans Female Machine Learning Male
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Achieving SDoH Resource Equity in PICU Using an AI-Enabled Patient Navigator.

Studies in health technology and informatics May 15, 2025
Trauma care coordination in the pediatric intensive care unit (PICU), including personalization of resources based on social determinants of health (SDoH), is challenging for already strained healthcare providers. Patient SDoH data collection is inco...
Child Intensive Care Units, Pediatric Health Equity Social Determinants of Health Humans Artificial Intelligence Resource Allocation
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PROGNOSTIC ACCURACY OF MACHINE LEARNING MODELS FOR IN-HOSPITAL MORTALITY AMONG CHILDREN WITH PHOENIX SEPSIS ADMITTED TO THE PEDIATRIC INTENSIVE CARE UNIT.

Shock (Augusta, Ga.) Jan 1, 2025
Objective: The Phoenix sepsis criteria define sepsis in children with suspected or confirmed infection who have ≥2 in the Phoenix Sepsis Score. The adoption of the Phoenix sepsis criteria eliminated the Systemic Inflammatory Response Syndrome criteri...
Child Hospital Mortality Intensive Care Units, Pediatric Sepsis Adolescent Child, Preschool Shock, Septic Machine Learning Prognosis Retrospective Studies Female Male Infant Humans
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Narrowing the gap: expected versus deployment performance.

Journal of the American Medical Informatics Association : JAMIA Aug 18, 2023
OBJECTIVES: Successful model development requires both an accurate a priori understanding of future performance and high performance on deployment. Optimistic estimations of model performance that are unrealized in real-world clinical settings can co...
Child Intensive Care Units, Pediatric Neural Networks, Computer Retrospective Studies Hospitalization Humans
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Clinical Informatics and Quality Improvement in the Pediatric Intensive Care Unit.

Pediatric clinics of North America Jun 1, 2022
Clinical informatics can support quality improvement and patient safety in the pediatric intensive care unit (PICU) in several ways including data extraction, analysis, and decision support enabled by electronic health records (EHRs), and databases a...
Artificial Intelligence Quality Improvement Humans Electronic Health Records Intensive Care Units, Pediatric Child Decision Support Systems, Clinical
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Neural Networks for Mortality Prediction: Ready for Prime Time?

Pediatric critical care medicine : a journal of the Society of Critical Care Medicine and the World Federation of Pediatric Intensive and Critical Care Societies Jun 1, 2021
Neural Networks, Computer Child Intensive Care Units, Pediatric Humans
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Continuous Prediction of Mortality in the PICU: A Recurrent Neural Network Model in a Single-Center Dataset.

Pediatric critical care medicine : a journal of the Society of Critical Care Medicine and the World Federation of Pediatric Intensive and Critical Care Societies Jun 1, 2021
OBJECTIVES: Develop, as a proof of concept, a recurrent neural network model using electronic medical records data capable of continuously assessing an individual child's risk of mortality throughout their ICU stay as a proxy measure of severity of i...
Humans Infant Intensive Care Units, Pediatric Neural Networks, Computer Child Retrospective Studies ROC Curve Hospital Mortality
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