AIMC Topic: Extracorporeal Membrane Oxygenation

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COMPREHENSIVE CHARACTERIZATION OF CYTOKINES IN PATIENTS UNDER EXTRACORPOREAL MEMBRANE OXYGENATION: EVIDENCE FROM INTEGRATED BULK AND SINGLE-CELL RNA SEQUENCING DATA USING MULTIPLE MACHINE LEARNING APPROACHES.

Shock (Augusta, Ga.)
Background : Extracorporeal membrane oxygenation (ECMO) is an effective technique for providing short-term mechanical support to the heart, lungs, or both. During ECMO treatment, the inflammatory response, particularly involving cytokines, plays a cr...

Machine Learning from Veno-Venous Extracorporeal Membrane Oxygenation Identifies Factors Associated with Neurological Outcomes.

Lung
BACKGROUND: Neurological complications are common in patients receiving veno-venous extracorporeal membrane oxygenation (VV-ECMO) support. We used machine learning (ML) algorithms to identify predictors for neurological outcomes for these patients.

Machine Learning Differentiates Extracorporeal Membrane Oxygenation Mortality Risk Profiles Among Trauma Patients.

The American surgeon
BACKGROUND: Extracorporeal membrane oxygenation (ECMO) is resource intensive with high mortality. Identifying trauma patients most likely to derive a survival benefit remains elusive despite current ECMO guidelines. Our objective was to identify uniq...

Machine Learning Identifies Higher Survival Profile In Extracorporeal Cardiopulmonary Resuscitation.

Critical care medicine
OBJECTIVES: Extracorporeal cardiopulmonary resuscitation (ECPR) has been shown to improve neurologically favorable survival in patients with refractory out-of-hospital cardiac arrest (OHCA) caused by shockable rhythms. Further refinement of patient s...

Neurologic Statistical Prognostication and Risk Assessment for Kids on Extracorporeal Membrane Oxygenation-Neuro SPARK.

ASAIO journal (American Society for Artificial Internal Organs : 1992)
This study presents Neuro-SPARK, the first scoring system developed to assess the risk of neurologic injury in pediatric and neonatal patients on extracorporeal membrane oxygenation (ECMO). Using the extracorporeal life support organization (ELSO) re...

Deetect: A Deep Learning-Based Image Analysis Tool for Quantification of Adherent Cell Populations on Oxygenator Membranes after Extracorporeal Membrane Oxygenation Therapy.

Biomolecules
The strong interaction of blood with the foreign surface of membrane oxygenators during ECMO therapy leads to adhesion of immune cells on the oxygenator membranes, which can be visualized in the form of image sequences using confocal laser scanning m...

Lactate levels as a prognostic predict in cardiogenic shock under venoarterial extracorporeal membrane oxygenation support.

Revista espanola de cardiologia (English ed.)
INTRODUCTION AND OBJECTIVES: Lactate and its evolution are associated with the prognosis of patients in shock, although there is little evidence in those assisted with an extracorporeal venoarterial oxygenation membrane (VA-ECMO). Our objective was t...

A maChine and deep Learning Approach to predict pulmoNary hyperteNsIon in newbornS with congenital diaphragmatic Hernia (CLANNISH): Protocol for a retrospective study.

PloS one
INTRODUCTION: Outcome predictions of patients with congenital diaphragmatic hernia (CDH) still have some limitations in the prenatal estimate of postnatal pulmonary hypertension (PH). We propose applying Machine Learning (ML), and Deep Learning (DL) ...