AIMC Topic: Sepsis

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A machine learning model for the early diagnosis of bloodstream infection in patients admitted to the pediatric intensive care unit.

PloS one May 1, 2024
Bloodstream infection (BSI) is associated with increased morbidity and mortality in the pediatric intensive care unit (PICU) and high healthcare costs. Early detection and appropriate treatment of BSI may improve patient's outcome. Data on machine-le...
Sepsis Adolescent Child, Preschool Child Intensive Care Units, Pediatric Bacteremia Infant, Newborn Male Infant Machine Learning Retrospective Studies Humans Female Early Diagnosis
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Early prediction of sepsis-induced respiratory tract infection using a biomarker-based machine-learning algorithm.

Scandinavian journal of clinical and laboratory investigation Apr 29, 2024
Early and differential diagnosis of sepsis is essential to avoid unnecessary antibiotic use and further reduce patient morbidity and mortality. Here, we aimed to identify predictors of sepsis and advance a machine-learning strategy to predict sepsis-...
Humans Machine Learning Middle Aged Sepsis Respiratory Tract Infections Female Aged Male Algorithms Biomarkers Retrospective Studies
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Predicting community acquired bloodstream infection in infants using full blood count parameters and C-reactive protein; a machine learning study.

European journal of pediatrics Apr 18, 2024
Early recognition of bloodstream infection (BSI) in infants can be difficult, as symptoms may be non-specific, and culture can take up to 48 h. As a result, many infants receive unneeded antibiotic treatment while awaiting the culture results. In thi...
Sensitivity and Specificity Male Infant Retrospective Studies Female Infant, Newborn Predictive Value of Tests C-Reactive Protein Blood Cell Count Sepsis Bacteremia Decision Trees Humans Machine Learning Biomarkers
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Development and Validation of an Interpretable Conformal Predictor to Predict Sepsis Mortality Risk: Retrospective Cohort Study.

Journal of medical Internet research Mar 18, 2024
BACKGROUND: Early and reliable identification of patients with sepsis who are at high risk of mortality is important to improve clinical outcomes. However, 3 major barriers to artificial intelligence (AI) models, including the lack of interpretabilit...
Artificial Intelligence Retrospective Studies Clinical Decision-Making Humans Hospitals, Teaching Adult Sepsis Multicenter Studies as Topic
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Real-time machine learning-assisted sepsis alert enhances the timeliness of antibiotic administration and diagnostic accuracy in emergency department patients with sepsis: a cluster-randomized trial.

Internal and emergency medicine Feb 21, 2024
Machine learning (ML) has been applied in sepsis recognition across different healthcare settings with outstanding diagnostic accuracy. However, the advantage of ML-assisted sepsis alert in expediting clinical decisions leading to enhanced quality fo...
Emergency Service, Hospital Middle Aged Sepsis Triage Humans Aged Machine Learning Adult Anti-Bacterial Agents Male Female
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Early detection of late-onset neonatal sepsis from noninvasive biosignals using deep learning: A multicenter prospective development and validation study.

International journal of medical informatics Feb 4, 2024
BACKGROUND: Neonatal sepsis is responsible for significant morbidity and mortality worldwide. Its accurate and timely diagnosis is hindered by vague symptoms and the urgent necessity for early antibiotic intervention. The gold standard for diagnosing...
Sepsis Neonatal Sepsis Humans Algorithms Prospective Studies Infant, Newborn Deep Learning
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The critical role of neutrophil-endothelial cell interactions in sepsis: new synergistic approaches employing organ-on-chip, omics, immune cell phenotyping and modeling to identify new therapeutics.

Frontiers in cellular and infection microbiology Jan 8, 2024
Sepsis is a global health concern accounting for more than 1 in 5 deaths worldwide. Sepsis is now defined as life-threatening organ dysfunction caused by a dysregulated host response to infection. Sepsis can develop from bacterial (gram negative or g...
Neutrophils Cell Communication Computer Simulation Humans Animals Machine Learning Sepsis
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Deep learning-based prediction of in-hospital mortality for sepsis.

Scientific reports Jan 3, 2024
As a serious blood infection disease, sepsis is characterized by a high mortality risk and many complications. Accurate assessment of mortality risk of patients with sepsis can help physicians in Intensive Care Unit make optimal clinical decisions, w...
Hospital Mortality ROC Curve Intensive Care Units Humans Deep Learning Machine Learning Sepsis
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Integrated analysis of single-cell RNA-seq and chipset data unravels PANoptosis-related genes in sepsis.

Frontiers in immunology Jan 3, 2024
BACKGROUND: The poor prognosis of sepsis warrants the investigation of biomarkers for predicting the outcome. Several studies have indicated that PANoptosis exerts a critical role in tumor initiation and development. Nevertheless, the role of PANopto...
Humans B-Lymphocytes Cell Transformation, Neoplastic Algorithms Sepsis Single-Cell Gene Expression Analysis
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TRENDS IN CHOLESTEROL AND LIPOPROTEINS ARE ASSOCIATED WITH ACUTE RESPIRATORY DISTRESS SYNDROME INCIDENCE AND DEATH AMONG SEPSIS PATIENTS.

Shock (Augusta, Ga.) Dec 28, 2023
Objective: Compare changes in cholesterol and lipoprotein levels occurring in septic patients with and without acute respiratory distress syndrome (ARDS) and by survivorship. Methods: We reanalyzed data from prospective sepsis studies. Cholesterol an...
Lipoproteins Cholesterol Sepsis Apolipoprotein A-I Incidence Humans Cholesterol, LDL Respiratory Distress Syndrome Prospective Studies
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