AIMC Topic: Shock, Septic

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Serial change of C1 inhibitor in patients with sepsis--a preliminary report.

The American journal of emergency medicine Dec 19, 2015
OBJECTIVE: C1 inhibitor (C1INH) regulates not only the complement system but also the plasma kallikrein-kinin, fibrinolytic, and coagulation systems. The biologic activities of C1INH can be divided into the regulation of vascular permeability and ant...
Aged Complement C1 Inhibitor Protein Humans Disease Progression Aged, 80 and over Prospective Studies Sepsis Male Intensive Care Units Shock, Septic Middle Aged Female Complement C1 Inactivator Proteins
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Learning a Severity Score for Sepsis: A Novel Approach based on Clinical Comparisons.

AMIA ... Annual Symposium proceedings. AMIA Symposium Nov 5, 2015
Sepsis is one of the leading causes of death in the United States. Early administration of treatment has been shown to decrease sepsis-related mortality and morbidity. Existing scoring systems such as the Acute Physiology and Chronic Health Evaluatio...
Machine Learning Prognosis Sepsis Shock, Septic APACHE Electronic Data Processing Humans
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Clinical Decision Support for Septic Shock in the Emergency Department: A Cluster Randomized Trial.

Pediatrics Jul 1, 2025
BACKGROUND AND OBJECTIVES: Delays in septic shock diagnosis cause preventable mortality in children. Evidence is limited around early recognition strategies. The hypothesis was that clinical decision support (CDS) based on machine-learning predictive...
Humans Machine Learning Anti-Bacterial Agents Prospective Studies Female Male Infant Adolescent Child, Preschool Shock, Septic Emergency Service, Hospital Time-to-Treatment Child Decision Support Systems, Clinical
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Early Prediction of Septic Shock in Emergency Department Using Serum Metabolites.

Journal of the American Society for Mass Spectrometry Jun 4, 2025
Early recognition of septic shock is crucial for improving clinical management and patient outcomes, especially in the emergency department (ED). This study conducted serum metabolomic profiling on ED patients diagnosed with septic shock (n = 32) and...
Biomarkers Metabolome Female Aged Middle Aged Emergency Service, Hospital Humans Adult Machine Learning Early Diagnosis Shock, Septic Male Algorithms Mass Spectrometry Metabolomics
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Exploring treatment effects and fluid resuscitation strategies in septic shock: a deep learning-based causal inference approach.

Scientific reports May 25, 2025
Septic shock exhibits diverse etiologies and patient characteristics, necessitating tailored fluid management. We aimed to compare resuscitation strategies using normal saline, Ringer's lactate, and albumin, and to determine which patient factors are...
Female Aged Male Middle Aged Deep Learning Humans Acute Kidney Injury Albumins Resuscitation Ringer's Lactate Hospital Mortality Shock, Septic Treatment Outcome Fluid Therapy
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Optimal Vasopressin Initiation in Septic Shock: The OVISS Reinforcement Learning Study.

JAMA May 20, 2025
IMPORTANCE: Norepinephrine is the first-line vasopressor for patients with septic shock. When and whether a second agent, such as vasopressin, should be added is unknown.
Vasoconstrictor Agents Datasets as Topic Practice Guidelines as Topic Organ Dysfunction Scores Hospital Mortality Shock, Septic Observational Studies as Topic Norepinephrine Vasopressins Reinforcement Machine Learning Humans Critical Illness Electronic Health Records Aged Male Middle Aged Clinical Decision-Making Female
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Multicenter target trial emulation to evaluate corticosteroids for sepsis stratified by predicted organ dysfunction trajectory.

Nature communications May 13, 2025
Corticosteroids decrease the duration of organ dysfunction in sepsis and a range of overlapping and complementary infectious critical illnesses, including septic shock, pneumonia and the acute respiratory distress syndrome (ARDS). The risk and benefi...
Pneumonia Machine Learning Multiple Organ Failure Retrospective Studies Female Organ Dysfunction Scores Humans Sepsis Male Aged Adrenal Cortex Hormones Shock, Septic Middle Aged Respiratory Distress Syndrome
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Comparison of different AI systems for diagnosing sepsis, septic shock, and cardiogenic shock: a retrospective study.

Scientific reports May 6, 2025
Sepsis, septic shock, and cardiogenic shock are life-threatening conditions associated with high mortality rates, but differentiating them is complex because they share certain symptoms. Using the Medical Information Mart for Intensive Care (MIMIC)-I...
Middle Aged Sepsis Neural Networks, Computer Shock, Septic Shock, Cardiogenic Bayes Theorem Humans Artificial Intelligence Female Retrospective Studies Aged Adult Male
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Scale to predict risk for refractory septic shock based on a hybrid approach using machine learning and regression modeling.

Emergencias : revista de la Sociedad Espanola de Medicina de Emergencias Feb 1, 2025
OBJECTIVE: To develop a scale to predict refractory septic shock (SS) based on clinical variables recorded during initial evaluations of patients.
Norepinephrine Shock, Septic Male Regression Analysis Humans Emergency Service, Hospital Middle Aged Intensive Care Units Risk Assessment Registries ROC Curve Female Machine Learning Aged Retrospective Studies
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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...
Hospital Mortality Humans Sepsis Intensive Care Units, Pediatric Machine Learning Adolescent Shock, Septic Prognosis Retrospective Studies Child, Preschool Female Child Male Infant
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