AIMC Topic: Sepsis

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Integrating bioinformatics and machine learning to discover sumoylation associated signatures in sepsis.

Scientific reports Apr 24, 2025
Small Ubiquitin-like MOdifier-mediated modification (SUMOylation) is associated with sepsis; however, its molecular mechanism remains unclear. Herein, hub genes and regulatory mechanisms in sepsis was investigated. The GSE65682 and GSE95233 datasets ...
Sumoylation Humans Gene Regulatory Networks Machine Learning Computational Biology Gene Expression Profiling Databases, Genetic Sepsis
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IDENTIFYING A SEPSIS SUBPHENOTYPE CHARACTERIZED BY DYSREGULATED LIPOPROTEIN METABOLISM USING A SIMPLIFIED CLINICAL DATA ALGORITHM.

Shock (Augusta, Ga.) Apr 23, 2025
Background: Cholesterol metabolism is dysregulated in sepsis contributing to patient heterogeneity. Subphenotypes displaying lower lipoprotein levels and higher mortality (previously subphenotyped hypolipoprotein phenotype [HYPO]) or higher lipoprote...
Humans Algorithms Phenotype Middle Aged Sepsis Lipoproteins Cholesterol, HDL Prospective Studies Female Aged Male
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Interpretable machine learning model for predicting delirium in patients with sepsis: a study based on the MIMIC data.

BMC infectious diseases Apr 23, 2025
OBJECTIVE: The aim of this study was to construct interpretable machine learning models to predict the risk of developing delirium in patients with sepsis and to explore the impact of delirium on the 28-day survival rate of patients.
Risk Factors Aged Aged, 80 and over Male Middle Aged Sepsis ROC Curve Delirium Organ Dysfunction Scores Humans Machine Learning Female
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Association between the (neutrophil + monocyte)/albumin ratio and all-cause mortality in sepsis patients: a retrospective cohort study and predictive model establishment according to machine learning.

BMC infectious diseases Apr 22, 2025
INTRODUCTION: Sepsis is a life-threatening condition characterized by widespread inflammatory response syndrome in the body resulting from infection. Previous studies have demonstrated that some inflammatory factors or nutritional elements contribute...
Predictive Learning Models Male Middle Aged Sepsis Cohort Studies Retrospective Studies Monocytes Humans Female Neutrophils Machine Learning Risk Factors Blood Cell Count Aged Serum Albumin, Human
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A machine learning model for predicting acute respiratory distress syndrome risk in patients with sepsis using circulating immune cell parameters: a retrospective study.

BMC infectious diseases Apr 21, 2025
BACKGROUND: Acute respiratory distress syndrome (ARDS) is a severe complication associated with a high mortality rate in patients with sepsis. Early identification of patients with sepsis at high risk of developing ARDS is crucial for timely interven...
Adult Male Middle Aged Risk Assessment Sepsis ROC Curve Respiratory Distress Syndrome Retrospective Studies Female Risk Factors Aged Humans Machine Learning
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Predicting mortality and risk factors of sepsis related ARDS using machine learning models.

Scientific reports Apr 18, 2025
Sepsis related acute respiratory distress syndrome (ARDS) is a common and serious disease in clinic. Accurate prediction of in-hospital mortality of patients is crucial to optimize treatment and improve prognosis under the new global definition of AR...
Risk Factors Aged Male Middle Aged Machine Learning Prognosis Female Sepsis Hospital Mortality Respiratory Distress Syndrome Bayes Theorem Humans
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Early prediction of sepsis associated encephalopathy in elderly ICU patients using machine learning models: a retrospective study based on the MIMIC-IV database.

Frontiers in cellular and infection microbiology Apr 17, 2025
BACKGROUND: Sepsis associated encephalopathy (SAE) is prevalent among elderly patients in the ICU and significantly affects patient prognosis. Due to the symptom similarity with other neurological disorders and the absence of specific biomarkers, ear...
Female Databases, Factual Humans Sepsis Aged Machine Learning Prognosis Early Diagnosis Aged, 80 and over Algorithms Retrospective Studies Male Sepsis-Associated Encephalopathy Intensive Care Units
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CLIC1 and IFITM2 expression in brain tissue correlates with cognitive impairment via immune dysregulation in sepsis and Alzheimer's disease.

International immunopharmacology Apr 10, 2025
BACKGROUND: Sepsis, a life-threatening condition driven by dysregulated host responses to infection, is associated with long-term cognitive impairments resembling Alzheimer's disease (AD). However, the molecular mechanisms linking sepsis-induced cogn...
Humans Brain Animals Male Chloride Channels Sepsis Disease Models, Animal Cognitive Dysfunction Mice, Inbred C57BL Mice Alzheimer Disease Membrane Proteins
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Clinical subtypes identification and feature recognition of sepsis leukocyte trajectories based on machine learning.

Scientific reports Apr 10, 2025
Sepsis is a highly variable condition, and tracking leukocyte patterns may offer insights for tailored treatment and prognosis. We used the MIMIC-IV database to analyze patients diagnosed with Sepsis-3 within 24 h of ICU admission. Latent class mixed...
Humans Machine Learning Prognosis Intensive Care Units Middle Aged Female Sepsis Aged Leukocytes Male Leukocyte Count
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Machine learning approach for the prediction of 30-day mortality in patients with sepsis-associated delirium.

PloS one Apr 9, 2025
This study aimed to develop models for predicting the 30-day mortality of sepsis-associated delirium (SAD) by multiple machine learning (ML) algorithms. On the whole, a cohort of 3,197 SAD patients were collected from the Medical Information Mart for...
Female Risk Factors Aged Aged, 80 and over Male Humans Machine Learning Middle Aged Algorithms Sepsis Prognosis Delirium
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