AIMC Topic: Sepsis

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Revolutionizing sepsis diagnosis using machine learning and deep learning models: a systematic literature review.

BMC infectious diseases
Sepsis is a life-threatening condition resulting from a dysregulated immune response to infection, often leading to organ failure and death. Early detection is vital, as delays significantly worsen outcomes. In recent years, the integration of artifi...

Dynamic HGI trajectories and their impact on survival in patients with sepsis: a machine learning prognostic model.

Inflammation research : official journal of the European Histamine Research Society ... [et al.]
BACKGROUND: Previous studies have indicated a correlation between the glycosylated hemoglobin index (HGI) and the prognosis of patients with sepsis. However, the impact of its dynamic fluctuations on patient outcomes remains insufficiently explored. ...

Association between atherogenic index of plasma and sepsis in critically ill patients with ischemic stroke: a retrospective cohort study using propensity score and machine learning approaches.

Lipids in health and disease
BACKGROUND: Sepsis is a severe and frequent complication among ischemic stroke patients during hospitalization. The atherogenic index of plasma (AIP), as metabolism-related markers, are closely linked to inflammation. However, their relationship with...

Hospital Outcome of Host Heterogeneity, Organ dysfunction and Trajectory in sepsis (HOHHOT): A cohort study in the critical care unit.

BMJ open
INTRODUCTION: Prognosis estimation is the basis for establishing the personal interventions in sepsis patients. Serum biomarkers are potential tools for predicting the outcomes of sepsis patients admitted to the intensive care unit (ICU). Here, we pl...

Prediction of Moderate-to-Severe Sepsis-Associated Acute Kidney Injury Using a Dual-Timepoint Machine Learning Model: Development, Multiregional Validation, and Clinical Deployment Study.

Journal of medical Internet research
BACKGROUND: Sepsis-associated acute kidney injury (SA-AKI) is a frequent and life-threatening complication in patients in the intensive care unit (ICU), significantly increasing both mortality rates and the risk of chronic kidney dysfunction. However...

Integrated multi omics and machine learning reveal mitochondrial immunometabolic networks in sepsis associated encephalopathy.

Scientific reports
Sepsis-associated encephalopathy (SAE) is a major complication in intensive care units, characterized by diffuse brain dysfunction due to systemic inflammation. Despite advances in critical care medicine, SAE remains a key factor in poor patient outc...

InfEHR: Clinical phenotype resolution through deep geometric learning on electronic health records.

Nature communications
Electronic health records contain multimodal data that can inform clinical decisions but are often unsuited for advanced machine learning analyses due to lack of labeled data. Here, we present InfEHR, a framework to automatically compute clinical lik...

Development and validation of an explainable machine learning model for predicting sepsis risk following flexible ureteroscopic lithotripsy.

Urolithiasis
Sepsis is a severe complication of flexible ureteroscopic lithotripsy (fURL), a widely used treatment for kidney stones. This study aimed to develop and validate a predictive model based on machine learning (ML) for assessing the risk of sepsis follo...

Machine learning-based transcriptomic analysis identifies candidate genes in sepsis-induced coagulopathy and explores the immunomodulatory potential of baicalein.

Human genomics
BACKGROUND: Sepsis is a major contributor to high morbidity and mortality, often leading to coagulation disorders (CD) in affected individuals. Baicalein, a natural compound with well-established anti-inflammatory properties, shows promise as a poten...

Identification and analysis of the endoplasmic reticulum stress hub genes in sepsis-associated ARDS.

Scientific reports
Acute respiratory distress syndrome (ARDS) is one of the most common and serious complications in the development of sepsis. Endoplasmic reticulum stress (ERS) plays an important role in the pathophysiologic process of sepsis-associated ARDS. The aim...