Sepsis

Toward Standardized ICU Trauma Resuscitation via Markov Decision Processes.

OBJECTIVE: Guideline-based recommendations for posthemostasis resuscitation in trauma patients remain limited. This study aimed to define an interpretable Markov Decision Process (MDP) to model intensive care unit (ICU) trauma resuscitation and evaluate its potential to support clinical decision-making using a previously established framework from sepsis care. DESIGN: Retrospective observational s...

A Retrospective Cohort Study on 28-Day Mortality in Immunosuppressed Sepsis: An Interpretability-Based Predictive Model Using MIMIC-IV V2.2.

BACKGROUND: Sepsis in immunosuppressed patients is associated with significantly higher mortality rates, yet predictive models tailored to this high-risk population remain limited. This study aims to develop an interpretable machine learning model to predict 28-day mortality in immunosuppressed sepsis patients, with a focus on model transparency and clinical applicability. METHODS: A retrospective...

Interrelations between dopaminergic-, gabaergic- and glutamatergic neurotransmitters in antipsychotic-naïve psychosis patients and the association to initial treatment response.

Preclinical evidence points to disturbances in neural networks in psychosis involving interrelations between dopaminergic-, GABAergic- and glutamaterg...

Bu Zhong Yi Qi Tang targets key monocyte-associated genes to enhance sepsis therapy.

ETHNOPHARMACOLOGICAL RELEVANCE: Sepsis is a life-threatening condition resulting from an uncontrolled immune response to infection, leading to organ d...

Salt-inducible kinase 1 is a key gene in suppressing EVD68-induced asthma by modulating antiviral immunity.

Asthma is a complex inflammatory disease of the airways, affecting over 300 million individuals globally. Infection with enterovirus D68 (EV-D68) has ...

Pharmacological Haemodynamic Management in the Intensive Care Unit: The Evolution of the Nurse's Role Over 50 Years.

AIM: To examine the evolution of intensive care nurses' roles in pharmacological haemodynamic management from 1975 to 2025 and to explore projected re...

Unsupervised machine learning to explore inflammation following cardiopulmonary bypass.

IntroductionCardiac surgery with cardiopulmonary bypass (CPB) often induces systemic inflammatory reaction syndrome (SIRS), affecting postoperative ou...

Explainable machine learning for discontinuation of therapeutic antibiotics in intensive care patients.

INTRODUCTION: The threshold for initiating lifesaving antibiotics for intensive care patients is low while determining when to stop remains challengin...

Convergence: Multi-omics and AI are reshaping the landscape biomedical research.

This special volume of Biochimica et Biophysica Acta - Molecular Basis of Disease showcases a transformative era in biomedical research, driven by the...

Computational glycosyltransferases masked deoxynivalenol toxicity and halted FHB spread in wheat grains.

INTRODUCTION: Contamination of cereal grains by deoxynivalenol (DON) poses a significant threat to food safety. This toxic secondary metabolite, produ...

Sepsis as a complex syndrome: Are combined biomarkers the future of diagnosis and prognosis? Clinical perspective.

Sepsis remains a major cause of mortality worldwide, driven by a dysregulated host response to infection that leads to life-threatening organ dysfunct...

Use of Machine Learning to Derive Discrete Clinical Phenotypes and Assess Treatment-Effect Heterogeneity in the Steroids in Cardiac Surgery Trial Dataset.

BACKGROUND: Robust clinical trial data provide a key component for the development of evidence-informed medicine. However, clinical trial data may dem...

How do experts classify sepsis cases for sepsis surveillance? Lessons learned from a Behavioural Artificial Intelligence Technology (BAIT) approach.

OBJECTIVES: To identify relevant objective variables for retrospective identification of 'suspected infection' and sepsis, using behavioural artificia...

Leveraging machine learning for predicting Opisthorchis viverrini infection in cats: A tool for veterinary epidemiology.

Opisthorchis viverrini (Ov) infection is a major public health concern in the Greater Mekong Subregion, with cats as key reservoir hosts. Although mac...

An update on experimental to large-scale production of bacteriophages against superbugs: a review.

The escalating problem of antibiotic resistance has sparked renewed interest in bacteriophages (phages) as potential substitutes for conventional anti...

Biomarkers associated with Hashimoto's thyroiditis induced by viral infection: An integrative bioinformatics and machine learning.

OBJECTIVE: Hashimoto's thyroiditis (HT) is a common disease characterized by autoimmune injury of the thyroid. Its pathogenesis entails complex intera...

Predicting delirium in critically Ill COVID-19 patients using EEG-derived data: a machine learning approach.

Delirium is a severe and common complication among critically ill patients, particularly those with SARS-CoV-2 infection, contributing to increased mo...

Tissue perfusion pressure: A novel hemodynamic measure to assess risk of acute kidney injury after cardiac surgery.

BACKGROUND: Optimal hemodynamic targets for preventing acute kidney injury (AKI) have remained elusive. We hypothesized that lower tissue perfusion pr...

A Machine Learning Approach to Microcalorimetric Pattern Classification of Pathogens in Synovial Fluid.

Isothermal microcalorimetry (IMC) is a promising tool for diagnosing periprosthetic joint infection (PJI), based on real-time measurement of growth-re...

Computational exploration of global venoms for antimicrobial discovery with Venomics artificial intelligence.

The rise of antibiotic-resistant pathogens, particularly gram-negative bacteria, highlights the urgent need for novel therapeutics. Drug-resistant inf...