Sepsis

Ventral hernia repair in emergency settings. A machine learning model to predict post-operative complications.

BACKGROUND: Emergency ventral hernia repair remains a challenging procedure due to patient instability, contaminated surgical fields, and heterogeneity in hernia types and operative techniques. Predicting postoperative complications in this setting is difficult using traditional statistical methods. Machine learning (ML) may offer improved predictive accuracy by recognizing nonlinear patterns amon...

Arctic deep-sea hydrothermal microbiomes as a natural niche for novel antimicrobial peptides.

BACKGROUND: The escalating threat of antimicrobial resistance (AMR) has created an urgent need for new antimicrobial agents. Antimicrobial peptides (AMPs) are promising alternatives to conventional antibiotics due to their broad-spectrum activity and reduced risk of resistance development. While most AMP discovery efforts have focused on terrestrial microbes, extreme environments remain largely un...

Agentic GPT-5.0 system outperforms standard large language models and human experts in critical care clinical decision-making: a simulation study.

BACKGROUND: Agentic artificial intelligence (AI) systems employing multi-model architectures with iterative reasoning may surpass standard single-mode...

Metabolomics and Artificial Intelligence (AI) assisted metabolomics in the diagnosis of non-tuberculous mycobacterial infections: progress and challenges.

BACKGROUND: Non tuberculous mycobacterial (NTM) infections are caused in individuals who are immunocompromised or with certain lung conditions. The NT...

Identification of sepsis subphenotypes: current methods and clinical implications in critical care practice. A structured narrative review.

Sepsis demonstrates high variability in clinical manifestations, and patients with similar manifestations at the moment of diagnosis usually develop i...

Machine Learning-Based Prediction Model for Infectious Complications in Trauma and Its Association With In-Hospital Mortality.

BACKGROUND: Infectious complications, such as sepsis or catheter-related infections, are common and serious sequelae after trauma. Despite their clini...

Global Perspectives on CNS Drug Innovation: Achievements, Barriers, and Priorities for the Next Decade.

BACKGROUND: Over the past decade, neuropsychopharmacology has shifted from stagnation to momentum, with first-in-class mechanisms and biomarker-enable...

Early prediction of in-hospital mortality in ICU patients with heart failure using an interpretable machine learning model: a retrospective study based on MIMIC-IV.

BACKGROUND: Heart failure (HF) remains a major cause of morbidity and mortality worldwide, and acute decompensation frequently necessitates intensive ...

End-of-surgery prediction of postoperative infectious complications from intraoperative vital-sign dynamics.

Infections after surgery remain a leading cause of morbidity and mortality, yet reliable risk stratification at the end of surgery is limited. Intraop...

A Lightweight LSTM-Transformer Fusion Architecture for Real-Time Sepsis Mortality Prediction.

BackgroundAccurate prediction of short-term mortality in sepsis patients is critical for timely clinical decision-making. However, existing deep learn...

Evaluating the Potential Impact of AI on Urinary Tract Infection Diagnosis in the Emergency Department Across Demographic Groups: Retrospective Cohort Study.

BACKGROUND: Urinary tract infection (UTI) is a common emergency department (ED) presentation but can be challenging to diagnose; both overdiagnosis an...

Early sepsis prediction using a hybrid LSTM-GAT model: a study on the PhysioNet 2019 dataset.

OBJECTIVE: Sepsis is a potentially fatal systemic response to infection, in which early clinical intervention is critical to reduce mortality. This st...

Positron emission tomography imaging of inflammation and infection in children: an update.

Positron emission tomography (PET) has been used in pediatric oncology since the modality gained traction 20 years ago but has been used more sparingl...

Beyond NIHSS and neuroimaging: an interpretable gradient boosting model for predicting in-hospital mortality in ICU patients with acute ischemic stroke.

This study aimed to develop an interpretable machine learning model for predicting in-hospital mortality among acute ischemic stroke (AIS) patients ad...

Research progress on biomarkers for acute kidney injury in children.

Pediatric acute kidney injury (AKI) often presents insidiously and progresses rapidly. Traditional diagnostic criteria based on serum creatinine and u...

Artificial intelligence for analysing antibiotic use: an exploratory study in a tertiary care paediatric hospital in Italy.

BACKGROUND: Monitoring antibiotic consumption and resistance is central to antimicrobial stewardship (AMS). However, this is particularly challenging ...

Global Trends in Postoperative Sepsis After Pancreatoduodenectomy: A Bibliometric Analysis.

INTRODUCTION: Postoperative sepsis after pancreatoduodenectomy (PSPD) remains a major determinant of morbidity and mortality. Although extensive clini...

Controlled human malaria infection in adults identify combinations of merozoite antigens associated with clinical immunity.

Two vaccines are currently licensed against Plasmodium falciparum malaria but offer only partial protection that wanes, necessitating repeated dosing ...

AI-enabled digital wound monitoring after cardiac surgery: a randomised controlled feasibility, safety, and acceptability trial.

BACKGROUND: Surgical site infection after cardiac surgery is a common cause of morbidity and unplanned healthcare use, with most infections developing...

Cost-effectiveness of latent tuberculosis infection screening using interferon-gamma release assays among migrants to Japan: a Markov modelling study incorporating social vulnerability and access barriers.

OBJECTIVE: This study aims to evaluate the cost-effectiveness of latent tuberculosis infection (LTBI) screening strategies using interferon-gamma rele...