Leveraging explainable artificial intelligence for early prediction of bloodstream infections using historical electronic health records.

Bloodstream infections (BSIs) are a severe public health threat due to their rapid progression into critical conditions like sepsis. This study presents a novel eXplainable Artificial Intelligence (XAI) framework to predict BSIs using historical electronic health records (EHRs). Leveraging a dataset from St.

Prolonged outpatient parenteral antimicrobial treatment: frequency and evolution over a six-year period in a Swiss University Hospital.

Background: Emerging research indicates the potential for early transition from intravenous to oral antimicrobial therapy in certain infections. This trend may have implications for outpatient parenteral antibiotic therapy (OPAT) programs, as the demand for prolonged intravenous treatment could decrease. The objective of this study was to evaluate the frequency and evolution of OPAT courses of ≥ 14 days over the years and determine the medical justification for those prolonged treatments.

In-hospital mortality, readmission, and prolonged length of stay risk prediction leveraging historical electronic patient records.

Objective: This study aimed to investigate the predictive capabilities of historical patient records to predict patient adverse outcomes such as mortality, readmission, and prolonged length of stay (PLOS).

Methods: Leveraging a de-identified dataset from a tertiary care university hospital, we developed an eXplainable Artificial Intelligence (XAI) framework combining tree-based and traditional machine learning (ML) models with interpretations and statistical analysis of predictors of mortality, readmission, and PLOS.

Results: Our framework demonstrated exceptional predictive performance with a notable area under the receiver operating characteristic (AUROC) of 0.

Neutrophil Extracellular Traps in ST-Segment Elevation Myocardial Infarction: Reduced by Tocilizumab and Associated With Infarct Size.

Background: Interleukin-6-receptor inhibition with tocilizumab improves myocardial salvage in patients with ST-segment elevation myocardial infarction (STEMI). Reduced levels of neutrophil extracellular traps (NETs), which consist of nuclear material studded with proteins released upon neutrophil activation, might contribute to this effect.

Objectives: The purpose of this study was to evaluate the effect of tocilizumab on NETs and investigate the association between NETs and myocardial injury in patients with STEMI.