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Clostridioides difficile

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Evaluation of growth and sporulation of a non-toxigenic strain of Clostridioides difficile (Z31) and its shelf viability.

Brazilian journal of microbiology : [publication of the Brazilian Society for Microbiology]
The oral administration of non-toxigenic strains of Clostridioides difficile (NTCD) is currently showing promising results for the prevention of Clostridioides difficile infection (CDI) in humans and animals, and is being considered as a possible com...

A Deep Learning Approach to Antibiotic Discovery.

Cell
Due to the rapid emergence of antibiotic-resistant bacteria, there is a growing need to discover new antibiotics. To address this challenge, we trained a deep neural network capable of predicting molecules with antibacterial activity. We performed pr...

Modest Clostridiodes difficile infection prediction using machine learning models in a tertiary care hospital.

Diagnostic microbiology and infectious disease
Previous studies have shown promising results of machine learning (ML) models for predicting health outcomes. We develop and test ML models for predicting Clostridioides difficile infection (CDI) in hospitalized patients. This is a retrospective coho...

Pre-Trained Deep Convolutional Neural Network for Clostridioides Difficile Bacteria Cytotoxicity Classification Based on Fluorescence Images.

Sensors (Basel, Switzerland)
infection (CDI) is an enteric bacterial disease that is increasing in incidence worldwide. Symptoms of CDI range from mild diarrhea to severe life-threatening inflammation of the colon. While antibiotics are standard-of-care treatments for CDI, they...

Anastomotic Leak is Increased With Infection After Colectomy: Machine Learning-Augmented Propensity Score Modified Analysis of 46 735 Patients.

The American surgeon
BACKGROUND: infection (CDI) is now the most common cause of healthcare-associated infections, with increasing prevalence, severity, and mortality of nosocomial and community-acquired CDI which makes up approximately one third of all CDI. There are a...

Robotic pyelolithotomy in a solitary pelvic kidney complicated with fulminant Clostridium difficile: a case report.

Journal of medical case reports
BACKGROUND: Robotic-assisted surgeries have gradually become the standard of care for many procedures, especially in the field of urology. Despite the widespread use of robotic assistance in surgeries, data on its postoperative complications are extr...

Machine Learning-Based Prediction Models for Clostridioides difficile Infection: A Systematic Review.

Clinical and translational gastroenterology
INTRODUCTION: Despite research efforts, predicting Clostridioides difficile incidence and its outcomes remains challenging. The aim of this systematic review was to evaluate the performance of machine learning (ML) models in predicting C. difficile i...

Predicting Clostridioides difficile infection outcomes with explainable machine learning.

EBioMedicine
BACKGROUND: Clostridioides difficile infection results in life-threatening short-term outcomes and the potential for subsequent recurrent infection. Predicting these outcomes at diagnosis, when important clinical decisions need to be made, has proven...

Analysis of high-molecular-weight proteins using MALDI-TOF MS and machine learning for the differentiation of clinically relevant Clostridioides difficile ribotypes.

European journal of clinical microbiology & infectious diseases : official publication of the European Society of Clinical Microbiology
PURPOSE: Clostridioides difficile is the main cause of antibiotic related diarrhea and some ribotypes (RT), such as RT027, RT181 or RT078, are considered high risk clones. A fast and reliable approach for C. difficile ribotyping is needed for a corre...