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Bacteremia

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Rapid Rule Out of Culture-Negative Bloodstream Infections by Use of a Novel Approach to Universal Detection of Bacteria and Fungi.

The journal of applied laboratory medicine 31639722
BACKGROUND: Currently it can take up to 5 days to rule out bloodstream infection. With the low yield of blood cultures (approximately 10%), a significant number of patients are potentially exposed to inappropriate therapy that can lead to adverse eve...
Anti-Infective Agents Antimicrobial Stewardship Bacteremia Bacteria Bacterial Proteins Blood Culture DNA-Directed DNA Polymerase Fungal Proteins Fungemia Fungi Humans Limit of Detection Predictive Value of Tests Real-Time Polymerase Chain Reaction Time Factors
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Distribution of main Gram-positive pathogens causing bloodstream infections in United States and European hospitals during the SENTRY Antimicrobial Surveillance Program (2010-2016): concomitant analysis of oritavancin in vitro activity.

Journal of chemotherapy (Florence, Italy) 30843778
This study updates the distribution and trends of Gram-positive organisms causing bloodstream infections (BSIs) in the United States (US) and Europe during 2010-2016. In vitro activities of oritavancin and comparators were also evaluated. Staphylococ...
Anti-Bacterial Agents Bacteremia Cross Infection Europe Gram-Positive Bacteria Gram-Positive Bacterial Infections Hospitals Humans Lipoglycopeptides United States
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Community-acquired bacteremia in adult patients. analysis of 645 episodes.

Revista de la Facultad de Ciencias Medicas (Cordoba, Argentina) 28152365
Bacteremia is an important cause of morbimortality. This study describes the episodes of communityacquired bacteremia in adult patients registered at our hospital. Between January 2005 and December 2013, 645 episodes were studied. A total of 51% of p...
Adolescent Adult Aged Aged, 80 and over Argentina Bacteremia Community-Acquired Infections Female Humans Male Middle Aged Prospective Studies Young Adult
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Predicting central line-associated bloodstream infections and mortality using supervised machine learning.

Journal of critical care 29486341
PURPOSE: The purpose of this study was to compare machine learning techniques for predicting central line-associated bloodstream infection (CLABSI).
Bacteremia Catheter-Related Infections Central Venous Catheters Databases, Factual Female Florida Hospital Mortality Humans Intensive Care Units Logistic Models Male Middle Aged Predictive Value of Tests Risk Assessment Simplified Acute Physiology Score Supervised Machine Learning
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Assessing patient risk of central line-associated bacteremia via machine learning.

American journal of infection control 29661634
BACKGROUND: Central line-associated bloodstream infections (CLABSIs) contribute to increased morbidity, length of hospital stay, and cost. Despite progress in understanding the risk factors, there remains a need to accurately predict the risk of CLAB...
Academic Medical Centers Adolescent Adult Aged Aged, 80 and over Bacteremia Case-Control Studies Catheter-Related Infections Catheterization, Central Venous Child Child, Preschool Epidemiologic Methods Female Humans Infant Infant, Newborn Machine Learning Male Middle Aged Retrospective Studies Risk Assessment Young Adult
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Supervised machine learning in critical care: The path forward.

Journal of critical care 29804636
Bacteremia Critical Care Humans Supervised Machine Learning
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