Prevalence, underlying causes, and preventability of sepsis-associated mortality in US acute care hospitals [PDF]
, 2019 Importance: Sepsis is present in many hospitalizations that culminate in death. The contribution of sepsis to these deaths, and the extent to which they are preventable, is unknown.
Anderson, Deverick J +10 more
core +1 more source
Fecal microbiota transplant rescues mice from human pathogen mediated sepsis by restoring systemic immunity. [PDF]
, 2020 Death due to sepsis remains a persistent threat to critically ill patients confined to the intensive care unit and is characterized by colonization with multi-drug-resistant healthcare-associated pathogens.
Alverdy, John C +24 more
core
Proenkephalin, neutrophil gelatinase-associated lipocalin, and estimated glomerular filtration rates in patients with sepsis [PDF]
, 2017 Background: Proenkephalin (PENK) has been suggested as a novel biomarker for kidney function. We investigated the diagnostic and prognostic utility of plasma PENK in comparison with neutrophil gelatinase-associated lipocalin (NGAL) and estimated ...
Andreas Bergmann +10 more
core +1 more source
Identifying and Analyzing Sepsis States: A Retrospective Study on Patients with Sepsis in ICUs [PDF]
arXiv, 2020 Sepsis accounts for more than 50% of hospital deaths, and the associated cost ranks the highest among hospital admissions in the US. Improved understanding of disease states, severity, and clinical markers has the potential to significantly improve patient outcomes and reduce cost.
arxiv
An Improved Mathematical Model of Sepsis: Modeling, Bifurcation Analysis, and Optimal Control Study for Complex Nonlinear Infectious Disease System [PDF]
arXiv, 2022 Sepsis is a life-threatening medical emergency, which is a major cause of death worldwide and the second highest cause of mortality in the United States. Researching the optimal control treatment or intervention strategy on the comprehensive sepsis system is key in reducing mortality.
arxiv
Leveraging Implicit Expert Knowledge for Non-Circular Machine Learning in Sepsis Prediction [PDF]
Artificial Intelligence in Medicine, Volume 100, September 2019,
Pages 101725, 2019 Sepsis is the leading cause of death in non-coronary intensive care units. Moreover, a delay of antibiotic treatment of patients with severe sepsis by only few hours is associated with increased mortality. This insight makes accurate models for early prediction of sepsis a key task in machine learning for healthcare.
arxiv +1 more source
The atypical chemokine receptor ACKR2 is protective against sepsis [PDF]
, 2018 Sepsis is a systemic inflammatory response as a result of uncontrolled infections. Neutrophils are the first cells to reach the primary sites of infection and chemokines play a key role in recruiting neutrophils.
Alves-Filho, José Carlos +15 more
core +1 more source
Canadian Journal of Infectious Diseases and Medical Microbiology, 2011 Severe sepsis and septic shock represent the most extreme ends of the infectious diseases spectrum. Severe sepsis is generally defined by evidence of a systemic inflammatory response to an infection, with associated organ dysfunction (1). Patients who fulfill criteria for severe sepsis, who also have hypotension refractory to adequate volume ...
Laupland, Kevin B., Fisman, David N.
openaire +5 more sources
All that seems sepsis is not sepsis
Indian Journal of Critical Care Medicine, 2013 Catastrophic antiphospholipid antibody syndrome (CAPS) resembles severe sepsis in its acute presentation, with features of systemic inflammatory response syndrome (SIRS) leading to multiple organ dysfunction. Infections are the best known triggers of CAPS. This emphasizes the need for early diagnosis and aggressive treatment as the mortality is as high
Subramanian Shankar +3 more
openaire +3 more sources
Sepsis Prediction with Temporal Convolutional Networks [PDF]
arXiv, 2022 We design and implement a temporal convolutional network model to predict sepsis onset. Our model is trained on data extracted from MIMIC III database, based on a retrospective analysis of patients admitted to intensive care unit who did not fall under the definition of sepsis at the time of admission.
arxiv