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Smoke Inhalation Injury

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[Effects of non-muscle myosin ⅡA silenced bone marrow mesenchymal stem cells on lung damage of rats at early stage of smoke inhalation injury].

Zhonghua shao shang za zhi = Zhonghua shaoshang zazhi = Chinese journal of burns 29275618
To investigate the effects of non-muscle myosin ⅡA (NMⅡA) silenced bone marrow mesenchymal stem cells (BMSCs) on the lung damage of rats at early stage of smoke inhalation injury. Forty Sprague-Dawley rats were divided into control, simple injury, ...
Animals Bone Marrow Cells Enzyme-Linked Immunosorbent Assay Interleukin-10 Lung Injury Male Nonmuscle Myosin Type IIA Rats Rats, Sprague-Dawley Smoke Inhalation Injury Tumor Necrosis Factor-alpha
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R-100 improves pulmonary function and systemic fluid balance in sheep with combined smoke-inhalation injury and Pseudomonas aeruginosa sepsis.

Journal of translational medicine 29282084
BACKGROUND: Septic shock is a major cause of death in intensive care units around the world . The aim of the study was to investigate whether the novel drug R-100 (a superoxide degradation catalyst and nitric oxide donor) improves pulmonary function ...
Animals Blood Proteins Body Fluids Female Hemodynamics Lung Nitric Oxide Donors Pseudomonas aeruginosa Pulmonary Gas Exchange Respiratory Function Tests Sepsis Sheep Smoke Inhalation Injury Superoxides
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Mortality risk prediction in burn injury: Comparison of logistic regression with machine learning approaches.

Burns : journal of the International Society for Burn Injuries 25931158
INTRODUCTION: Predicting mortality from burn injury has traditionally employed logistic regression models. Alternative machine learning methods have been introduced in some areas of clinical prediction as the necessary software and computational faci...
Adolescent Adult Age Factors Bayes Theorem Body Surface Area Burns Child Child, Preschool Decision Support Techniques England Female Humans Infant Logistic Models Machine Learning Male Models, Statistical Neural Networks, Computer Registries Risk Assessment ROC Curve Smoke Inhalation Injury Software Support Vector Machine Wales Young Adult
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A novel mathematical model to predict prognosis of burnt patients based on logistic regression and support vector machine.

Burns : journal of the International Society for Burn Injuries 26774603
OBJECTIVE: To develop a mathematical model of predicting mortality based on the admission characteristics of 6220 burn cases.
Adolescent Adult Aged Body Surface Area Burns Child Child, Preschool Humans Infant Infant, Newborn Logistic Models Middle Aged Models, Theoretical Multivariate Analysis Principal Component Analysis Prognosis ROC Curve Shock Smoke Inhalation Injury Support Vector Machine Trauma Severity Indices Young Adult
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