Predictive value of red blood cell distribution width in septic shock patients with thrombocytopenia: A retrospective study using machine learning

Predictive value of red blood cell distribution width in septic shock patients with thrombocytopenia: A retrospective study using machine learning

Background: Sepsis-associated thrombocytopenia (SAT) is common in critical patients and results in the elevation of mortality. Red cell distribution width (RDW) can reflect body response to inflammation and oxidative stress. We try to investigate the relationship between the RDW and the prognosis of...

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Bibliographic Details
Main Authors: Fang, M. (Author), Jin, H. (Author), Liao, T. (Author), Ling, J. (Author), Lu, F. (Author), Wang, Z. (Author), Wu, Y. (Author)
Format: Article
Language:English
Published: John Wiley and Sons Inc 2021
Subjects:
adult
aged
Aged
Article
blood
comorbidity
Comorbidity
controlled study
Erythrocyte Indices
female
Female
hospital mortality
Hospital Mortality
human
Humans
inflammation
Kaplan Meier method
Kaplan-Meier Estimate
logistic regression analysis
machine learning
Machine Learning
major clinical study
male
Male
mean corpuscular volume
middle aged
Middle Aged
mortality
mortality rate
prognosis
Prognosis
propensity score
Propensity Score
receiver operating characteristic
red blood cell distribution width
red cell distribution width
Retrospective Studies
retrospective study
septic shock
Shock, Septic
survivor
thrombocytopenia
Thrombocytopenia
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