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
Yinghui HuangGaoxing Luo

Abstract

To develop a mathematical model of predicting mortality based on the admission characteristics of 6220 burn cases. Data on all the burn patients presenting to Institute of Burn Research, Southwest Hospital, Third Military Medical University from January of 1999 to December of 2008 were extracted from the departmental registry. The distributions of burn cases were scattered by principal component analysis. Univariate associations with mortality were identified and independent associations were derived from multivariate logistic regression analysis. Using variables independently and significantly associated with mortality, a mathematical model to predict mortality was developed using the support vector machine (SVM) model. The predicting ability of this model was evaluated and verified. The overall mortality in this study was 1.8%. Univariate associations with mortality were identified and independent associations were derived from multivariate logistic regression analysis. Variables at admission independently associated with mortality were gender, age, total burn area, full thickness burn area, inhalation injury, shock, period before admission and others. The sensitivity and specificity of logistic model were 99.75% and 85.84% r...Continue Reading

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Citations

Jul 9, 2021·Plastic and Reconstructive Surgery. Global Open·Angelos MantelakisAnkur Khajuria
Aug 24, 2021·Burns and Trauma·Francisco Serra E MouraChidi Ekwobi
Aug 23, 2021·Burns : Journal of the International Society for Burn Injuries·Samantha HuangJustin Gillenwater

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