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Volume 5, Issue 2 (11-2019)
IJCA 2019, 5(2): 0-0 |
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Haghighi Aski B, Manafi Anari A, Sarejloo N, Abolhassan Choobdar F, Saemi R, Hoseini R et al . A new scoring system for stratifying risk for cerebral edema in children suffering diabetic ketoacidosis. IJCA 2019; 5 (2)
URL: http://ijca.iums.ac.ir/article-1-126-en.html
URL: http://ijca.iums.ac.ir/article-1-126-en.html
Behzad Haghighi Aski 
, Ali Manafi Anari , Nazanin Sarejloo , Farhad Abolhassan Choobdar , Ramin Saemi , Rozita Hoseini , Davoud Amirkashani
, Ali Manafi Anari , Nazanin Sarejloo , Farhad Abolhassan Choobdar , Ramin Saemi , Rozita Hoseini , Davoud Amirkashani
Iran university of mdeical sciences
Abstract: (2647 Views)
Background: Predicting adverse neurovascular complications due to diabetic ketoacidosis (DKA) particularly in children leads to more appropriately management of disease as well as achievement of acceptable patients' survival. Cerebral edema is a life-threatening adverse event following DKA responsible for high mortality rate. Recently, authors have focused introducing new risk assessment tools for predicting occurrence of brain edema to early prevention of nervous defects and losing consciousness following DKA. The present study aimed to present a new scoring system for predicting brain edema as a serious consequence of DKA among children.
Methods: A retrospective chart review was conducted on 112 children with the definitive diagnosis of DKA who were admitted to Ali-e-Asghar Hospital, Tehran, between 2014 and 2017. The multivariable logistic regression modeling and analysis of the ROC curve were used to determine and stratify parameters predicting high risk groups for cerebral edema.
Results: In multivariable logistic regression model, using infant formula (OR = 4.153, p = 0.020), tachypnea on admission (OR = 3.342, p = 0.027), and raised serum creatinine (OR = 1.658, p = 0.026) could effectively predict the likelihood of brain edema following DKA in children. The children with three parameters were scored as 3, two of three parameters scored as 2, one of three parameters scored as 1, and none parameters scored as 0 considering as very high risk (with 8-fold risk for brain edema), high risk (with 5 to 6-fold risk for brain edema), moderate risk (with 2 to 4- fold risk for brain edema) and low risk for brain edema following DKA.
Conclusion: We presents a new scoring system for early identifying children prone to cerebral edema following DKA. This scoring system considers triad of history of using formula, tachypnea on admission and raised serum creatinine and thus can stratify DKA patients to low, moderate, high and very high risk for cerebral edema.
Methods: A retrospective chart review was conducted on 112 children with the definitive diagnosis of DKA who were admitted to Ali-e-Asghar Hospital, Tehran, between 2014 and 2017. The multivariable logistic regression modeling and analysis of the ROC curve were used to determine and stratify parameters predicting high risk groups for cerebral edema.
Results: In multivariable logistic regression model, using infant formula (OR = 4.153, p = 0.020), tachypnea on admission (OR = 3.342, p = 0.027), and raised serum creatinine (OR = 1.658, p = 0.026) could effectively predict the likelihood of brain edema following DKA in children. The children with three parameters were scored as 3, two of three parameters scored as 2, one of three parameters scored as 1, and none parameters scored as 0 considering as very high risk (with 8-fold risk for brain edema), high risk (with 5 to 6-fold risk for brain edema), moderate risk (with 2 to 4- fold risk for brain edema) and low risk for brain edema following DKA.
Conclusion: We presents a new scoring system for early identifying children prone to cerebral edema following DKA. This scoring system considers triad of history of using formula, tachypnea on admission and raised serum creatinine and thus can stratify DKA patients to low, moderate, high and very high risk for cerebral edema.
Keywords: cerebral edema, diabetes
Type of Study: Systematic Review & Metaanalysis |
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