Serum anion gap at admission as a predictor of mortality in the pediatric intensive care unit

Abstract An accurate method to predict the mortality in the intensive care unit (ICU) patients has been required, especially in children. The aim of this study is to evaluate the value of serum anion gap (AG) for predicting mortality in pediatric ICU (PICU). We reviewed a data of 461 pediatric patie...

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Autores principales:	Min Jung Kim, Yoon Hee Kim, In Suk Sol, Soo Yeon Kim, Jong Deok Kim, Ha Yan Kim, Kyung Won Kim, Myung Hyun Sohn, Kyu-Earn Kim
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2017
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/95c46f186ce342da98ff5c4f932ff30e
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spelling	oai:doaj.org-article:95c46f186ce342da98ff5c4f932ff30e2021-12-02T15:05:06ZSerum anion gap at admission as a predictor of mortality in the pediatric intensive care unit10.1038/s41598-017-01681-92045-2322https://doaj.org/article/95c46f186ce342da98ff5c4f932ff30e2017-05-01T00:00:00Zhttps://doi.org/10.1038/s41598-017-01681-9https://doaj.org/toc/2045-2322Abstract An accurate method to predict the mortality in the intensive care unit (ICU) patients has been required, especially in children. The aim of this study is to evaluate the value of serum anion gap (AG) for predicting mortality in pediatric ICU (PICU). We reviewed a data of 461 pediatric patients were collected on PICU admission. Corrected anion gap (cAG), the AG compensated for abnormal albumin levels, was significantly lower in survivors compared with nonsurvivors (p < 0.001). Multivariable logistic regression analysis identified the following variables as independent predictors of mortality; cAG (OR 1.110, 95% CI 1.06–1.17; p < 0.001), PIM3 [OR 7.583, 95% CI 1.81–31.78; p = 0.006], and PRISM III [OR 1.076, 95% CI 1.02–1.14; p = 0.008]. Comparing AUCs for mortality prediction, there were no statistically significant differences between cAG and other mortality prediction models; cAG 0.728, PIM2 0.779, PIM3 0.822, and PRISM III 0.808. The corporation of cAG to pre-existing mortality prediction models was significantly more accurate at predicting mortality than using any of these models alone. We concluded that cAG at ICU admission may be used to predict mortality in children, regardless of underlying etiology. And the incorporation of cAG to pre-existing mortality prediction models might improve predictability.Min Jung KimYoon Hee KimIn Suk SolSoo Yeon KimJong Deok KimHa Yan KimKyung Won KimMyung Hyun SohnKyu-Earn KimNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 7, Iss 1, Pp 1-8 (2017)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Min Jung Kim Yoon Hee Kim In Suk Sol Soo Yeon Kim Jong Deok Kim Ha Yan Kim Kyung Won Kim Myung Hyun Sohn Kyu-Earn Kim Serum anion gap at admission as a predictor of mortality in the pediatric intensive care unit
description	Abstract An accurate method to predict the mortality in the intensive care unit (ICU) patients has been required, especially in children. The aim of this study is to evaluate the value of serum anion gap (AG) for predicting mortality in pediatric ICU (PICU). We reviewed a data of 461 pediatric patients were collected on PICU admission. Corrected anion gap (cAG), the AG compensated for abnormal albumin levels, was significantly lower in survivors compared with nonsurvivors (p < 0.001). Multivariable logistic regression analysis identified the following variables as independent predictors of mortality; cAG (OR 1.110, 95% CI 1.06–1.17; p < 0.001), PIM3 [OR 7.583, 95% CI 1.81–31.78; p = 0.006], and PRISM III [OR 1.076, 95% CI 1.02–1.14; p = 0.008]. Comparing AUCs for mortality prediction, there were no statistically significant differences between cAG and other mortality prediction models; cAG 0.728, PIM2 0.779, PIM3 0.822, and PRISM III 0.808. The corporation of cAG to pre-existing mortality prediction models was significantly more accurate at predicting mortality than using any of these models alone. We concluded that cAG at ICU admission may be used to predict mortality in children, regardless of underlying etiology. And the incorporation of cAG to pre-existing mortality prediction models might improve predictability.
format	article
author	Min Jung Kim Yoon Hee Kim In Suk Sol Soo Yeon Kim Jong Deok Kim Ha Yan Kim Kyung Won Kim Myung Hyun Sohn Kyu-Earn Kim
author_facet	Min Jung Kim Yoon Hee Kim In Suk Sol Soo Yeon Kim Jong Deok Kim Ha Yan Kim Kyung Won Kim Myung Hyun Sohn Kyu-Earn Kim
author_sort	Min Jung Kim
title	Serum anion gap at admission as a predictor of mortality in the pediatric intensive care unit
title_short	Serum anion gap at admission as a predictor of mortality in the pediatric intensive care unit
title_full	Serum anion gap at admission as a predictor of mortality in the pediatric intensive care unit
title_fullStr	Serum anion gap at admission as a predictor of mortality in the pediatric intensive care unit
title_full_unstemmed	Serum anion gap at admission as a predictor of mortality in the pediatric intensive care unit
title_sort	serum anion gap at admission as a predictor of mortality in the pediatric intensive care unit
publisher	Nature Portfolio
publishDate	2017
url	https://doaj.org/article/95c46f186ce342da98ff5c4f932ff30e
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Serum anion gap at admission as a predictor of mortality in the pediatric intensive care unit

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