Evidence map›Paper›PMID 40650685›Full record

ArticleEuropean journal of pediatrics2025

Aspartate aminotransferase-based risk stratification for liver injury in pediatric patients: developing a simple rule for predicting adverse outcomes.

Xun Li, Haipeng Yan, Xiao Li, Ting Luo, Xiangyu Wang, Longlong Xie, Yufan Yang, Pingping Liu, Xinping Zhang, Jiaotian Huang and 2 more

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Article in European journal of pediatrics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

12 authors.

Xun Li *Pediatrics Research Institute of Hunan Province, Affiliated Children's Hospital of Xiangya School of Medicine, Central South University (Hunan Children's Hospital), Changsha, China. li.xunxx@qq.com.
Haipeng Yan *Pediatric Intensive Care Unit, Affiliated Children's Hospital of Xiangya School of Medicine, Central South University (Hunan Children's Hospital), Changsha, China.
Xiao LiPediatric Intensive Care Unit, Affiliated Children's Hospital of Xiangya School of Medicine, Central South University (Hunan Children's Hospital), Changsha, China.
Ting LuoPediatrics Research Institute of Hunan Province, Affiliated Children's Hospital of Xiangya School of Medicine, Central South University (Hunan Children's Hospital), Changsha, China.
Xiangyu WangPediatrics Research Institute of Hunan Province, Affiliated Children's Hospital of Xiangya School of Medicine, Central South University (Hunan Children's Hospital), Changsha, China.
Longlong XiePediatrics Research Institute of Hunan Province, Affiliated Children's Hospital of Xiangya School of Medicine, Central South University (Hunan Children's Hospital), Changsha, China.
Yufan YangPediatric Intensive Care Unit, Affiliated Children's Hospital of Xiangya School of Medicine, Central South University (Hunan Children's Hospital), Changsha, China.
Pingping LiuPediatric Intensive Care Unit, Affiliated Children's Hospital of Xiangya School of Medicine, Central South University (Hunan Children's Hospital), Changsha, China.
Xinping ZhangPediatric Intensive Care Unit, Affiliated Children's Hospital of Xiangya School of Medicine, Central South University (Hunan Children's Hospital), Changsha, China.
Jiaotian HuangPediatric Intensive Care Unit, Affiliated Children's Hospital of Xiangya School of Medicine, Central South University (Hunan Children's Hospital), Changsha, China.
Xiulan LuSchool of Pediatrics, University of South China, Hengyang, China. 13787252674@163.com.
Zhenghui XiaoPediatric Intensive Care Unit, Affiliated Children's Hospital of Xiangya School of Medicine, Central South University (Hunan Children's Hospital), Changsha, China. xiaozhenghui888@163.com.

Funding

Hunan Provincial Health High-Level Talent Scientific Research Project R2023143Hunan Provincial Health High-Level Talent Scientific Research Project R2023156Hunan Provincial Key Laboratory of Emergency Medicine for Children 2018TP1028Hunan Provincial Natural Science Foundation of China 2022JJ40203National Natural Science Foundation of China 82102285Science and Technology Innovation Program of Hunan Province 2024RC3230
6 · The paper itself

Abstract

Aspartate aminotransferase (AST) and alanine aminotransferase (ALT) are the most commonly used biomarkers for liver injury, but they are insufficient on their own as prognostic indicators. This study aims to develop a simple method that combines aminotransferases with other routinely available liver function parameters to identify pediatric patients at high risk of adverse outcomes. Medical records from 144,044 pediatric patients with ALT and AST test results were analyzed. The trend in the change of adverse outcome rates by percentiles of AST and ALT was examined to identify a sub-population potentially at risk of liver injury. Within this sub-population, a logistic regression-based prediction rule was developed using liver injury and function markers to predict adverse outcomes. Results showed that an AST level of 80 IU/L can serve as a threshold to identify pediatric patients at higher risk for adverse outcomes. The prediction rule for AST-based risk stratification for liver injury (ASTLI) was developed as follows: among patients with AST > 80 IU/L, the presence of up to two abnormalities in total protein (or albumin), lactate dehydrogenase, or international normalized ratio (or prothrombin time) can help further stratify those at high risk for adverse outcomes (training set: sensitivity = 76%, specificity = 73%; validation set: sensitivity = 76%, specificity = 79%). Age and disease subgroup analysis demonstrated potential for broad applicability across various pediatric populations.

conclusionThe stratification rule could serve as a fast risk stratification tool for liver injury among pediatric patients. WHAT IS KNOWN: • ALT and AST are the most commonly used biomarkers for liver injury. • An elevation in AST and ALT does not always necessitate specific therapeutic intervention nor does it necessarily correlate with disease severity or prognosis. WHAT IS NEW: • A stratification rule was developed to identify pediatric patients at high risk for adverse outcomes. It incorporates AST > 80 IU/L and up to two abnormalities in total protein (or albumin), lactate dehydrogenase, or international normalized ratio (or prothrombin time).

Indexed as

Aspartate AminotransferasesClinical Decision RulesLiver DiseasesAdolescentAlanine TransaminaseBiomarkersChildChild, PreschoolFemaleHumansInfantInfant, NewbornLiver Function TestsL-Lactate DehydrogenaseLogistic ModelsMaleAlanine TransaminaseAspartate AminotransferasesBiomarkersL-Lactate DehydrogenaseAspartate aminotransferaseChildrenLiver injuryPrediction ruleRisk stratification

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.