Evidence map›Paper›PMID 38047995›Full record

ArticleIndian journal of pediatrics2025

Establishment of Biliary Atresia Prognostic Classification System via Survival-Based Forward Clustering - A New Biliary Atresia Classification.

Chen Xu, Xing Qin, Shuyang Dai, Zhen Shen, Yifan Yang, Yanlei Huang, Song Sun, Shan Zheng, Mengyun Wu, Gong Chen

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Article in Indian journal of pediatrics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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2citing papers in PubMed
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1 · What the graph read from it

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Latest Developments in Artificial Intelligence and Machine Learning Models in General Pediatric Surgery.European journal of pediatric surgery : official journal of Austrian Association of Pediatric Surgery ... [et al] = Zeitschrift fur Kinderchirurgie · 2026
    Review
  2. (T-) Regulation of Immunity in Membranous Nephropathy.Indian journal of pediatrics · 2024
    Article
4 · The record

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5 · Who and what money

Authors and funding

10 authors.

Chen Xu *Department of Pediatric Surgery, Shanghai Key Laboratory of Birth Defect, Children's Hospital of Fudan University, 399 Wan Yuan Road, Shanghai, 201102, China.
Xing Qin *School of Statistics and Information, Shanghai University of International Business and Economics, 1900 Wenxiang Road, Shanghai, 201620, China.
Shuyang Dai *Department of Pediatric Surgery, Shanghai Key Laboratory of Birth Defect, Children's Hospital of Fudan University, 399 Wan Yuan Road, Shanghai, 201102, China.
Zhen ShenDepartment of Pediatric Surgery, Shanghai Key Laboratory of Birth Defect, Children's Hospital of Fudan University, 399 Wan Yuan Road, Shanghai, 201102, China.
Yifan YangDepartment of Pediatric Surgery, Shanghai Key Laboratory of Birth Defect, Children's Hospital of Fudan University, 399 Wan Yuan Road, Shanghai, 201102, China.
Yanlei HuangDepartment of Pediatric Surgery, Shanghai Key Laboratory of Birth Defect, Children's Hospital of Fudan University, 399 Wan Yuan Road, Shanghai, 201102, China.
Song SunDepartment of Pediatric Surgery, Shanghai Key Laboratory of Birth Defect, Children's Hospital of Fudan University, 399 Wan Yuan Road, Shanghai, 201102, China.
Shan ZhengDepartment of Pediatric Surgery, Shanghai Key Laboratory of Birth Defect, Children's Hospital of Fudan University, 399 Wan Yuan Road, Shanghai, 201102, China. szheng@shmu.edu.cn.
Mengyun WuSchool of Statistics and Management, Shanghai University of Finance and Economics, 777 Guoding Road, Shanghai, 200433, China. wu.mengyun@mail.shufe.edu.cn.
Gong ChenDepartment of Pediatric Surgery, Shanghai Key Laboratory of Birth Defect, Children's Hospital of Fudan University, 399 Wan Yuan Road, Shanghai, 201102, China. chengongzlp@hotmail.com.ORCID 0000-0003-3351-0819

Funding

Children's National Medical Center 2022LCKXJ06Children's National Medical Center EK112520180211National Natural Science Foundation of China 81974059National Natural Science Foundation of China 82001595National Natural Science Foundation of China 82270541Shanghai Municipal Key Clinical Specialty shslczdzk05703The Science Foundation of Shanghai 19ZR1406600
6 · The paper itself

Abstract

objectivesTo develop a machine learning algorithm with prognosis data to identify different clinical phenotypes of biliary atresia (BA) and provide instructions for choosing treatment schemes.

methodsSix hundred thirty-nine cases of type III BA were retrospectively collected from the Children's Hospital of Fudan University from Jan 1

resultsA total of 2 clusters were identified (cluster 1 = 324 and cluster 2 = 315), where cluster 2 had a lower 2 y native liver survival post-Kasai rate. The infant patients in cluster 2 have higher weight, liver, and spleen volume, wider portal vein width, and older operative age; worse coagulation and liver function results; higher grade of liver fibrosis and detection rate of hepatic portal fibrous mass, and higher recent infection detection rate of herpes simplex virus type I. With the proposed prognostic classification system, the authors predicted the subtypes of the 187 cases of type III BA in a testing dataset collected from the whole year of 2020. The p-value computed from the log-rank testing for the Kaplan-Meier survival curves of the predicted two testing groups was 0.0113.

conclusionsThis classification system would be a convenient tool to choose appropriate treatment and accelerate the choice-making between clinicians and infant patients.

Indexed as

Biliary AtresiaMachine LearningAlgorithmsCluster AnalysisFemaleHumansInfantInfant, NewbornMalePrognosisRetrospective StudiesBiliary atresiaForward clusteringPrognostic classificationSurvival analysis

Identifiers

PMID38047995

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