Evidence map›Paper›PMID 32162000›Full record

ArticleEuropean radiology2020

Three-color risk stratification for improving the diagnostic accuracy for biliary atresia.

Yan Chen, Dongying Zhao, Shengli Gu, Yahui Li, Weihua Pan, Yongjun Zhang

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Article in European radiology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed, 2 pooled it
2.2field-weighted citation impact, top 12% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

13 citing papers in PubMed, 2 syntheses or guidelines pooled it, 16 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors at 2 institutions in 1 country.

Yan ChenDepartment of Neonatology, Xinhua Hospital, Shanghai JiaoTong University School of Medicine, 1665 Kong Jiang Road, Shanghai, 200092, China.
Dongying ZhaoDepartment of Neonatology, Xinhua Hospital, Shanghai JiaoTong University School of Medicine, 1665 Kong Jiang Road, Shanghai, 200092, China.
Shengli GuDepartment of Ultrasound, Xinhua Hospital, Shanghai JiaoTong University School of Medicine, Shanghai, China.
Yahui LiDepartment of Neonatology, Xinhua Hospital, Shanghai JiaoTong University School of Medicine, 1665 Kong Jiang Road, Shanghai, 200092, China.
Weihua PanDepartment of Pediatric Surgery, Xinhua Hospital, Shanghai JiaoTong University School of Medicine, 1665 Kong Jiang Road, Shanghai, 200092, China. dr_panwh@163.com.
Yongjun ZhangDepartment of Neonatology, Xinhua Hospital, Shanghai JiaoTong University School of Medicine, 1665 Kong Jiang Road, Shanghai, 200092, China. zhangyongjun@sjtu.edu.cn.
Shanghai Jiao Tong University · CNXinHua Hospital · CN

Funding

National Natural Science Foundation of China 81671501Shanghai Municipal Commission of Health and Family Planning 2016ZB0103
6 · The paper itself

Abstract

objectivesIt is challenging to early differentiate biliary atresia from other causes of cholestasis. We aimed to develop an algorithm with risk stratification to distinguish biliary atresia from infantile cholestasis.

methodsIn this study, we enrolled infants with cholestasis into 2 subgroups from January 2010 to April 2019. A prospective cohort (subgroup 2) of 187 patients (107 with biliary atresia and 80 without biliary atresia) underwent acoustic radiation force impulse elastography. Stepwise regression was used to identify significant predictors of biliary atresia. A sequential algorithm with risk stratification was constructed.

resultsAmong 187 patients, shear wave speed > 1.35 m/s and presence of the triangular cord sign were considered high risk for biliary atresia (red), in which 73 of 78 patients (accuracy of 93.6%) with biliary atresia were identified. Afterwards, γ-GT, abnormal gallbladder, and clay stool were introduced into the algorithm and 55 intermediate-risk infants were identified (yellow) with a diagnostic accuracy of 60% for biliary atresia. Of the remaining 54 infants who were classified as low-risk patients (green), the accuracy for excluding biliary atresia was 98.1%. By applying a three-color risk stratification tool, 70.6% patients were identified as either high risk or low risk for biliary atresia (area under the curve, 0.983; sensitivity, 98.7%; specificity, 91.4%). We also estimated the risk of biliary atresia in different color groups, which was 94.7% (95%CI, 94.3-95.5%) in the red group and 7.2% (95%CI, 6.6-8.3%) in the green group.

conclusionsOur simple noninvasive approach was able to identify biliary atresia with high accuracy. KEY POINTS: • Five predictors, namely shear wave speed, triangle cord sign, γ-glutamyl transferase, abnormal gallbladder, and clay stool, were selected to identify biliary atresia in cholestasis. • Shear wave speed > 1.35 m/s and presence of the triangle cord sign were considered high-risk patients with a diagnostic accuracy of 93.6% for biliary atresia. • Risk for biliary atresia was high (red), intermediate (yellow), or low (green). In the red and green group, we achieved an extremely high diagnostic performance (area under the curve, 0.983; sensitivity, 98.7%; specificity, 91.4%).

Indexed as

AdultBile DuctsBiliary AtresiaCholestasisCohort StudiesColorDiagnosis, DifferentialElasticity Imaging TechniquesFemaleGallbladderHumansInfantMaleProspective StudiesReproducibility of ResultsRisk AssessmentBiliary atresiaDiagnostic testsElasticity imaging techniquesRisk

Identifiers

PMID32162000
OpenAlexW3012155658

What OpenQuestion holds

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Read underepoch 390

Registered trials

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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.