Evidence map›Paper›PMID 39959699›Full record

ArticleLiver research (Beijing, China)2023

A novel nomogram based on routine clinical indicators for screening for Wilson's disease.

Jiahui Pang, Shuru Chen, Weiqiang Gan, Guofang Tang, Yusheng Jie, Zhanyi Li, Yutian Chong, Youming Chen, Jiao Gong, Xinhua Li and 1 more

Abstract read
In one paragraph

Article in Liver research (Beijing, China), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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

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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

1 citing paper in PubMed.

  1. Insights into the coexistence of WilsonLiver research (Beijing, China) · 2025
    Article
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

11 authors.

Jiahui PangDepartment of Infectious Diseases, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong, China.
Shuru ChenDepartment of Infectious Diseases, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong, China.
Weiqiang GanDepartment of Infectious Diseases, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong, China.
Guofang TangGuangzhou Eighth People's Hospital, Guangzhou Medical University, Guangzhou, Guangdong, China.
Yusheng JieDepartment of Infectious Diseases, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong, China.
Zhanyi LiDepartment of Infectious Diseases, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong, China.
Yutian ChongDepartment of Infectious Diseases, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong, China.
Youming ChenDepartment of Infectious Diseases, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong, China.
Jiao GongDepartment of Laboratory Medicine, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong, China.
Xinhua LiDepartment of Infectious Diseases, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong, China.
Yongyu MeiDepartment of Infectious Diseases, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background and aims: There is currently no single model for predicting Wilson's disease (WD). We aimed to create a nomogram using daily clinical parameters to improve the accuracy of WD diagnosis in patients with abnormal liver function. Methods: Between July 2016 and December 2020, we identified 90 WD patients with abnormal liver function who had homozygous or compound heterozygous mutations in the Results: We developed a nomogram for screening for WD based on six predictive factors: serum copper, direct bilirubin, uric acid, cholinesterase, prealbumin, and reticulocyte percentage. In the training cohort, the area under curve (AUC) of the nomogram reached 0.967 (95% confidence interval (CI) 0.946-0.988), while the area under the precision-recall curve was 0.961. Based on the optimal cutpoint of 213.55, our nomogram performed well, with a sensitivity of 96% and a specificity of 87%. In the validation cohort, the AUC of the nomogram was as high as 0.991 (95% CI 0.970-1.000). Conclusions: We developed a nomogram that can predict the risk of WD prior to the detection of serum ceruloplasmin or urinary copper, greatly increasing screening efficiency for patients with abnormal liver function.

Indexed as

DiagnosisNomogramPredictorProbabilistic modelWilson's disease (WD)

Identifiers

PMID39959699
PMCPMC11791895

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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.