Evidence map›Paper›PMID 38514272›Full record

ReviewZhonghua gan zang bing za zhi = Zhonghua ganzangbing zazhi = Chinese journal of hepatology2024

[Predictive factors for HBsAg-negative seroconversion in chronic hepatitis B after antiviral therapy].

L L Wu, Z L Gao

Open access · greenAbstract readReviewEnglish Abstract
In one paragraph

Review in Zhonghua gan zang bing za zhi = Zhonghua ganzangbing zazhi = Chinese journal of hepatology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact, top 77% 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

2 citing papers in PubMed, 0 citations in OpenAlex.

  1. Article
  2. [Dynamic changes of HBsAb and its predictive value in patients with chronic hepatitis B receiving antiviral therapy for clinical cure].Zhonghua gan zang bing za zhi = Zhonghua ganzangbing zazhi = Chinese journal of hepatology · 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

2 authors at 1 institution in 1 country.

L L WuDepartment of Infectious Diseases, Third Affiliated Hospital of Sun Yat-sen University, Guangzhou 501630, China.
Z L GaoDepartment of Infectious Diseases, Third Affiliated Hospital of Sun Yat-sen University, Guangzhou 501630, China.
Sun Yat-sen University · CN

Funding

Guangzhou Science and Technology Program Key Projects 2023B01J1007National Natural Science Foundation of China 82170612
6 · The paper itself

Abstract

Hepatitis B surface antigen (HBsAg) negative seroconversion (HBsAg < 0.05 IU/ml) is research hotspot in the field of hepatitis at this stage, and patients who achieve HBsAg negative seroconversion have significantly fewer liver-related complications. Presently, there are many studies with regard to HBsAg-negative seroconversion, but there are still relatively few indicators used in clinical practice to predict HBsAg-negative seroconversion. Low baseline HBsAg quantification and dynamic decline during treatment are currently recognized as the best indicators for predicting HBsAg-negative seroconversion. However, other factors such as viral genotype, elevated transaminases during treatment course, immune cell function and cytokine levels, and host factors can all influence HBsAg-negative seroconversion. This article reviews the relevant indicators and potential predictive factors for HBsAg-negative seroconversion.

Indexed as

Hepatitis B, ChronicHepatitis B Surface AntigensAntiviral AgentsDNA, ViralHepatitis B e AntigensHepatitis B virusHumansInterferon-alphaSeroconversionTreatment OutcomeAntiviral AgentsDNA, ViralHepatitis B e AntigensHepatitis B Surface AntigensInterferon-alphaChronic hepatitis BClinical cureHepatitis B surface antigenPredictor

Identifiers

PMID38514272
PMCPMC12850704
OpenAlexW4394761471

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.