Evidence map›Paper›PMID 30317798›Full record

ArticleZhonghua gan zang bing za zhi = Zhonghua ganzangbing zazhi = Chinese journal of hepatology2018

[Research progress in prognostic factors of hepatitis B virus-associated end-stage liver disease].

X Feng, X F Shi

Open access · greenAbstract read
In one paragraph

Article in Zhonghua gan zang bing za zhi = Zhonghua ganzangbing zazhi = Chinese journal of hepatology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact, top 72% 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

3 citing papers in PubMed, 1 citations in OpenAlex.

  1. [Analysis of risk factors for decompensated cirrhosis complicated with sepsis].Zhonghua gan zang bing za zhi = Zhonghua ganzangbing zazhi = Chinese journal of hepatology · 2022
    Article
  2. [Research progress on the relationship between liver cirrhosis and thyroid hormones].Zhonghua gan zang bing za zhi = Zhonghua ganzangbing zazhi = Chinese journal of hepatology · 2022
    Review
  3. Review
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.

X FengSecond Affiliated Hospital of Chongqing Medical University, Chongqing 400010, China.
X F Shi
Dalian Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Hepatitis B remains a worldwide health problem with a high mortality rate associated with end-stage liver diseases. The Model for End-Stage Liver Disease and Child-Pugh score is still widely used as the prognostic model for liver cirrhosis and inflammatory reaction, B-type natriuretic peptide and portal vein thrombosis are independent risk factors. Many new models have been proposed for liver failure, including a new model HINAT ACLF. HINAT ACLF is better than its preceding models and increased neutrophil-to-lymphocyte ratio is a single factor to promote thyroid hormone, cholinesterase, and antiviral treatment response in this model. HBV DNA is frequently involved in the predictive model of liver cancer, but with widespread use of antiviral drugs, the value of its long-term prognostication has gradually reduced. Therefore, liver stiffness value instead of HBV DNA shows apparent advantages in mREACH-B. ALBI has good median survival prediction value for hepatocellular carcinoma patients. Alpha-fetoprotein and staging method, which is based on tumor number and size, are still independent risk factors for liver cancer.

Indexed as

Hepatitis B virusAdultCarcinoma, HepatocellularChildEnd Stage Liver DiseaseHepatitis BHumansLiver NeoplasmsPrognosisCarcinoma, hepatocellularCirrhosisHepatitis B virusLiver failurePrognosis

Identifiers

PMID30317798
PMCPMC12768979
OpenAlexW2992467620

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.