Evidence map›Paper›PMID 36611384›Full record

ReviewDiagnostics (Basel, Switzerland)2022

Screening for Liver Fibrosis in the General Population: Where Do We Stand in 2022?

Clémence M Canivet, Jérôme Boursier

Open access · goldAbstract readReview
In one paragraph

Review in Diagnostics (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed, 1 pooled it
4.7field-weighted citation impact, top 4% 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

15 citing papers in PubMed, 1 synthesis or guideline pooled it, 31 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Review
  4. Article
  5. Avian Influenza: Outbreak in Viet Nam in 2024.Infectious disorders drug targets · 2025
    Article
  6. Article
  7. Review
  8. Article
  9. Advances in laboratory medicine · 2024
    Article
  10. Serum biomarkers for liver fibrosis assessment.Advances in laboratory medicine · 2024
    Review
  11. Article
  12. Article
  13. Article
  14. Article
  15. 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.

Clémence M CanivetService d'Hépato-Gastroentérologie et Oncologie Digestive, Centre Hospitalier Universitaire d'Angers, 49100 Angers, France.
Jérôme BoursierService d'Hépato-Gastroentérologie et Oncologie Digestive, Centre Hospitalier Universitaire d'Angers, 49100 Angers, France.
Centre Hospitalier Universitaire d'Angers · FR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Approximately 30% of the worldwide population has at least one risk factor for liver disease. Identifying advanced liver disease before the occurrence of complications remains a difficult challenge in clinical practice, where diagnosis comes too late for many patients, at the time of liver decompensation or palliative hepatocellular carcinoma, with poor short-term prognosis. Noninvasive, blood- or elastography-based tests of liver fibrosis (NITs) have been developed for the early diagnosis of advanced liver fibrosis. Recent population-based studies evaluating the screening of liver fibrosis with these NITs have provided important information on at-risk groups that should be targeted. New measures based on the sequential use of NITs help to better organize the referral of at-risk patients to the liver specialist. However, energizing these measures will require increased awareness of both chronic liver diseases and the use of NITs among non-specialists.

Indexed as

advanced fibrosisFIB-4liver fibrosisNAFLDnoninvasive liver fibrosis testprimary care

Identifiers

PMID36611384
PMCPMC9818643
OpenAlexW4313328016

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.