Evidence map›Paper›PMID 26779260›Full record

ReviewInterdisciplinary perspectives on infectious diseases2015

Imaging Based Methods of Liver Fibrosis Assessment in Viral Hepatitis: A Practical Approach.

Hicham Khallafi, Kamran Qureshi

Open access · goldAbstract readReview
In one paragraph

Review in Interdisciplinary perspectives on infectious diseases, 2015. 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
0.2field-weighted citation impact, top 38% 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, 2 citations in OpenAlex.

  1. Observational
  2. 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 2 institutions in 1 country.

Hicham KhallafiDivision of Gastroenterology, Case Western Reserve University, School of Medicine, MetroHealth System, 2500 MetroHealth Drive, Cleveland, OH 44109, USA.
Kamran QureshiSection of Gastroenterology and Hepatology, Temple University Lewis Katz School of Medicine, Temple University Health System, 3440 N. Broad Street, Philadelphia, PA 19140, USA.
MetroHealth Medical Center · USTemple University Health System · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Liver fibrosis represents the repair mechanism in liver injury and is a feature of most chronic liver diseases. The degree of liver fibrosis in chronic viral hepatitis infections has major clinical implications and presence of advanced fibrosis or cirrhosis determines prognosis. Treatment initiation for viral hepatitis is indicated in most cases of advanced liver fibrosis and diagnosis of cirrhosis entails hepatology evaluation for specialized clinical care. Liver biopsy is an invasive technique and has been the standard of care of fibrosis assessment for years; however, it has several limitations and procedure related complications. Recently, several methods of noninvasive assessment of liver fibrosis have been developed which require either serologic testing or imaging of liver. Imaging based noninvasive techniques are reviewed here and their clinical use is described. Some of the imaging based tests are becoming widely available, and collectively they are shown to be superior to liver biopsy in important aspects. Clinical utilization of these methods requires understanding of performance and quality related parameters which can affect the results and provide wrong assessment of the extent of liver fibrosis. Familiarity with the strengths and weaknesses of each modality is needed to correctly interpret the results in appropriate clinical context.

Identifiers

PMID26779260
PMCPMC4686715
OpenAlexW2196434792

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.