Evidence map›Paper›PMID 34447231›Full record

ReviewWorld journal of gastroenterology2021

Muscular abnormalities in liver cirrhosis.

Andrej Hari

Open access · greenAbstract readReview
In one paragraph

Review in World journal of gastroenterology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 2 pooled it
1.9field-weighted citation impact, top 14% 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

11 citing papers in PubMed, 2 syntheses or guidelines pooled it, 17 citations in OpenAlex.

  1. Pooled it
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  6. Review
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  10. Journal of investigative medicine high impact case reports
    Article
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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

1 author at 1 institution in 1 country.

Andrej HariDepartment of Gastroenterology and Hepatology, General Hospital Celje, Celje 3000, Savinjska, Slovenia. andrej.hari@sb-celje.si.
College of Nursing in Celje · SI

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Sarcopenia is becoming a well-established player in evaluating patients with chronic liver disease. Data regarding its clinical significance and consequences in the course of liver disease have been growing; many of the data support the idea that it impacts decompensation event frequency, prolonged hospitalization, and mortality, as well as providing the possibility to better prioritize patients on lists awaiting liver transplantation. When assessing the whole clinical scope of the field, which includes malnutrition and frailty, as well as the complete spectrum of muscle mass, strength, and function, it becomes clear that a well-founded approach in everyday clinical practice is essential. In this respect, this article attempts to unveil the most recently published data regarding possible methods and modalities that could be used to diagnose sarcopenia as early as possible, along with the required accuracy and reliability. From the most important field discoveries to data that need further clarification, the merits and weaknesses of the very diverse existing evaluation methods are presented. Finally, a critical overview is given, in an attempt to discern study lines of importance from those that could pose further ambiguity for the theme. The author also poses relevant questions that remain unanswered but are of clinical importance in the field.

Indexed as

Liver TransplantationMalnutritionSarcopeniaHumansLiver CirrhosisReproducibility of ResultsFrailtyLiver cirrhosisMuscle strengthNutrition indicesRisk factorsSarcopenia

Identifiers

PMID34447231
PMCPMC8371506
OpenAlexW3189069964

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.