Evidence map›Paper›PMID 27543499›Full record

ReviewBritish medical bulletin2016

Non-alcoholic fatty liver disease in 2016.

S A Townsend, Philip N Newsome

Open access · bronzeAbstract readReview
In one paragraph

Review in British medical bulletin, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 39 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
39citing papers in PubMed, 2 pooled it
8.6field-weighted citation impact, top 2% 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

39 citing papers in PubMed, 2 syntheses or guidelines pooled it, 72 citations in OpenAlex.

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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

2 authors at 2 institutions in 1 country.

S A TownsendNational Institute for Health Research (NIHR) Birmingham Liver Biomedical Research Unit, Centre for Liver Research, University of Birmingham, Birmingham, UK Liver Unit, University Hospital Birmingham NHS Foundation Trust, Birmingham, B15 2WB, UK.
Philip N NewsomeNational Institute for Health Research (NIHR) Birmingham Liver Biomedical Research Unit, Centre for Liver Research, University of Birmingham, Birmingham, UK Liver Unit, University Hospital Birmingham NHS Foundation Trust, Birmingham, B15 2WB, UK p.n.newsome@bham.ac.uk.
NIHR Birmingham Liver Biomedical Research Unit · GBUniversity of Birmingham · GB

Funding

Medical Research Council MR/L022699/1
6 · The paper itself

Abstract

introductionNon-alcoholic fatty liver disease is the commonest cause of liver disease worldwide, and is rapidly becoming the leading indication for liver transplantation. SOURCES OF DATA: Original articles, reviews and meta-analyses, guidelines. AREAS OF AGREEMENT: NAFLD strongly correlates with obesity and insulin resistance; currently, the best management strategy is weight loss and treatment of the metabolic syndrome. AREAS OF CONTROVERSY: Recent data suggest that the presence of fibrosis and not non-alcoholic steatohepatitis (NASH) is the predictor of clinical outcome. GROWING POINTS: Many phase 2 and 3 trials are underway. Drugs hoped to be effective are obeticholic acid, elafibranor, glucagon-like peptide-1 analogues and CCR2/5 inhibitors. AREAS TIMELY FOR DEVELOPING RESEARCH: Improved understanding of the pathophysiology of NAFLD should help us identify which patients progress to significant liver disease and to develop therapies to target this population.

Indexed as

HumansInsulin ResistanceLiver TransplantationMetabolic SyndromeNon-alcoholic Fatty Liver DiseaseObesityRisk FactorsRisk Reduction BehaviorWeight Lossassessmentcardiovascular diseasefibrosismetabolic syndromeNASHnon-alcoholic fatty liver diseaseobesitytreatment

Identifiers

PMID27543499
PMCPMC5862239
OpenAlexW2509952385

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.