Evidence map›Paper›PMID 31229991›Full record

SynthesisHeart (British Cardiac Society)2019

Weight change and the risk of incident atrial fibrillation: a systematic review and meta-analysis.

Nicholas R Jones, Kathryn S Taylor, Clare J Taylor, Paul Aveyard

Open access · hybridAbstract readMeta-AnalysisSystematic Review
PubMed Full text at PMC Publisher
In one paragraph

Synthesis in Heart (British Cardiac Society), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
30citing papers in PubMed, 3 pooled it
4.2field-weighted citation impact, top 5% 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

30 citing papers in PubMed, 3 syntheses or guidelines pooled it, 58 citations in OpenAlex.

  1. Pooled it
  2. Prediction models for atrial fibrillation applicable in the community: a systematic review and meta-analysis.Europace : European pacing, arrhythmias, and cardiac electrophysiology : journal of the working groups on cardiac pacing, arrhythmias, and cardiac cellular electrophysiology of the European Society of Cardiology · 2020
    Pooled it
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  12. Innovative approaches to atrial fibrillation prediction: should polygenic scores and machine learning be implemented in clinical practice?Europace : European pacing, arrhythmias, and cardiac electrophysiology : journal of the working groups on cardiac pacing, arrhythmias, and cardiac cellular electrophysiology of the European Society of Cardiology · 2024
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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

4 authors at 1 institution in 1 country.

Nicholas R JonesNuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK.ORCID 0000-0002-0352-3785
Kathryn S TaylorNuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK.
Clare J TaylorNuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK.ORCID 0000-0001-8926-2581
Paul AveyardNuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK.
University of Oxford · GB

Funding

Wellcome TrustWellcome Trust 203921/Z/16/Z
6 · The paper itself

Abstract

backgroundThe prevalence of obesity is increasing globally and this could partly explain the worldwide increase in the prevalence of atrial fibrillation (AF), as both overweight and obesity are established risk factors. However, the relationship between weight change and risk of incident AF, independent of starting weight, remains uncertain.

methodsMEDLINE, Embase, Pubmed, Web of Science, Cochrane Central Register of Controlled Trials, Database of Abstracts of Reviews of Effects, Trials Register-clinicaltrials.gov, CINAHL and the WHO ICTRP were searched from inception to July 2018.We included randomised controlled trials and cohort studies across all healthcare settings but excluded studies of bariatric surgery. A random effects model was used to calculate pooled hazard ratios. The primary outcome was the risk of incident AF in relation to weight change.

resultsTen studies, including 108 996 people, met our inclusion criteria. For a 5% gain in weight, the incidence of AF increased by 13% (HR 1.13, 95% CI 1.04 to 1.23, I

conclusionsWeight gain may increase the risk of AF, but there was no clear evidence that non-surgical weight loss altered AF incidence. Strategies to prevent weight gain in the population may reduce the global burden of AF. Given the lack of studies and methodological limitations, further research is needed.

Indexed as

Atrial FibrillationBody WeightHumansIncidenceObesityRisk AssessmentWeight GainWeight LossAtrial FibrillationGlobal Disease PatternsMeta-analysisObesitySystemic Review

Identifiers

PMID31229991
PMCPMC6900224
OpenAlexW2947074780

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.