Evidence map›Paper›PMID 35721699›Full record

ArticleThe Lancet regional health. Europe2022

Temporal trends and patterns in atrial fibrillation incidence: A population-based study of 3·4 million individuals.

Jianhua Wu, Ramesh Nadarajah, Yoko M Nakao, Kazuhiro Nakao, Chris Wilkinson, Mamas A Mamas, A John Camm, Chris P Gale

Open access · goldAbstract read
In one paragraph

Article in The Lancet regional health. Europe, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 83 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
83citing papers in PubMed, 3 pooled it
15.1field-weighted citation impact, top 1% 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

83 citing papers in PubMed, 3 syntheses or guidelines pooled it, 99 citations in OpenAlex.

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  16. Multimorbidity in Atrial Fibrillation: Impact on Outcomes.Journal of the American Heart Association · 2026
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23 more citing papers are in PubMed but not listed here.

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

8 authors at 4 institutions in 1 country.

Jianhua WuLeeds Institute for Cardiovascular and Metabolic Medicine, University of Leeds, 6 Clarendon Way, Leeds LS2 9DA, UK.
Ramesh NadarajahLeeds Institute for Cardiovascular and Metabolic Medicine, University of Leeds, 6 Clarendon Way, Leeds LS2 9DA, UK.
Yoko M NakaoLeeds Institute for Cardiovascular and Metabolic Medicine, University of Leeds, 6 Clarendon Way, Leeds LS2 9DA, UK.
Kazuhiro NakaoLeeds Institute for Cardiovascular and Metabolic Medicine, University of Leeds, 6 Clarendon Way, Leeds LS2 9DA, UK.
Chris WilkinsonFaculty of Medical Sciences, Population Health Sciences Institute, Newcastle University, UK.
Mamas A MamasKeele Cardiovascular Research Group, Institute for Prognosis Research, University of Keele, Keele, UK.
A John CammMolecular and Clinical Sciences Research Institute, St George's University of London, UK.
Chris P GaleLeeds Institute for Cardiovascular and Metabolic Medicine, University of Leeds, 6 Clarendon Way, Leeds LS2 9DA, UK.
University of Leeds · GBKeele University · GBNewcastle University · GBSt George's, University of London · GB

Funding

British Heart Foundation FS/20/12/34789
6 · The paper itself

Abstract

Background: Population-based studies of atrial fibrillation (AF) incidence are needed to inform health-service planning, but evidence is conflicting. We assessed trends of AF incidence in a large general population cohort from England. Methods: We used linked primary and secondary electronic health records of 3.4 million individuals. Eligible patients aged 16 years and older contributed data between Jan 2 1998 and Dec 31 2017. For patients with incident AF, we extracted baseline characteristics, comorbidities, socioeconomic status and geographic region. We calculated standardised rates by applying direct age and sex standardisation to the 2013 European Standard Population. We applied year-specific, age-specific and sex-specific incidence to UK census mid-year population estimates for yearly total incident AF. Findings: Comparing 2017 to 1998 standardised AF incidence increased by 30% (322 vs. 247 per 100 000 person-years; adjusted incidence ratio [IRR] 1·30, 95% CI 1·27-1·33). Absolute number of incident AF increased by 72% (202 333 vs. 117 880), due to an increasing number of older persons. Comorbidity burden at diagnosis of AF increased (3·74 [SD 2·29] vs 2·58 [1·83]; adjusted difference 1·26, 95% CI 1·14-1·39). The age of AF diagnosis declined in the most deprived individuals compared to the most affluent (adjusted difference 0·74 years, 0·62-0·88). Across the study period, age-standardised incidence was higher in men than women (IRR 1·49; 95% CI 1·46-1·52), and men were younger at diagnosis (adjusted difference 5·53 years; 95% CI 5·36 to 5·69). Socioeconomically deprived individuals had more comorbidities and a higher incidence of AF than the most affluent individuals (IRR 1·20; 95% CI 1·15-1·24). Interpretation: In England AF incidence has increased, and the socioeconomic gradient in age at diagnosis and comorbidity burden widened. This changing burden requires policy-based interventions to achieve health equity. Funding: British Heart Foundation and National Institute for Health Research.

Indexed as

Atrial fibrillationElectronic health recordsIncidenceMultimorbidity

Identifiers

PMID35721699
PMCPMC9198843
OpenAlexW4224879894

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.