Evidence map›Paper›PMID 37624589›Full record

ArticleEuropean heart journal2023

Temporal trends of cause-specific mortality after diagnosis of atrial fibrillation.

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

Open access · hybridAbstract read
In one paragraph

Article in European heart journal, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed
7.7field-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

23 citing papers in PubMed, 35 citations in OpenAlex.

  1. Article
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  9. Discovery ofDiagnostics (Basel, Switzerland) · 2025
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  15. Observational
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  17. Identification and Functional Investigation ofDiagnostics (Basel, Switzerland) · 2024
    Article
  18. Article
  19. Article
  20. Global burden of atrial fibrillation/atrial flutter and its attributable risk factors from 1990 to 2021.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
    Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

8 authors at 4 institutions in 1 country.

Jianhua WuCentre for Primary Care, Wolfson Institute of Population Health, Queen Mary University of London, 58 Turner Street, London E1 2AB, UK.ORCID 0000-0001-6093-599X
Ramesh NadarajahLeeds Institute of Data Analytics, University of Leeds, Leeds, UK.ORCID 0000-0001-9895-9356
Yoko M NakaoLeeds Institute of Data Analytics, University of Leeds, Leeds, UK.
Kazuhiro NakaoLeeds Institute of Data Analytics, University of Leeds, Leeds, UK.
Chris WilkinsonAcademic Cardiovascular Unit, South Tees NHS Foundation Trust, Middlesbrough, UK.
J Campbell CowanDepartment of Cardiology, Leeds Teaching Hospitals NHS Trust, Leeds, UK.
A John CammMolecular and Clinical Sciences Research Institute, St George's University of London, London, UK.
Chris P GaleLeeds Institute of Data Analytics, University of Leeds, Leeds, UK.
University of Leeds · GBLeeds Teaching Hospitals NHS Trust · GBSouth Tees Hospitals NHS Foundation Trust · GBSt George's, University of London · GB

Funding

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

Abstract

BACKGROUND AND

aimsReports of outcomes after atrial fibrillation (AF) diagnosis are conflicting. The aim of this study was to investigate mortality and hospitalization rates following AF diagnosis over time, by cause and by patient features.

methodsIndividuals aged ≥16 years with a first diagnosis of AF were identified from the UK Clinical Practice Research Datalink-GOLD dataset from 1 January 2001, to 31 December 2017. The primary outcomes were all-cause and cause-specific mortality and hospitalization at 1 year following diagnosis. Poisson regression was used to calculate rate ratios (RRs) for mortality and incidence RRs (IRRs) for hospitalization and 95% confidence intervals (CIs) comparing 2001/02 and 2016/17, adjusted for age, sex, region, socio-economic status, and 18 major comorbidities.

resultsOf 72 412 participants, mean (standard deviation) age was 75.6 (12.4) years, and 44 762 (61.8%) had ≥3 comorbidities. All-cause mortality declined (RR 2016/17 vs. 2001/02 0.72; 95% CI 0.65-0.80), with large declines for cardiovascular (RR 0.46; 95% CI 0.37-0.58) and cerebrovascular mortality (RR 0.41; 95% CI 0.29-0.60) but not for non-cardio/cerebrovascular causes of death (RR 0.91; 95% CI 0.80-1.04). In 2016/17, deaths caused from dementia (67, 8.0%), outstripped deaths from acute myocardial infarction, heart failure, and acute stroke combined (56, 6.7%, P < .001). Overall hospitalization rates increased (IRR 2016/17 vs. 2001/02 1.17; 95% CI, 1.13-1.22), especially for non-cardio/cerebrovascular causes (IRR 1.42; 95% CI 1.39-1.45). Older, more deprived, and hospital-diagnosed AF patients experienced higher event rates.

conclusionsAfter AF diagnosis, cardio/cerebrovascular mortality and hospitalization has declined, whilst hospitalization for non-cardio/cerebrovascular disease has increased.

Indexed as

Atrial FibrillationHeart FailureStrokeCause of DeathComorbidityHospitalizationHumansRisk FactorsAtrial fibrillationElectronic health recordsHospitalizationMortalityPublic health

Identifiers

PMID37624589
PMCPMC10635669
OpenAlexW4386154231

What OpenQuestion holds

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LicenceCC BY-NC
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Registered trials

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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.