Evidence map›Paper›PMID 30618162›Full record

ArticleEuropean journal of heart failure2019

Risk factors for incident heart failure in age- and sex-specific strata: a population-based cohort using linked electronic health records.

Alicia Uijl, Stefan Koudstaal, Kenan Direk, Spiros Denaxas, Rolf H H Groenwold, Amitava Banerjee, Arno W Hoes, Harry Hemingway, Folkert W Asselbergs

Open access · hybridAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in European journal of heart failure, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed, 3 pooled it
6.8field-weighted citation impact, top 3% 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, 3 syntheses or guidelines pooled it, 67 citations in OpenAlex.

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  17. NETosis as a Pathogenic Factor for Heart Failure.Oxidative medicine and cellular longevity · 2021
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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

9 authors at 5 institutions in 2 countries.

Alicia UijlJulius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands.
Stefan KoudstaalFarr Institute of Health Informatics Research, Institute of Health Informatics, University College London, London, UK.
Kenan DirekFarr Institute of Health Informatics Research, Institute of Health Informatics, University College London, London, UK.
Spiros DenaxasFarr Institute of Health Informatics Research, Institute of Health Informatics, University College London, London, UK.
Rolf H H GroenwoldJulius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands.
Amitava BanerjeeFarr Institute of Health Informatics Research, Institute of Health Informatics, University College London, London, UK.
Arno W HoesJulius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands.
Harry HemingwayFarr Institute of Health Informatics Research, Institute of Health Informatics, University College London, London, UK.
Folkert W AsselbergsFarr Institute of Health Informatics Research, Institute of Health Informatics, University College London, London, UK.
Utrecht University · NLFarr Institute · GBUniversity College London · GBUniversity College London Hospitals NHS Foundation Trust · GBUniversity Medical Center Utrecht · NL

Funding

Medical Research Council MR/K006584/1Wellcome Trust MR/K006584/1
6 · The paper itself

Abstract

aimsSeveral risk factors for incident heart failure (HF) have been previously identified, however large electronic health records (EHR) datasets may provide the opportunity to examine the consistency of risk factors across different subgroups from the general population. METHODS AND

resultsWe used linked EHR data from 2000 to 2010 as part of the UK-based CALIBER resource to select a cohort of 871 687 individuals 55 years or older and free of HF at baseline. The primary endpoint was the first record of HF from primary or secondary care. Cox proportional hazards analysis was used to estimate hazard ratios for associations between risk factors and incident HF, separately for men and women and by age category: 55-64, 65-74, and > 75 years. During 5.8 years of median follow-up, a total of 47 987 incident HF cases were recorded. Age, social deprivation, smoking, sedentary lifestyle, diabetes, atrial fibrillation, chronic obstructive pulmonary disease, body mass index, haemoglobin, total white blood cell count and creatinine were associated with HF. Smoking, atrial fibrillation and diabetes showed stronger associations with incident HF in women compared to men.

conclusionWe confirmed associations of several risk factors with HF in this large population-based cohort across age and sex subgroups. Mainly modifiable risk factors and comorbidities are strongly associated with incident HF, highlighting the importance of preventive strategies targeting such risk factors for HF.

Indexed as

AgedAge FactorsElectronic Health RecordsFemaleHeart FailureHumansIncidenceMaleMedical Record LinkageMiddle AgedRisk FactorsSex FactorsUnited KingdomElectronic health recordsHeart failureIncidencePopulation attributable riskRisk factors

Identifiers

PMID30618162
PMCPMC7074015
OpenAlexW2908594081

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.