Evidence map›Paper›PMID 36895179›Full record

ArticleEuropean journal of preventive cardiology2023

Determining cardiovascular risk in patients with unattributed chest pain in UK primary care: an electronic health record study.

Kelvin P Jordan, Trishna Rathod-Mistry, Danielle A van der Windt, James Bailey, Ying Chen, Lorna Clarson, Spiros Denaxas, Richard A Hayward, Harry Hemingway, Theocharis Kyriacou and 1 more

Open access · hybridAbstract read
In one paragraph

Article in European journal of preventive cardiology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
1.1field-weighted citation impact, top 21% 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

4 citing papers in PubMed, 5 citations in OpenAlex.

  1. Review
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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

11 authors at 4 institutions in 2 countries.

Kelvin P JordanSchool of Medicine, David Weatherall Building, University Road, Keele University, Staffordshire ST5 5BG, UK.ORCID 0000-0003-4748-5335
Trishna Rathod-MistrySchool of Medicine, David Weatherall Building, University Road, Keele University, Staffordshire ST5 5BG, UK.
Danielle A van der WindtSchool of Medicine, David Weatherall Building, University Road, Keele University, Staffordshire ST5 5BG, UK.
James BaileySchool of Medicine, David Weatherall Building, University Road, Keele University, Staffordshire ST5 5BG, UK.
Ying ChenSchool of Medicine, David Weatherall Building, University Road, Keele University, Staffordshire ST5 5BG, UK.
Lorna ClarsonSchool of Medicine, David Weatherall Building, University Road, Keele University, Staffordshire ST5 5BG, UK.
Spiros DenaxasInstitute of Health Informatics, University College London, 222 Euston Road, London NW1 2DA, UK.ORCID 0000-0001-9612-7791
Richard A HaywardSchool of Medicine, David Weatherall Building, University Road, Keele University, Staffordshire ST5 5BG, UK.
Harry HemingwayInstitute of Health Informatics, University College London, 222 Euston Road, London NW1 2DA, UK.
Theocharis KyriacouSchool of Computing and Mathematics, Keele University, Staffordshire ST5 5AA, UK.
Mamas A MamasKeele Cardiovascular Research Group, School of Medicine, David Weatherall Building, University Road, Keele University, Staffordshire ST5 5BG, UK.
Keele University · GBHealth Data Research UK · GBNational Institute for Health Research · GBNuffield Orthopaedic Centre · GB

Funding

British Heart Foundation AA/18/6/24223British Heart Foundation PG/19/46/34307Department of HealthMedical Research Council MC_PC_20059
6 · The paper itself

Abstract

aimsMost adults presenting in primary care with chest pain symptoms will not receive a diagnosis ('unattributed' chest pain) but are at increased risk of cardiovascular events. To assess within patients with unattributed chest pain, risk factors for cardiovascular events and whether those at greatest risk of cardiovascular disease can be ascertained by an existing general population risk prediction model or by development of a new model. METHODS AND

resultsThe study used UK primary care electronic health records from the Clinical Practice Research Datalink linked to admitted hospitalizations. Study population was patients aged 18 plus with recorded unattributed chest pain 2002-2018. Cardiovascular risk prediction models were developed with external validation and comparison of performance to QRISK3, a general population risk prediction model. There were 374 917 patients with unattributed chest pain in the development data set. The strongest risk factors for cardiovascular disease included diabetes, atrial fibrillation, and hypertension. Risk was increased in males, patients of Asian ethnicity, those in more deprived areas, obese patients, and smokers. The final developed model had good predictive performance (external validation c-statistic 0.81, calibration slope 1.02). A model using a subset of key risk factors for cardiovascular disease gave nearly identical performance. QRISK3 underestimated cardiovascular risk.

conclusionPatients presenting with unattributed chest pain are at increased risk of cardiovascular events. It is feasible to accurately estimate individual risk using routinely recorded information in the primary care record, focusing on a small number of risk factors. Patients at highest risk could be targeted for preventative measures.

Indexed as

Cardiovascular DiseasesAdultChest PainElectronic Health RecordsHeart Disease Risk FactorsHumansMalePrimary Health CareRisk AssessmentRisk FactorsUnited KingdomCardiovascular diseaseChest painElectronic health recordsEpidemiologyPrimary health careRisk

Identifiers

PMID36895179
PMCPMC10442054
OpenAlexW4323812502

What OpenQuestion holds

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LicenceCC BY
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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.