Evidence map›Paper›PMID 33422437›Full record

ArticleEuropean journal of vascular and endovascular surgery : the official journal of the European Society for Vascular Surgery2021

Development and Internal Validation of a Risk Score to Detect Asymptomatic Carotid Stenosis.

Michiel H F Poorthuis, Paul Sherliker, Dylan R Morris, M Sofia Massa, Robert Clarke, Natalie Staplin, Sarah Lewington, Gert J de Borst, Richard Bulbulia, Alison Halliday

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In one paragraph

Article in European journal of vascular and endovascular surgery : the official journal of the European Society for Vascular Surgery, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed, 3 pooled it
3.1field-weighted citation impact, top 8% 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

16 citing papers in PubMed, 3 syntheses or guidelines pooled it, 33 citations in OpenAlex.

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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

10 authors at 3 institutions in 2 countries.

Michiel H F PoorthuisClinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK; MRC Population Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK; Department of Vascular Surgery, University Medical Centre Utrecht, Utrecht, The Netherlands.
Paul SherlikerClinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK; MRC Population Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK.
Dylan R MorrisClinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK; MRC Population Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK.
M Sofia MassaClinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK.
Robert ClarkeClinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK.
Natalie StaplinClinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK; MRC Population Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK.
Sarah LewingtonClinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK; MRC Population Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK.
Gert J de BorstDepartment of Vascular Surgery, University Medical Centre Utrecht, Utrecht, The Netherlands.
Richard BulbuliaClinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK; MRC Population Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK. Electronic address: richard.bulbulia@ctsu.ox.ac.uk.
Alison HallidayNuffield Department of Surgical Sciences, John Radcliffe Hospital, University of Oxford, Oxford, UK.
University of Oxford · GBUniversity Medical Center Utrecht · NLJohn Radcliffe Hospital · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveAsymptomatic carotid stenosis (ACS) is associated with an increased risk of ischaemic stroke and myocardial infarction. Risk scores have been developed to detect individuals at high risk of ACS, thereby enabling targeted screening, but previous external validation showed scope for refinement of prediction by adding additional predictors. The aim of this study was to develop a novel risk score in a large contemporary screened population.

methodsA prediction model was developed for moderate (≥50%) and severe (≥70%) ACS using data from 596 469 individuals who attended screening clinics. Variables that predicted the presence of ≥50% and ≥70% ACS independently were determined using multivariable logistic regression. Internal validation was performed using bootstrapping techniques. Discrimination was assessed using area under the receiver operating characteristic curves (AUROCs) and agreement between predicted and observed cases using calibration plots.

resultsPredictors of ≥50% and ≥70% ACS were age, sex, current smoking, diabetes mellitus, prior stroke/transient ischaemic attack, coronary artery disease, peripheral arterial disease, blood pressure, and blood lipids. Models discriminated between participants with and without ACS reliably, with an AUROC of 0.78 (95% confidence interval [CI] 0.77-0.78) for ≥ 50% ACS and 0.82 (95% CI 0.81-0.82) for ≥ 70% ACS. The number needed to screen in the highest decile of predicted risk to detect one case with ≥50% ACS was 13 and that of ≥70% ACS was 58. Targeted screening of the highest decile identified 41% of cases with ≥50% ACS and 51% with ≥70% ACS.

conclusionThe novel risk model predicted the prevalence of ACS reliably and performed better than previous models. Targeted screening among the highest decile of predicted risk identified around 40% of all cases with ≥50% ACS. Initiation or intensification of cardiovascular risk management in detected cases might help to reduce both carotid related ischaemic strokes and myocardial infarctions.

Indexed as

AgedAsymptomatic DiseasesCarotid StenosisCohort StudiesFemaleHumansLogistic ModelsMaleMiddle AgedPredictive Value of TestsReproducibility of ResultsRisk AssessmentRisk FactorsROC CurveAtherosclerosisCarotid artery stenosisIschaemic strokePreventionRisk prediction modelTargeted screening

Identifiers

PMID33422437
PMCPMC7994015
OpenAlexW3108510474

What OpenQuestion holds

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LicenceCC BY
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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.