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


Journal

European journal of vascular and endovascular surgery : the official journal of the European Society for Vascular Surgery
ISSN: 1532-2165
Titre abrégé: Eur J Vasc Endovasc Surg
Pays: England
ID NLM: 9512728

Informations de publication

Date de publication:
03 2021
Historique:
received: 13 05 2020
revised: 07 10 2020
accepted: 16 11 2020
pubmed: 11 1 2021
medline: 13 4 2021
entrez: 10 1 2021
Statut: ppublish

Résumé

Asymptomatic 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. A 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. Predictors 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. The 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.

Identifiants

pubmed: 33422437
pii: S1078-5884(20)31050-9
doi: 10.1016/j.ejvs.2020.11.029
pmc: PMC7994015
pii:
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

365-373

Commentaires et corrections

Type : CommentIn

Informations de copyright

Copyright © 2020 The Authors. Published by Elsevier B.V. All rights reserved.

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Auteurs

Michiel H F Poorthuis (MHF)

Clinical 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 Sherliker (P)

Clinical 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 Morris (DR)

Clinical 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 Massa (MS)

Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK.

Robert Clarke (R)

Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK.

Natalie Staplin (N)

Clinical 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 Lewington (S)

Clinical 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 Borst (GJ)

Department of Vascular Surgery, University Medical Centre Utrecht, Utrecht, The Netherlands.

Richard Bulbulia (R)

Clinical 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 Halliday (A)

Nuffield Department of Surgical Sciences, John Radcliffe Hospital, University of Oxford, Oxford, UK.

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