Validation of continuous clinical indices of cardiometabolic risk in a cohort of Australian adults

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dc.contributor.authorCarroll, S.
dc.contributor.authorPaquet, C.
dc.contributor.authorHoward, N.
dc.contributor.authorAdams, R.
dc.contributor.authorTaylor, A.
dc.contributor.authorDaniel, M.
dc.date.issued2014
dc.description.abstractBackground: Indicators of cardiometabolic risk typically include non-clinical factors (e.g., smoking). While the incorporation of non-clinical factors can improve absolute risk prediction, it is impossible to study the contribution of non-clinical factors when they are both predictors and part of the outcome measure. Metabolic syndrome, incorporating only clinical measures, seems a solution yet provides no information on risk severity. The aims of this study were: 1) to construct two continuous clinical indices of cardiometabolic risk (cCICRs), and assess their accuracy in predicting 10-year incident cardiovascular disease and/or type 2 diabetes; and 2) to compare the predictive accuracies of these cCICRs with existing risk indicators that incorporate non-clinical factors (Framingham Risk Scores). Methods: Data from a population-based biomedical cohort (n = 4056) were used to construct two cCICRs from waist circumference, mean arteriole pressure, fasting glucose, triglycerides and high density lipoprotein: 1) the mean of standardised risk factors (cCICR-Z); and 2) the weighted mean of the two first principal components from principal component analysis (cCICR-PCA). The predictive accuracies of the two cCICRs and the Framingham Risk Scores were assessed and compared using ROC curves. Results: Both cCICRs demonstrated moderate accuracy (AUCs 0.72 – 0.76) in predicting incident cardiovascular disease and/or type 2 diabetes, among men and women. There were no significant differences between the predictive accuracies of the cCICRs and the Framingham Risk Scores. Conclusions: cCICRs may be useful in research investigating associations between non-clinical factors and health by providing suitable alternatives to current risk indicators which include non-clinical factors.
dc.description.statementofresponsibilitySuzanne J Carroll, Catherine Paquet, Natasha J Howard, Robert J Adams, Anne W Taylor and Mark Daniel
dc.identifier.citationBMC Cardiovascular Disorders, 2014; 14(1):27-1-27-9
dc.identifier.doi10.1186/1471-2261-14-27
dc.identifier.issn1471-2261
dc.identifier.issn1471-2261
dc.identifier.orcidHoward, N. [0000-0002-8099-3107]
dc.identifier.orcidAdams, R. [0000-0002-7572-0796]
dc.identifier.orcidTaylor, A. [0000-0002-4422-7974]
dc.identifier.urihttp://hdl.handle.net/2440/85818
dc.language.isoen
dc.publisherBioMed Central
dc.relation.granthttp://purl.org/au-research/grants/nhmrc/570150
dc.relation.granthttp://purl.org/au-research/grants/nhmrc/631917
dc.rights© 2014 Carroll et al.; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
dc.source.urihttps://doi.org/10.1186/1471-2261-14-27
dc.subjectCardiometabolic; cardiovascular disease; type 2 diabetes; risk scores; ROC; AUC; validation
dc.titleValidation of continuous clinical indices of cardiometabolic risk in a cohort of Australian adults
dc.typeJournal article
pubs.publication-statusPublished

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