Please use this identifier to cite or link to this item:
https://hdl.handle.net/2440/85818
Citations | ||
Scopus | Web of Science® | Altmetric |
---|---|---|
?
|
?
|
Type: | Journal article |
Title: | Validation of continuous clinical indices of cardiometabolic risk in a cohort of Australian adults |
Author: | Carroll, S. Paquet, C. Howard, N. Adams, R. Taylor, A. Daniel, M. |
Citation: | BMC Cardiovascular Disorders, 2014; 14(1):27-1-27-9 |
Publisher: | BioMed Central |
Issue Date: | 2014 |
ISSN: | 1471-2261 1471-2261 |
Statement of Responsibility: | Suzanne J Carroll, Catherine Paquet, Natasha J Howard, Robert J Adams, Anne W Taylor and Mark Daniel |
Abstract: | Background: 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. |
Keywords: | Cardiometabolic; cardiovascular disease; type 2 diabetes; risk scores; ROC; AUC; validation |
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. |
DOI: | 10.1186/1471-2261-14-27 |
Grant ID: | http://purl.org/au-research/grants/nhmrc/570150 http://purl.org/au-research/grants/nhmrc/631917 |
Published version: | http://dx.doi.org/10.1186/1471-2261-14-27 |
Appears in Collections: | Aurora harvest 2 Medicine publications |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
hdl_85818.pdf | Published version | 685.02 kB | Adobe PDF | View/Open |
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.