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01.12.2014 | Research article | Ausgabe 1/2014 Open Access

BMC Cardiovascular Disorders 1/2014

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

Zeitschrift:
BMC Cardiovascular Disorders > Ausgabe 1/2014
Autoren:
Suzanne J Carroll, Catherine Paquet, Natasha J Howard, Robert J Adams, Anne W Taylor, Mark Daniel
Wichtige Hinweise

Electronic supplementary material

The online version of this article (doi:10.​1186/​1471-2261-14-27) contains supplementary material, which is available to authorized users.

Competing interests

The authors declare that they have no competing interests.

Authors’ contributions

SJC, MD, CP, NJH, AWT, and RJA conceived and designed the study. SJC analysed the data under guidance of CP. SJC, CP, MD contributed to interpretation of results. SJC wrote the manuscript, and CP, NJH, and MD revised it critically for important intellectual content. All authors approved the final manuscript.

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.
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