Normative equations for central augmentation index: assessment of inter-population applicability and how it could be improved

Sci Rep. 2016 May 27:6:27016. doi: 10.1038/srep27016.

Abstract

Common reference values of arterial stiffness indices could be effective screening tool in detecting vascular phenotypes at risk. However, populations of the same ethnicity may differ in vascular phenotype due to different environmental pressure. We examined applicability of normative equations for central augmentation index (cAIx) derived from Danish population with low cardiovascular risk on the corresponding Croatian population from the Mediterranean area. Disagreement between measured and predicted cAIx was assessed by Bland-Altman analysis. Both, cAIx-age distribution and normative equation fitted on Croatian data were highly comparable to Danish low-risk sample. Contrarily, Bland-Altman analysis of cAIx disagreement revealed a curvilinear deviation from the line of full agreement indicating that the equations were not equally applicable across age ranges. Stratification of individual data into age decades eliminated curvilinearity in all but the 30-39 (men) and 40-49 (women) decades. In other decades, linear disagreement independent of age persisted indicating that cAIx determinants other than age were not envisaged/compensated for by proposed equations. Therefore, established normative equations are equally applicable to both Nordic and Mediterranean populations but are of limited use. If designed for narrower age ranges, the equations' sensitivity in detecting vascular phenotypes at risk and applicability to different populations could be improved.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Age Factors
  • Aged
  • Analysis of Variance
  • Cardiovascular Diseases / diagnosis
  • Cardiovascular Diseases / physiopathology
  • Croatia
  • Cross-Sectional Studies
  • Denmark
  • Female
  • Humans
  • Male
  • Middle Aged
  • Pulse Wave Analysis / methods
  • Pulse Wave Analysis / statistics & numerical data*
  • Reference Values
  • Risk Factors
  • Sex Factors
  • Vascular Stiffness*