INTRODUCTION: The ambulatory arterial stiffness index (AASI), derived from ambulatory blood pressure monitoring (ABPM) recordings, has been proposed as a surrogate marker of arterial stiffness. However, there is controversy to what extent it reflects stiffness or is affected by other parameters. Using a previously validated one-dimensional computer model of the arterial circulation, the relative importance of the different determinants of the AASI was explored. METHODS: Arterial distensibility (inverse of stiffness), peripheral resistance, heart rate, maximal cardiac elastance and venous filling pressure were varied from 80 to 120% of their initial value in steps of 10% to generate 3125 BP values, mimicking the daily fluctuations in one theoretical patient. From this dataset, we assessed the confidence with which AASI can be derived in this patient, as well as the influence of different individual parameters on AASI. To assess the ability of AASI to detect large changes in arterial stiffness, two additional patients were simulated with a distensibility of 50 and 25% of the default distensibility, respectively. RESULTS: The distribution of AASI values, obtained from 10 000 ABPM simulations (each using 72 BP values randomly selected among 3125) was normal [AASI = 0.43 ± 0.04 (SD)]. An increase in heart rate, distensibility or resistance from 80 to 120% of its default value caused the AASI to decrease by 37, 21 or 9%, respectively. Whereas there was no overlap in the distensibility ranges for the three theoretical patients, the amount of overlap between the AASI distributions was substantial. CONCLUSION: The confounding effects of vascular resistance and heart rate seriously limit the use of AASI as a marker of stiffness.
INTRODUCTION: The ambulatory arterial stiffness index (AASI), derived from ambulatory blood pressure monitoring (ABPM) recordings, has been proposed as a surrogate marker of arterial stiffness. However, there is controversy to what extent it reflects stiffness or is affected by other parameters. Using a previously validated one-dimensional computer model of the arterial circulation, the relative importance of the different determinants of the AASI was explored. METHODS: Arterial distensibility (inverse of stiffness), peripheral resistance, heart rate, maximal cardiac elastance and venous filling pressure were varied from 80 to 120% of their initial value in steps of 10% to generate 3125 BP values, mimicking the daily fluctuations in one theoretical patient. From this dataset, we assessed the confidence with which AASI can be derived in this patient, as well as the influence of different individual parameters on AASI. To assess the ability of AASI to detect large changes in arterial stiffness, two additional patients were simulated with a distensibility of 50 and 25% of the default distensibility, respectively. RESULTS: The distribution of AASI values, obtained from 10 000 ABPM simulations (each using 72 BP values randomly selected among 3125) was normal [AASI = 0.43 ± 0.04 (SD)]. An increase in heart rate, distensibility or resistance from 80 to 120% of its default value caused the AASI to decrease by 37, 21 or 9%, respectively. Whereas there was no overlap in the distensibility ranges for the three theoretical patients, the amount of overlap between the AASI distributions was substantial. CONCLUSION: The confounding effects of vascular resistance and heart rate seriously limit the use of AASI as a marker of stiffness.
Authors: Y Wang; J J Mu; L K Geng; D Wang; K Y Ren; T S Guo; C Chu; B Q Xie; F Q Liu; Z Y Yuan Journal: Braz J Med Biol Res Date: 2014-11-07 Impact factor: 2.590