Submitted on June 23, 2004
Accepted on November 1, 2004
Non-symmetrical double logistic analysis of ambulatory blood pressure recordings
Geoffrey A Head1*, Christopher M Reid2, and Elena V Lukoshkova3
1 Neuropharmacology Laboratory, Baker Heart Research Institute, Melbourne, Melbourne, Australia
2 Department of Epidemiology and Preventative Medicine, Monash University, Melbourne, Melbourne, Australia
3 Department of Cardiovascular Regulation, National Cardiology Research Centre, Moscow, Russian Federation
* To whom correspondence should be addressed. E-mail: geoff.head{at}baker.edu.au.
We developed an asymmetric double logistic curve fitting procedure for circadian analysis which can determine the rate of change in variables during the day to night separately from the night to day transition for use in animal studies. We now have applied this procedure to 24hr systolic (SAP) and diastolic arterial pressure (DAP) and heart rate (HR) ambulatory recordings from 302 patients. In 292 cases, all parameters showed a pattern of higher day and lower night values. In males there was a similar rate of transition between day and night or from night to day for both SAP and DAP which lasted 3-4 hours indicating a symmetrical diurnal pattern. By contrast females showed a faster rate of decrease in MAP in the evening compared to males (P <0.05) and therefore showed an asymmetric diurnal SAP pattern. For both males and females there was a markedly greater rate of morning increase in HR compared to the rate of evening decrease (2.2 and 1.9 fold respectively, P <0.001). The logistic method provided a better fit than the square wave or the Cosinor method (P<0.001) and more appropriately detected non dippers. We conclude that analysis of ambulatory recordings by a new logistic curve fitting method reveals more rapid reductions in evening SAP in females than males but both have 2-3 fold more rapid morning rates of tachycardia. The ability of the double logistic method to determine the diurnal blood pressure rates of change independently is key to determining new markers for cardiovascular risk.
