A new model for diurnal blood pressure profiling. Square wave fit compared with conventional methods.

For the characterization of diurnal blood pressure variation, we developed a simple mathematical model that nevertheless does justice to the specific form characteristics of individual blood pressure registrations. Analysis was based on 24-hour continuous intra-arterial measurement of blood pressure obtained in 23 hospitalized patients with mild-to-moderate untreated essential hypertension (mean +/- SD, 112 +/- 13 mm Hg). The day-night difference for mean arterial pressure varied markedly (mean, 18.6 mm Hg; range, 6.8-36.0). Inspection of profiles suggested a model of blood pressure as two contiguous, complementary periods of constant pressure, a so-called square wave. Determination of the times of transience between both periods (segmentation) was performed individually using a least-square error criterion. Results were compared with those obtained by conventional methods, including analysis by Fourier modeling. The square wave fit accounted for a larger fraction (66%) of circadian variance of mean arterial pressure than modeling based on segmentation by visual inspection (59%, considerable observer bias) or by clock time (50%). Application of the Minnesota Cosinor Method resulted in the poorest description (47%). Segmentation based on harmonic modeling (61%) appeared to be cumbersome (10 harmonics needed), and the significance of additional information offered over the square wave fit is dubious. Observer bias makes segmentation by visual inspection unsuitable for assessment of the circadian variance of blood pressure. Even when daily activities are strictly regulated (hospital environment), circadian variance is not well modeled by clock time. As compared with harmonic analysis, square wave fitting is simple, and it appears to best model the circadian variance. The method can also be applied to data obtained from noninvasive ambulatory blood pressure monitoring.

[1]  P. Linkowski,et al.  Quantitative Analysis of the 24‐Hour Blood Pressure and Heart Rate Patterns in Young Men , 1991, Hypertension.

[2]  A. J. Honour,et al.  Direct arterial pressure, heart rate, and electrocardiogram in unrestricted patients before and after removal of a phaeochromocyoma. , 1974, The Quarterly journal of medicine.

[3]  A. Libretti,et al.  Temporal analysis of blood pressure by ambulatory 24 H blood pressure monitoring. , 1985, Clinical and Experimental Hypertension Part A Theory and Practice.

[4]  C. Redman,et al.  Reversed diurnal blood pressure rhythm in hypertensive pregnancies. , 1976, Clinical science and molecular medicine. Supplement.

[5]  E. Cauter,et al.  Problems in the statistical analysis of biological time series: The Cosinor test and the periodogram∗∗ , 1973 .

[6]  A Pedotti,et al.  Continuous vs intermittent blood pressure measurements in estimating 24-hour average blood pressure. , 1983, Hypertension.

[7]  A. J. Man in 't Veld,et al.  The Second Sir George Pickering Memorial Lecture What Regulates Whole Body Autoregulation? Clinical Observations , 1985, Journal of hypertension.

[8]  C. Guilleminault,et al.  Hemodynamics in sleep-induced apnea. Studies during wakefulness and sleep. , 1976, Annals of internal medicine.

[9]  Franz Halberg,et al.  Circadian System Phase — An Aspect of Temporal Morphology; Procedures and Illustrative Examples , 1967 .

[10]  F Halberg,et al.  Cardiovascular reference data base for recognizing circadian mesor- and amplitude-hypertension in apparently healthy men. , 1984, Chronobiologia.

[11]  B. Bagni,et al.  Circadian rhythms of atrial natriuretic peptide, renin, aldosterone, cortisol, blood pressure and heart rate in normal and hypertensive subjects. , 1990, Journal of hypertension.

[12]  Y. Imai,et al.  Altered circadian blood pressure rhythm in patients with Cushing's syndrome. , 1988, Hypertension.

[13]  J. Laragh,et al.  Blood pressure during normal daily activities, sleep, and exercise. Comparison of values in normal and hypertensive subjects. , 1982, JAMA.

[14]  F Halberg,et al.  Inferential statistical methods for estimating and comparing cosinor parameters. , 1982, Chronobiologia.

[15]  M. Knapp,et al.  Variations of bloodpressure in hypertensives during sleep. , 1963, Lancet.

[16]  E. K. Harris,et al.  Multivariate Interpretation of Clinical Laboratory Data , 1987 .

[17]  A Pedotti,et al.  Blood Pressure and Heart Rate Variabilities in Normotensive and Hypertensive Human Beings , 1983, Circulation research.