Objective: Ambulatory blood pressure monitoring (ABPM) data using values of
arbitrarily separated day- and nighttime hours are poorly reproducible, un
dermining the validity of this diagnostic tool. Previous studies from our g
roup have demonstrated that polynomial curves can be produced of ABPM data
from both normo- and hypertensive groups, and that these polynomial curves
are within the 95% confidence intervals of the data means. However, intra-i
ndividual reproducibility of this approach has not been assessed, and is an
important prerequisite for further implementing this approach.
Methods: Reproducibility was studied in 10 untreated mildly hypertensive pa
tients by performing 24 hour ABPM monitoring in each of them 2 times, inter
vals at least one week. ABPM monitoring was performed using validated Space
Lab Medical Inc portable equipments, polynomial regression analyses of the
systolic blood pressures using Harvard Graphics 3 as well as SPSS Statisti
cal Software. Polynomes were compared,vith the actual data as measured.
Results: Reproducibility of means of the population: Polynomes of duplicate
24 hour observations were not significantly different from each other (p=0
.44), The duplicate standard errors of the polynomes of the data were signi
ficantly better reproducible (P<0.001) than those of the actual data (1.86
mmHg and 15.9 mmHg, respectively). So was intra-class correlation (98.6% an
d 46%, respectively, P<0.001).
Reproducibility of the individual data: Duplicate standard errors of raw da
ta were generally more than twice the size of those of the polynomes, while
intraclass correlations of raw data were accordingly generally almost half
the size of those of the polynomes, Pooled differences were statistically
highly significant both for duplicate standard errors and for intraclass co
rrelations (P<0.001 and P=0.009, respectively).
Conclusions: Reproducibility of polynomial analysis of ABPM data is fundame
ntally better than that of actual data, and this is so not only with means
of populations but also with individual data. We assume that the difference
in reproducibility is due to the potential of polynomial analysis to remov
e exogenic components from the data and thus visualize the true endogenic c
ircadian rhythm of blood pressures.