Estimating a cardiac age by means of heart rate variability.
A data set of R-R intervals recorded for at least 15 min in 141 healthy individuals of different ages and under two different conditions ("resting" and "tilted" states) has been considered. The data have been subjected to spectral analysis by fast Fourier transform methods and considered in view of the possibility to work out a model in which the chronological and cardiac age could be compared. Understanding the results was greatly facilitated by 1) working out a number of derived variables from the original ones to highlight the presence of small but conceptually important variability factors; 2) extraction of the principal components from the original as well as from the derived variables to exclude redundancies and correlation effects; and 3) automatic clustering of the subjects in age classes, which allowed removal of individual variability within each class. The main conclusion is that, within the examined individuals, cardiac and chronological ages do not match for ages higher than approximately 50 years; this could reflect the presence of subtle (and difficult-to-envisage) biases in the data analysis or a real discrepancy. The latter hypothesis should be confirmed by similar observations in different systemic contexts. The use of a simple equation relating chronological and cardiac age, derived from a careful regression analysis on our data set and of general use for screening purposes, is demonstrated.
Colosimo
A
A
Dipartimento Scienze Biochimiche, Università di Roma La Sapienza, Rome, Italy.
Giuliani
A
A
Mancini
A M
AM
Piccirillo
G
G
Marigliano
V
V
D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D000375:Aging / Q000502:physiology*; D000465:Algorithms; D005583:Fourier Analysis; D018475:Head-Down Tilt; D006321:Heart / Q000502:physiology*; D006339:Heart Rate / Q000502:physiology*; D006801:Humans; D008875:Middle Aged; D008955:Models, Cardiovascular; D012016:Reference Values; D012146:Rest