A strategy for finding the optimal deconvolution estimates for hormone secretory kinetics using AutoDecon.
AutoDecon is a fully automatic, multiparameter deconvolution procedure that can be used to estimate various hormone secretion kinetics. We propose a strategy based on the application of the corrected Akaike's information criterion to select the optimal deconvolution model from a class of candidates generated by applying different combinations of initializing values. Using simulated cortisol time series, we show that, particularly in cases of diminished hormone half-life, this approach can yield estimates that are closer to the true underlying secretion kinetics compared with the commonly used approach based on a single set of initializing values. However, although we provide proof of principle, more extensive elaboration and validation of this approach are necessary.
Department of Neurology, Leiden University Medical Center, 2300 RC Leiden, The Netherlands. n.a.aziz@lumc.nl
N Ahmad
NA
Aziz
Ferdinand
F
Roelfsema
Marijke
M
Frölich
Raymund A C
RA
Roos
Hanno
H
Pijl
D000465:Algorithms; D005260:Female; D006207:Half-Life; D006801:Humans; D006854:Hydrocortisone / Q000378:metabolism*; D007700:Kinetics; D008297:Male; D008954:Models, Biological; D013997:Time Factors
D006854:Hydrocortisone