Study of relationship between volume of distribution and body weight application to amikacin

Amikacin use is difficult because of its narrow therapeutic and its pharmacokinetic variability. This variability of amikacin is not well known. To adapt amikacin the physician assumes that there is a linear and continuous relation between the volume of distribution and the body weight. The objectiv...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:European journal of drug metabolism and pharmacokinetics 2014-06, Vol.39 (2), p.87-91
Hauptverfasser: Rughoo, L., Bourguignon, L., Maire, P., Ducher, M.
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:Amikacin use is difficult because of its narrow therapeutic and its pharmacokinetic variability. This variability of amikacin is not well known. To adapt amikacin the physician assumes that there is a linear and continuous relation between the volume of distribution and the body weight. The objective of our study was to evaluate the relationship between the volume of distribution (Vd) and the body weight (BW) using a non parametric statistical analysis of dependence so called Z method. Retrospective pharmacokinetic population study and statistic analysis. 872 patients receiving intravenous amikacin. The volume of distribution was modelled using the Non Parametric Adaptive Grid algorithm (NPAG) for a two-compartment model with intravenous infusion. Z coefficient was performed to evaluate the relationships between Vd and BW. For the 872 patients (mean age of 73 ± 17 years) dispatched as follow 53 % female and 47 % male, the analysis of the statistical relationships by the non parametric Z analysis showed a scattered linkage between Vd and BW. For the whole population, the relationship between Vd and BW was not linear (regression analysis). Z analysis demonstrated that only for 80 % of patients there is a relationship between Vd and BW. For these patients, regression analysis give a significant adjustment of a linear model ( r  = 0.47, p  
ISSN:0378-7966
2107-0180
DOI:10.1007/s13318-013-0160-y