Rat cardiovascular telemetry: Marginal distribution applied to positive control drugs

Cardiovascular effects are considered frequent during drug safety testing. This investigation aimed to characterize the pharmacological response of the conscious telemetered rat in vivo model to known cardiovascular active agents. These effects were analyzed using statistical analysis and cloud repr...

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Bibliographic Details
Published in:Journal of pharmacological and toxicological methods 2016-09, Vol.81, p.120-127
Main Authors: Accardi, M.V., Troncy, E., Abtout, S., Ascah, A., Maghezzi, S., Authier, S.
Format: Article
Language:English
Subjects:
Animals
Body Temperature - drug effects
Cardiovascular Physiological Phenomena - drug effects
Cloud analysis
Contractility
Data Interpretation, Statistical
ECG
Electrocardiography - drug effects
Electrodes, Implanted
Heart Rate - drug effects
Left ventricular
Long QT Syndrome - chemically induced
Long QT Syndrome - physiopathology
Male
Myocardial Contraction - drug effects
Rat
Rats
Rats, Sprague-Dawley
Safety
Telemetry
Telemetry - methods
Ventricular Function, Left - drug effects
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Summary:Cardiovascular effects are considered frequent during drug safety testing. This investigation aimed to characterize the pharmacological response of the conscious telemetered rat in vivo model to known cardiovascular active agents. These effects were analyzed using statistical analysis and cloud representation with marginal distribution curves for the contractility index and heart rate as to assess the effect relationship between cardiac variables. Arterial blood pressure, left ventricular pressure, electrocardiogram and body temperature were monitored. The application of data cloud with marginal distribution curves to heart rate and contractility index provided an interesting tactic during the interpretation of drug-induced changes particularly during selective time resolution (i.e. marginal distribution curves restricted to Tmax). Taken together, the present data suggests that marginal distribution curves can be a valuable interpretation strategy when using the rat cardiovascular telemetry model to detect drug-induced cardiovascular effects. Marginal distribution curves could also be considered during the interpretation of other inter-dependent parameters in safety pharmacology studies.
ISSN:1056-8719
1873-488X
DOI:10.1016/j.vascn.2016.03.005