1. Rat cardiovascular telemetry: Marginal distribution applied to positive control drugs
- Author
-
Samir Abtout, Alexis Ascah, Simon Authier, Eric Troncy, Said Maghezzi, and Michael V. Accardi
- Subjects
Male ,medicine.medical_specialty ,030204 cardiovascular system & hematology ,Contractility ,Toxicology ,030226 pharmacology & pharmacy ,PR ,Ventricular Function, Left ,Cloud analysis ,Body Temperature ,Cardiovascular Physiological Phenomena ,Rats, Sprague-Dawley ,Electrocardiography ,03 medical and health sciences ,0302 clinical medicine ,Heart Rate ,Internal medicine ,Heart rate ,Left ventricular ,Animals ,Telemetry ,Medicine ,Pharmacology ,medicine.diagnostic_test ,ECG ,business.industry ,Safety pharmacology ,QT ,Myocardial Contraction ,Electrodes, Implanted ,Rats ,Long QT Syndrome ,Blood pressure ,Data Interpretation, Statistical ,Ventricular pressure ,Cardiology ,Rat ,Safety ,Marginal distribution ,business - Abstract
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.
- Published
- 2016