Determinants of infarct size in non-human primates.
To achieve a better understanding of the major factors that determine infarct size in non-human primates, a mathematical model was constructed using stepwise regression analysis. The model was developed on the basis of infarct size measurements, including the anatomical area at risk, regional myocardial blood flow measurements and hemodynamic determinants obtained in 23 control baboons undergoing up to 2 h of coronary artery thrombosis followed by thrombolysis. In this model, the size of the perfusion bed of the occluded coronary artery and the duration of coronary artery occlusion were found to be the only important predictors of infarct size (expressed as a percentage of left ventricular mass). R2 (square or the multiple correlation coefficient) was 70% in this model. Collateral blood flow and rate-pressure product were not identified as important predictors of infarct size. In a second group of eight baboons, atenolol (0.1 mg.kg-1) was administered intravenously 15 min after the onset of coronary artery thrombosis. Predicted infarct size (based on the mathematical model obtained in the control group) was larger than the observed infarct size in seven out of eight cases. In four instances observed infarct size was smaller than the 95% lower limit of the predicted value. It is concluded that the determinants of infarct size in non-human primates differ from those in canine models with respect to collateral flow and estimates of myocardial oxygen consumption (rate pressure product). The developed mathematical model of infarct size prediction allows the detection of cardioprotective drug effects with an acceptable efficacy.
Flameng
W
W
Department of Experimental Cardiac Surgery, Catholic University Leuven, Belgium.
Lesaffre
E
E
Vanhaecke
J
J
D000818:Animals; D003326:Coronary Circulation; D005544:Forecasting; D006439:Hemodynamics; D009203:Myocardial Infarction / Q000473:pathology* / Q000503:physiopathology; D010215:Papio; D012044:Regression Analysis; D012307:Risk Factors