Abstract 2011: A Simple Nomogram to Predict the Probability of Successful Reperfusion with Pre-Hospital Thrombolysis

Abstract

In ST-elevation myocardial infarction (STEMI), coronary recanalisation is a prerequisite for deriving benefit from thrombolysis, but achieving myocardial reperfusion is also key to benefit. Data regarding the impact of thrombolysis on myocardial reperfusion are scarcer than for recanalisation, especially when pre-hospital thrombolysis is considered. To develop a nomogram for predicting myocardial reperfusion after pre-hospital thrombolysis. In 2004 – 05, 800 consecutive French patients with STEMI received pre-hospital thrombolysis within 6 hours of symptom onset (median delay of 110 minutes). The assessment of myocardial reperfusion was based on the measurement of ST resolution (STR) between a first electrocardiogram (ECG), recorded before thrombolysis, and a second one in the cath laboratory. Myocardial reperfusion was assessed when STR was 70%, at least, in the single lead with the greatest baseline ST-elevation. The sample comprised 18% of women and median age was 59. The median delay between the two ECGs was 110 minutes. The proportion of patients who achieved STR was 42%. The nomogram was based on the variables that were independently associated with STR in multivariate logistic regression analysis. For instance, a non-obese smoker patient, with a non-anterior STEMI and a maximum ST-elevation of 2 mm, for whom thrombolysis is possible within 1 hour of symptom onset, together with the administration of a thienopyridine, but no IV nitrates, has a probability of 0.87 to achieve STR. If thrombolysis is delayed after one hour, without thienopyridine administration, in case of anterior STEMI, the probability declines to 0.50. The probabilities of STR for the different situations covered by the nomogram range from 0.10 to 0.87. This nomogram, developed in a “real world” setting, is designed to predict a priori the probability of myocardial reperfusion following thrombolysis, based on simple clinical and electrocardiographic data.