Performance of an automated real-time ST-segment analysis program to detect coronary occlusion and reperfusion.

Abstract:

:Continuously updated ST-segment recovery analysis has been shown to accurately predict infarct-related artery patency. Salient principles were converted into algorithms and incorporated into a portable ST monitor for optimal application. This study tested the automated program's ability to detect occlusion and reperfusion during balloon angioplasty. ST-segment recordings during 78 balloon occlusions in 31 patients were analyzed. The program requires at least one electrocardiogram with ST elevation of 200 microV or greater in the recording, caused by the current occlusion or by a previous occlusion, before it will yield a patency prediction. All 35 inflations causing peak ST elevation of 200 microV or more were indeed detected. All five inflations causing less than 200 microV ST elevation preceded by an inflation causing 200 microV or higher ST elevation were also detected. Occlusion was detected a median of 40 seconds after inflation, and reperfusion a median of 17 seconds after deflation. Peak ST elevation greater than 200 microV occurred in 19 of 26 left anterior descending artery inflations (73%), 1 of 22 left circumflex artery LCX inflations (5%), and 15 of 30 right coronary artery inflations (50%). Five different leads identified peak ST elevation through 12-lead surveillance. In this model of coronary occlusion during angioplasty balloon inflation, the automated patency assessment program appears to detect coronary angioplasty balloon occlusion and reperfusion within seconds in all occlusions causing a peak ST elevation of 200 microV or greater. Testing this automated patency assessment program as a noninvasive triage tool in myocardial infarction patients seems warranted.

journal_name

J Electrocardiol

authors

Veldkamp RF,Sawchak S,Pope JE,Califf RM,Krucoff MW

doi

10.1016/s0022-0736(96)80090-2

subject

Has Abstract

pub_date

1996-10-01 00:00:00

pages

257-63

issue

4

eissn

0022-0736

issn

1532-8430

journal_volume

29

pub_type

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