Anthony McClelland | PubMed Health

PubMed2005

Improved detection of acute myocardial infarction using a diagnostic algorithm based on calculated epicardial potentials.

BACKGROUND: New methods for detecting myocardial infarction in patients with suspected acute coronary syndromes are needed particularly in an era where the majority of patients with myocardial infarction present with non-diagnostic 12-lead electrocardiograms (ECG). We compared a novel epicardial diagnostic algorithm using epicardial potentials from the 80-lead body surface map with other electrocardiographic techniques in detection of myocardial infarction. METHODS: Between February 1999 and February 2001, consecutive patients (n=427) with ischemic type chest pain had an initial 12-lead ECG and body surface map recorded. Detecting myocardial infarction using an epicardial algorithm was first performed in a training set (n=213) and tested in a validation set of patients (n=214). The results from this epicardial algorithm in myocardial infarction detection were compared with the physician's interpretation of the 12-lead ECG, the body surface map algorithm (PRIME) and physician's interpretation of the body surface map. RESULTS: Myocardial infarction occurred in 205 patients (creatine kinase >or=2x upper limit of normal with creatine kinase-MB >or=7% CK). The physician's interpretation of the 12-lead ECG identified 122 with myocardial infarction (sensitivity 60%, specificity 99%), the body surface map algorithm 137 (sensitivity 67%, specificity 89%), the physician's interpretation of the body surface map 153 (sensitivity 75%, specificity 91%) and the epicardial algorithm 158 (sensitivity 77% specificity 99%). Combining the physician's interpretation of the 12-lead ECG with the epicardial algorithm increased significantly the detection of myocardial infarction (sensitivity 85%, specificity 98%, p<0.001) compared with the 12-lead ECG. CONCLUSIONS: An epicardial algorithm based on epicardial potentials increases significantly the detection of myocardial infarction particularly among those with non-diagnostic 12-lead ECG's.

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PubMed2003

The use of calculated epicardial potentials improves significantly the sensitivity of a diagnostic algorithm in the detection of acute myocardial infarction.

Inverse electrocardiography can calculate epicardial potentials (EP) from body surface potentials (BSP) taking into account a thoracic volume conductor model (TVCM). Previous studies have shown that a tailored TVCM is superior to a general TVCM in calculating EP. However, construction of a tailored TVCM for a patient in an acute clinical setting is impractical. In this study we used a general TVCM in our EP calculations to determine whether this improves detection of acute myocardial infarction (AMI) using a diagnostic algorithm. BSP were derived from the 80-lead body surface map (BSM). Consecutive patients (n=379) with ischemic type chest pain were recruited. The BSM and a 12-lead electrocardiogram (ECG) were recorded at initial presentation and creatine kinase (CK) and/or CK-MB were measured initially, 12 and 24 hours postsymptom onset. A physician interpreted the 12-lead electrocardiogram and documented ST elevation if present. AMI was defined by the World Health Organization (WHO) criteria. The diagnostic algorithm result for each patient using BSP and calculated EP were documented. AMI occurred in 171 patients. The diagnostic algorithm using BSP identified 106 of these as ST elevation AMI (STEMI) (sensitivity 62%, specificity 80%). The same algorithm using EP identified 133 as STEMI (sensitivity 78%, specificity 80%). Calculated EP improved the algorithm's diagnostic sensitivity by a factor of 1.25 (P<.001) with no significant difference in specificity. Calculated EP using a general TVCM significantly improves the sensitivity of a diagnostic algorithm based on BSP in detection of AMI with no significant loss in specificity.

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