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The Concordance of Intraoperative Left Ventricular Wall-motion Abnormalities and Electrocardiographic S-T Segment Changes: Association with Outcome After Coronary Revascularization. Multicenter Study of Perioperative Ischemia (McSPI) Research Group

Overview
Journal Anesthesiology
Specialty Anesthesiology
Date 1998 May 14
PMID 9579503
Citations 12
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Abstract

Background: Transesophageal echocardiography (TEE) and Holter electrocardiography (ECG) are used to detect intraoperative ischemia during coronary artery bypass graft surgery (CABG). Concordance of these modalities and sensitivity as indicators of adverse perioperative cardiac outcomes are poorly defined. The authors tried to determine whether routine use of Holter ECG and TEE in patients with CABGs has clinical value in identifying those patients in whom myocardial infarction (MI) is likely to develop.

Methods: A total of 351 patients with CABG and both ECG- and TEE-evaluable data were examined for the occurrence of ischemia and infarction. The TEE and five-lead Holter ECGs were performed continuously during cardiac surgery. The incidence of MI (creatine kinase-MB > or = 100 ng/ml) within 12 h of arrival in the intensive care [ICU] unit, new ECG Q wave on ICU admission or on the morning of postoperative day 1, or both, were recorded.

Results: Electrocardiographic or TEE evidence of intraoperative ischemia was present in 126 (36%) patients. The concordance between modalities was poor (positive concordance = 17%; Kappa statistic = 0.13). Myocardial infarction occurred in 62 (17%) patients, and 32 (52%) of them had previous intraoperative ischemia. Of these, 28 (88%) were identified by TEE, whereas 13 (41%) were identified by ECG. Prediction of MI was greater for TEE compared with ECG.

Conclusions: Wall-motion abnormalities detected by TEE are more common than S-T segment changes detected by ECG, and concordance between the two modalities is low. One half of patients with MI had preceding ECG or TEE ischemia. Logistic regression revealed that TEE is twice as predictive as ECG in identifying patients who have MI.

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