In order to identify patients with severe coronary artery disease (CAD) and at a higher risk of future cardiac events after uncomplicated myocardial infarction, 105 consecutive patients were studied prospectively. There were 93 men and 12 women with a mean age of 56 +/- 8.2 years. Treadmill testing, exercise radionuclide ventriculography, thallium-201 myocardial imaging and selective coronary arteriography were performed 6-8 weeks after infarction. Patients were grouped into those who had single and multiple vessel disease. Multiple regression analysis of 18 noninvasive indices was carried out using generalized linear interactive modelling (GLIM) and the results were compared with the severity of underlying CAD and the clinical outcome after a mean follow-up period of 18.8 +/- 3. 4 months. At the end of the follow-up period, patients were categorized into those who had no cardiac events, minor and major cardiac events. Multivariate analysis produced an algorithm from three factors found to be most predictive of the severity of CAD. These included ST-segment depression on exercise, total score of rest and exercise regional wall motion and the presence of significant redistribution on thallium-201 imaging. The sensitivity of this algorithm for predicting multiple vessel disease was 42%, with a specificity of 94%, and a predictive accuracy of 69%. However, the total score of regional wall motion abnormalities was the single most predictive factor of major cardiac events with a sensitivity of 94%, a specificity of 57%, and predictive accuracy of 63%. None of the other factors produced additional prognostic information. Therefore, exercise radionuclide ventriculography appears to be the investigation of choice in assessing prognosis after myocardial infarction.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:234489 |
| Date | January 1988 |
| Creators | Al-Khawaja, Imad Mahmoud Shihadeh |
| Publisher | University of Surrey |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://epubs.surrey.ac.uk/847183/ |
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