Insensitivity of noninvasive tests to detect coronary artery vasculopathy after heart transplant

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Abstract

Obstructive coronary artery vasculopathy can be a major problem after cardiac transplant. The use of noninvasive tests to detect coronary artery vasculopathy was studied in 73 consecutive patients after heart transplant. Angiographically or autopsyproved coronary artery disease was noted in 19 consecutive patients (26%) followed prospectively for 2.5 ± 1.3 years (mean ± standard deviation). Patients underwent yearly surveillance echocardiographic, rest/exercise-gated wall motion, oral dipyridamole thallium, ambulatory etectrocardiographic monitor and angiographic studies. Positive test results were defined by decrease in ejection fraction, wall motion abnormality, failure to increase ejection fraction, lack of systolic blood pressure increase, and ischemic ST changes at maximal exercise (or on ambulatory monitor). Wall motion abnormalities and depressed ejection fraction on echocardiography were also abnormal studies as were fixed or reversible perfusion defects on thallium scan. Angiograms were considered positive when 50% luminal narrowing was observed and autopsy coronary artery vasculopathy was defined as cross-sectional coronary obstruction ≥70%.

No procedure that was examined proved to be a sensitive noninvasive detector of heart transplant coronary artery vasculopathy. All except ambulatory electrocardiographic monitoring had positive predictive values <50%. Interestingly, of the techniques evaluated, echocardiography was most sensitive (53%). The poor predictive ability of noninvasive testing in this population may be due to the fact that these tests are designed to detect effects of ischemia rather than coronary obstruction alone. Use of these particular noninvasive modalities routinely after heart transplant to detect coronary artery vasculopathy should be reconsidered because of their low sensitivity and predictive value when used as a surveillance screen.

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    This study was supported, in part, by the Cullen Trust for Health Care, Houston, Texas. The computational assistance was provided by the CLINFO Project, and funded by Grant RR-0035, Division of Research Resources, National Institutes of Health, Bethesda, Maryland.

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