摘要：

Receiver operating characteristic analysis (ROC) evaluates continuous variables to define diagnostic criteria for the optimal sensitivity (SENS) and specificity (SPEC) of a test. The authors studied exercise-induced chest pain (CP), ST-changes on electrocardiography (ECG) and rest-exercise gated radionuclide ventriculography (RVG) using ROC to clarify the optimal criteria for detecting myocardial ischemia due to coronary artherosclerosis (CAD). The data of 95 consecutive patients studied with coronary angiography, rest-exercise RVG and ECG were reviewed. 77 patients had ''significant'' CAD (≥50% lesions). Exercise-induced CP, ECG abnormalities (ST-T shifts) and RVG abnormalities (change in ejection fraction, 2-view regional wall motion change and relative end-systolic volume) were evaluated to define optimal SENS/SPEC of each and for the combined data. ROC curves were constructed by multiple logistic regression (MLR). By MLR, RVG alone was superior to ECG and CP. The combination of all three produced the best ROC curve for the entire group and for clinical subsets based on the number of diseased vessels and the presence or absence of prior myocardial infarction. When CP, ECG and RVG were combined, the optimal SENS/SPEC for detection of single vessel disease was 88/86. The SENS/SPEC for 3 vessel disease was 93/95. Thus, the application of RVG for the diagnosis of myocardial ischemia is improved with the inclusion of ECG and CP data by the use of a multiple logistic regression model. ROC analysis allows clinical application of multiple data for diagnosing CAD at desired SENS/SPEC rather than by arbitrary single-standard criteria

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