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Performance of Diagnostic Tests for Intermediate Probabilities of Coronary Heart Disease: A Decision Making Analysis

Abstract

Patients with intermediate probability of coronary disease are a diagnostic challenge and it is precisely in this population where the degree of uncertainty is greater that the diagnostic tests have their greater applicability. However, according to the current definition, subjecting to tests a population with a disease probability between 10 and 90% can generate unnecessary tests and misleading results. Knowing the characteristics of each test, as well as risks and benefits of drug treatment for coronary disease and combining this information through diagnostic thresholds brings a new perspective to decision making. To review the origin of the currently recommended concepts of intermediate probability and to determine the thresholds for diagnosis and treatment of noninvasive tests and, based on them, propose a new concept of intermediate probability of coronary disease. Through the bibliographic review, meta-analyses were extracted in which data of sensitivity, specificity, positive and negative likelihood ratio, risks and benefits of the tests and treatment were provided. Using an algorithm developed by Pauker et al. it was possible to obtain the diagnostic and treatment thresholds adjusted for each tests in question. The concept of intermediate probability of coronary disease is quite broad, ranging, according to the authors, between 10 and 90%, 1 and 92%, 15 and 85%, with different rationale. Considering the discriminatory power of each test, risks and treatment benefits, the diagnostic and treatment thresholds were defined for exercise testing (22-58%), eco-stress (10-72%), myocardial scintigraphy (12-80%), nuclear magnetic resonance (16-80%) and coronary angiotomography (6.7-81%). The decision to submit to diagnostic tests should be individualized, taking into account the diagnostic and treatment thresholds of each method in question.

Keywords:
Coronary Artery Disease; Probability; Clinical Decision-Making; Diagnosis; Meta-Analysis

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