Euan Ashley1, Jonathan Myers, Victor Froelicher. 1. Cardiology Division (111C), Veterans Affairs Palo Alto Health Care System, Stanford University, 3801 Miranda Avenue, Palo Alto, CA 94304, USA.
Abstract
INTRODUCTION: The application of common statistical techniques to clinical and exercise test data has the potential to become a useful tool for assisting in the diagnosis of coronary artery disease, assessing prognosis, and reducing the cost of evaluating patients with suspected coronary disease. Since general practitioners function as gatekeepers and decide which patients must be referred to the cardiologist, they need to optimally use the basic tools they have available (i.e., history, physical exam, and the exercise test). METHODS: Review of the literature with a focus on the scientific techniques for aiding the decision-making process. RESULTS: Scores derived from multivariable statistical techniques considering clinical and exercise data have demonstrated superior discriminating power when compared using receiver-operating-characteristic curves with the ST segment response. In addition, by stratifying patients as to probability of disease and prognosis, they provide a management strategy. While computers as part of information management systems can calculate complicated equations to provide scores, physicians are reluctant to trust them. Thus, these scores have been represented as nomograms or simple additive tables so physicians are comfortable with their application. Scores have also been compared with physician judgment and been found to estimate the presence of coronary disease and prognosis as well as expert cardiologists, and often better than nonspecialists. CONCLUSION: Multivariate scores can empower the clinician to assure the cardiac patient with access to appropriate and cost-effective cardiological care.
INTRODUCTION: The application of common statistical techniques to clinical and exercise test data has the potential to become a useful tool for assisting in the diagnosis of coronary artery disease, assessing prognosis, and reducing the cost of evaluating patients with suspected coronary disease. Since general practitioners function as gatekeepers and decide which patients must be referred to the cardiologist, they need to optimally use the basic tools they have available (i.e., history, physical exam, and the exercise test). METHODS: Review of the literature with a focus on the scientific techniques for aiding the decision-making process. RESULTS: Scores derived from multivariable statistical techniques considering clinical and exercise data have demonstrated superior discriminating power when compared using receiver-operating-characteristic curves with the ST segment response. In addition, by stratifying patients as to probability of disease and prognosis, they provide a management strategy. While computers as part of information management systems can calculate complicated equations to provide scores, physicians are reluctant to trust them. Thus, these scores have been represented as nomograms or simple additive tables so physicians are comfortable with their application. Scores have also been compared with physician judgment and been found to estimate the presence of coronary disease and prognosis as well as expert cardiologists, and often better than nonspecialists. CONCLUSION: Multivariate scores can empower the clinician to assure the cardiac patient with access to appropriate and cost-effective cardiological care.
Authors: Jonathan Myers; Ricardo Oliveira; Frederick Dewey; Ross Arena; Marco Guazzi; Paul Chase; Daniel Bensimhon; Mary Ann Peberdy; Euan Ashley; Erin West; Lawrence P Cahalin; Daniel E Forman Journal: Circ Heart Fail Date: 2013-02-07 Impact factor: 8.790
Authors: Jonathan Myers; Ross Arena; Ricardo B Oliveira; Daniel Bensimhon; Leon Hsu; Paul Chase; Marco Guazzi; Peter Brubaker; Brian Moore; Dalane Kitzman; Mary Ann Peberdy Journal: J Card Fail Date: 2009-07-03 Impact factor: 5.712