Assessing patients with possible heart disease using scores

Multivariable analysis of 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 are functionin g as gatekeepers and decide which patients must be referred to the cardiolo gist, they need to use the basic tools they have available (i.e. history, p hysical examination and the exercise test), in an optimal fashion. Scores d erived from multivariable statistical techniques considering clinical and e xercise data have demonstrated superior discriminating power compared with simple classification of the ST response. In addition, by stratifying patie nts as to probability of disease and prognosis, they provide a management s trategy. While computers, as part of information management systems, can ru n complicated equations and derive these scores, physicians are reluctant t o trust them. Thus, these scores have been represented as nomograms or simp le additive tables so physicians are comfortable with their application. Th eir results have also been compared with physician judgment and found to es timate the presence of coronary disease and prognosis as well as expert car diologists and often better than nonspecialists. However, the discriminating power of specific variables from the medical hi story and exercise test remains unclear because of inadequate study design and differences in study populations. Should expired gases be substituted f or estimated metabolic equivalents (METs)? Should ST/heart rate (HR) index be used instead of putting these measurements separately into the models? S hould right-sided chest leads and HR in recovery be considered? There is a need for further evaluation of these routinely obtained variables to improv e the accuracy of prediction algorithms especially in women. The portabilit y and reliability of these equations must be demonstrated since access to s pecialised care must be safeguarded. Hopefully, sequential assessment of th e clinical and exercise test data and application of the newer generation o f multivariable equations can empower the clinician to assure the cardiac p atient access to appropriate and cost-effective cardiological care.