Abstract
A five-year study was undertaken to develop a valid mathematical model that could aid in diagnosing acute ischemic heart disease in the emergency room, thus reducing inappropriate admissions to the coronary care unit. The study was divided into two substudies. In the first, variables significantly predictive of ischemic heart disease were identified and a logistic function was developed and tested. In the second, a six-hospital study, the variables of the first substudy were validated and a final logistic regression was developed and tested prospectively. This model's availability proved to be successful in improving diagnostic accuracy and specificity and in reducing false positive predictive rates and admissions to coronary care units.
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