Simple treadmill score to diagnose coronary disease.

Area of Science:

• Cardiology
• Diagnostic Tools
• Medical Informatics

Background:

• Current guidelines recommend multivariable equations for treadmill test interpretation.
• Existing equations often involve complex statistical methods.
• Simplified scores exist for prognosis but not specifically for CAD diagnosis via exercise tests.

Purpose of the Study:

• To develop and validate a simplified treadmill score for predicting coronary artery disease (CAD).
• To create an accessible tool for estimating CAD probability from exercise test results.

Main Methods:

• A logistic regression model was used to identify predictors of significant CAD from treadmill test data.
• A simplified scoring system was derived using key variables: heart rate, ST-segment depression, age, angina, hypercholesterolemia, diabetes, and treadmill angina index.
• The score ranged from 6 to 95, categorizing patients into low (<40), intermediate (40-60), and high (>60) probability groups for CAD.

Main Results:

• The simplified score demonstrated superior diagnostic accuracy (AUC 0.79) compared to ST-segment response alone (AUC 0.67).
• Prevalence of significant CAD varied across probability groups: low (22-27%), intermediate (58-62%), and high (92%).
• The score improved patient classification by 7% over ST-segment criteria and achieved 88% sensitivity and 96% specificity.

Conclusions:

• The simplified exercise score is a practical and validated method for estimating CAD probability.
• Its ease of use without a calculator makes it valuable for physicians managing chest pain evaluations.
• This tool can significantly aid in the clinical management of patients suspected of having CAD.