Introduction:

epidemiological risk factors for coronary artery disease are closely related to the existence, evolution and complications of the disease.

Objective:

to design mathematical models predictive of coronary artery disease diagnosed by calcium score from epidemiological variables.

Methods:

a cross-sectional analytical study was carried out. The population consisted of 820 patients with chest pain and calcium score, the sample (246) was selected by simple random probability sampling. Logistic regression was employed from a logistic regression model (using the forward stepwise option) for each of the four coronary vessels, each model was fitted to the variables and those with coefficients significantly different from zero (p<0.05) were identified using the Wald statistic. We estimated the point Odd Ration and confidence intervals, performed internal validation and explored the performance through model discrimination with the analysis of the area under the curve and calibration through the Hosmer-Lemeshow Chi-square statistic.

Results:

the predominant age group was older than 60 years (61.4%), male sex (65.9%) and arterial hypertension (68.7%). The mathematical models for each coronary vessel exclude the variable age. The following are important predictors: diabetes and smoking. The internal validation technique supports the good performance of the mathematical models obtained.

Conclusion:

the result reinforces the need for predictive studies to ensure cardiovascular risk stratification by calcium score and epidemiological variables on which effective action should be taken to improve patient prognosis.

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