Application of the Truncated Zero-Inflated Double Poisson for Determining of the Effecting Factors on the Number of Coronary Artery Stenosis

Background. Risk factors of coronary heart disease have been discussed in the literature; however, conventional statistical models are not appropriate when the outcome of interest is number of vessels with obstructive coronary artery disease. In this paper, a novel statistical model is discussed to investigate the risk factors of number of vessels with obstructive coronary artery disease. Methods. This cross-sectional study was conducted on 633 elderly cardiovascular patients at Ghaem Hospital, Mashhad, Iran from September 2011 to May 2013. Clinical outcome is number of vessels with obstructive coronary artery disease (=0, 1, 2, 3), and predictor variables are baseline demographics and clinical features. A right-truncated zero-inflated double Poisson regression model is performed which can accommodate both underdispersion and excess zeros in the outcome. The goodness-of-fit of the proposed model is compared with conventional regression models. Results. Out of 633 cardiovascular patients, 327 were male (51.7%). Mean age was ~65 & PLUSMN;7 years (for individuals with zero, one ,and two coronary artery stenosis) and ~66 & PLUSMN;7 years (for individuals with three coronary artery stenosis). BMI (0.04 & PLUSMN;0.01, p=0.011) and female gender (0.19 & PLUSMN;0.09, p=0.032) were significant associated with the count part of the model, and only BMI (-0.47 & PLUSMN;0.2, p=0.011) was significantly predictive of logit part of the model. The goodness-of-fit measurements indicate that the proposed model outperforms the conventional regression models. Conclusion. The proposal regression model shows a better fit compared to the standard regression analysis in modeling number of vessels with obstructive coronary artery disease. Hence, using truncated zero-inflated double Poisson regression model-as an alternative model-is advised to study the risk factors of number of involved vessels of coronary artery stenosis.

Automated summary

This paper investigates the risk factors of the number of vessels with obstructive coronary artery disease and proposes a novel statistical model. The study finds significant associations between BMI, gender, and the count of obstructive vessels. The proposed model demonstrates better goodness-of-fit compared to conventional regression models.