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Comparison of Different Regression Analyses for Identifying Risk Factors in Obese and Nonobese Patients With Coronary Artery Disease

Departments of Biostatistics, Faculty of Medicine Inonu University, Malatya

Alpay Turan Sezgin, MD

Department of Cardiology Faculty of Medicine Baskent University, Adana, Turkeyand

Nurzen Sezgin, MD

Department of Biochemistry, Faculty of Medicine, Baskent University, Adana, Turkey

Ertan Yetkin, MD

Department of Cardiology, Faculty of Medicine, Inonu University, Malatya

Ercument Olmez, MD

Department of Pharmacology, Faculty of Medicine, Inonu University, Malatya

This study was designed to assess conventional and novel risk factors in obese and nonobese patients with coronary artery disease (CAD) by using multivariate forward and univariate logistic regression analysis and to find the best model of analysis for identifying these risk factors. The study group consisted of 398 patients who consecutively underwent coronary angiography for the investigation of chest pain, except overweight patients. In univariate logistic regression analysis, high C-reactive protein and cigarette smoking were found to be the strongest variables in obese and nonobese patients with CAD, respectively. In multivariate forward logistic regression analysis, some risk factors were not found as predictors of CAD. Multivariate forward logistic regression analysis with the advantage of a high predictable ratio may be more useful for the analysis of risk factors in patients with CAD.

Angiology, Vol. 58, No. 5, 543-549 (2007)
DOI: 10.1177/0003319706291115


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