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  • Küçük Resim
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    Identifying risk factors in a mostly overweight patient population with coronary artery disease
    (Angiology, 2003) Yoloğlu, Saim; Sezgin, Alpay Turan; Özdemir, Ramazan; Sezgin, Nurzen; Çolak, Cemil; Topal, Ergül; Barutçu, İrfan
    Overweight/obesity is a complex multifactorial chronic disorder, and the American Heart Association (AHA) has recently classified as a modifiable risk factor for coronary heart disease (CAD). This study (1) evaluates the association between CAD in a patient population mostly overweight (MOP) and conventional and novel coronary risk factors by using univariate and multivariate logistic regression analysis and (2) seeks to find the best model by comparing univariate and multivariate logistic regression analysis algorithms, which were systematically applied to risk factors by using Hosmer-Lemeshow statistic test. In univariate analysis, there were significant associations between CAD in MOP and conventional and novel risk factors. However, the model’s sensitivity, specificity, and accuracy levels were weak. In multivariate analysis, although some risk factors were not found as predictors of coronary artery disease, the model showed good fit to data and had high sensitivity, specificity, and accuracy levels. This was also confirmed by using the Hosmer-Lemeshow goodness of fit test, more specifically.
  • Küçük Resim
    Öğe
    Identifying risk factors in a mostly overweight patient population with coronary artery disease
    (Angiology, 2003) Yoloğlu, Saim; Sezgin, Alpay Turan; Özdemir, Ramazan; Sezgin, Nurzen; Çolak, Cemil; Topal, Ergül; Barutçu, İrfan
    Overweight/obesity is a complex multifactorial chronic disorder, and the American Heart Association (AHA) has recently classified as a modifiable risk factor for coronary heart disease (CAD). This study (1) evaluates the association between CAD in a patient population mostly overweight (MOP) and conventional and novel coronary risk factors by using univariate and multivariate logistic regression analysis and (2) seeks to find the best model by comparing univariate and multivariate logistic regression analysis algorithms, which were systematically applied to risk factors by using Hosmer-Lemeshow statistic test. In univariate analysis, there were significant associations between CAD in MOP and conventional and novel risk factors. However, the model’s sensitivity, specificity, and accuracy levels were weak. In multivariate analysis, although some risk factors were not found as predictors of coronary artery disease, the model showed good fit to data and had high sensitivity, specificity, and accuracy levels. This was also confirmed by using the Hosmer-Lemeshow goodness of fit test, more specifically.