Increased plasma lipoprotein-associated phospholipase A2 (Lp-PLA2) levels are related to good collateral development in patients with isolated left coronary artery disease

Örem, Cihan; Kahraman, Nuray; Örem, Asım; Ucar, Utku; Yucesan, Fulya Balaban; Menteşe, Ahmet

doi:10.1016/j.ijcard.2011.01.051

Cited by 2 publications

(1 citation statement)

References 21 publications

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“…The value of a well-developed CC to predict the prognosis in patients with CHD, have been leading the researchers to examine the demographic and biochemical determinants of CCC. Previous studies found a positive correlation between a well-developed CC and male gender, smoking, hyperlipidemia, calcium channel blocker usage, statin usage, higher serum CRP and lipoprotein associated phospholipase A2 level, paraoxanase activity and asymmetric dimethylarginine level [9][10][11][12][13][14]. On the other hand, diabetes mellitus demonstrates a relation to poor Coronary Collateral Development (CCD) [11].…”

Section: Introductionmentioning

confidence: 98%

Predictors of Well Developed Coronary Collateral Circulation in Patients with Stable Angina Pectoris

Akgüllü¹,

EryÄ±lmaz²,

Ok³

et al. 2014

J Clin Exp Cardiolog

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Objective: We aimed to demonstrate the predictors of Coronary Collateral Development (CCD) in patients with Stable Angina Pectoris (SAP). Methods: We prospectively enrolled 52 patients with at least 90% coronary stenosis. Their demographic, anthropometric and clinical data as well as hematological and biochemical parameters, medications, Ejection Fraction (EF) and perfusion index values and angiographic findings were used for determining the predictors for CCD. The Rentrop score (between 0 and 3) was used for the angiographic categorization and patients in Rentrop grades 0 and 1 were classified as poor CCD, and patients in Rentrop grades 2 and 3 were classified as well CCD. Results: We found moderate negative correlation between the Rentrop score and ejection fraction (r=-0,469, p<0.001). There was also positive correlation between the Gensini score (GS) and the Rentrop score (r=0.627, p<0.001). We made Classification and Regression Tree Model (C&RT) to define best predictors of CCD and found that EF (cut off 55%) and GS (cut off 41%) together constitute a useful prediction algorithm. Furthermore an advanced research was conducted to develop another algorithm to forecast coronary collateral development prior to angiography. The analysis was repeated after the extraction of angiographic data from the first C&RT model. It was concluded that EF (cut off 55%) and mean platelet volume (MPV) (cut off 9 fl) can be used in the second algorithm. Conclusions: CCD is negatively related to EF and positively related to GS. EF and MPV together constitute a simple and cost effective algorithm to predict the CCD before the angiography. However, GS and EF seem to be the best predictors of CCD among the whole variables.

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