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Objective: Extracorporeal shock wave lithotripsy (ESWL) is a safe and effective treatment for urinary tract calculi. While serious side effects are rare, transient cardiac arrhythmias may occur. New electrocardiographic (ECG) parameters, such as P wave dispersion (PWD), QT dispersion (QTd), T peak to T end (Tp-e) interval, Tp-e interval/QT ratio, and Tp-e interval/corrected QT ratio have been defined to help predict atrial and ventricular arrhythmias. However, effect of ESWL on these ECG parameters has not been previously investigated. The present study was an examination of the effect of ESWL on ECG parameters. Methods: Total of 40 consecutive patients who underwent ESWL were prospectively enrolled in the study. Pre-procedure ECG parameters were compared with post-procedure ECG parameters. Results: PWD values were significantly longer on post-procedure ECG compared with pre-procedure ECG (p=0.017). Corrected QT duration and QTd were significantly longer on post-procedure ECG compared with pre-procedure ECG (p=0.046 and p=0.008, respectively). In addition, Tp-e interval, Tp-e interval/QT ratio, and Tp-e interval/QTc ratio were significantly longer post procedure (p=0.035, p=0.045, and p=0.022, respectively). In univariate correlation analysis, duration of procedure was significantly correlated with post-procedure PWD, QTc, and QTD values. Conclusion: Clinical use of ECG parameters may be helpful in monitoring of patients receiving ungated ESWL in order to detect cardiac dysrhythmia.

Objectives: Previous studies have shown the association between various hematological parameters and cardiovascular diseases, and their prognostic value. In this study, we compared red cell distribution width (RDW), neutrophil lymphocyte ratio (NLR) and mean platelet volume (MPV) measurements among patients with poor coronary collateral circulation (CCC) and well-developed CCC. Study design: 326 patients with stable coronary artery disease (CAD) were evaluated retrospectively. CCC was graded by using the Rentrop classification. The poor CCC group included patients with Rentrop 0-1 CCC, and the good CCC group included Rentrop 2-3 CCC. Results: There were 171 subjects (84% male; mean age 56.6+-10.4 years) in the poor CCC group, and 155 subjects (89% male; mean age 57.6+-9.7 years) in the good CCC group. The total number of vessels with >95% stenosis (1.1+-0.5 vs. 1.0+-0.4; p=0.64) and Gensini scores (84.4+-38.8 vs. 83.3+-37.4; p=0.83) was not higher in the poor CCC group compared to the good CCC group. RDW was significantly higher in the poor CCC group compared to the good CCC group (14.19+-1.36% vs. 13.89+-1.19%; p=0.04). In multivariate logistic regression analysis, elevated levels of RDW and LDL were found to be independent predictors of poor CCC (OR 1.73, 95% CI: 1.30-2.29, p=0.01 and OR 1.01 95% CI 1.002-1.02; p=0.02, respectively). Conclusion: In the present study, poor CCC was found to be independently correlated with RDW, but not with any other hematological parameters in patients with stable CAD.

Objectives: It has been proposed that human platelet antigen- 1 (HPA-1) gene polymorphism is associated with coronary artery disease (CAD) and affects platelet function. We aimed to investigate the distribution of HPA gene polymorphism between angiographic CAD and a control group and the relation between HPA gene polymorphism and platelet aggregation. Study design: The study population consisted of 94 patients with angiographic CAD and 115 patients without angiographic CAD. Platelet aggregation was measured with impedance aggregometry on the fifth day of percutaneous coronary intervention (PCI). Platelet aggregation >480 AU*min was defined as the clopidogrel resistance group. Blood samples were obtained from all participants at discharge for investigating HPA- 1 gene polymorphism. Results: There was no significant difference in the distribution of HPA-1 gene polymorphism between the control and CAD groups (78.7% vs. 78.1% for A allele and 21.3% vs. 21.9% for B allele, p=NS). The analysis between groups with and without clopidogrel resistance revealed no significant difference in the distribution of HPA-1A and HPA-1B alleles between the groups (A allele 78.7% vs. 78.9% and B allele 21.3% vs. 21.1%, p=NS). In the CAD group, there were no significant differences in platelet aggregation between HPA-1A and HPA- 1B alleles (294+-240 vs. 259+-261 AU*min, p=NS). Conclusion: The distribution of HPA-1 gene polymorphism was not different in CAD patients compared to the control group. HPA-1 gene polymorphism was not associated with platelet aggregation or clopidogrel resistance assessed by impedance aggregometry in the CAD group.