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    Immunohistochemical evaluation of the effects of nebivolol on intimal hyperplasia following endothelial injury
    (Tubitak Scientific & Technological Research Council Turkey, 2011) Akar, Ilker; Rahman, Ali; Colak, M. Cengiz; Ustundag, Bilal; Ozercan, Ibrahim Hanifi; Uysal, Ayhan
    Aim: Intimal hyperplasia is a vascular remodeling process. It is a clinical problem that forms in the vascular wall as a result of smooth muscle cell migration, proliferation, and extracellular matrix accumulation. In this study we examined the immunohistochemical evaluation of the effects of nebivolol on intimal hyperplasia in damaged endothelial tissue. Materials and methods: The study was conducted using 21 rabbits equally divided into 3 groups: control, solvent, and nebivolol. The rabbits in the control group only underwent balloon injury of the abdominal aorta. The rabbits in the solvent group and nebivolol group underwent balloon injury and were treated with solvent and nebivolol intraperitoneally during the study. At the end of the study, the abdominal aortas were harvested. The intimal and medial areas were measured and the intima/media ratios were calculated. Tissue nitric oxide levels were determined and immunohistochemical findings were evaluated. Results: Statistically there were no differences between the control and solvent groups with respect to the intimal and medial areas, intima/media ratios, or the tissue nitric oxide (NO) levels. The neointimal thickening was significantly less in the nebivolol group than in the control and solvent groups (P < 0.001). Intima/media ratio was decreased in the nebivolol group (P < 0.001). Tissue nitric oxide levels were greater in the nebivolol group than in the control and solvent groups (P < 0.01). Immunohistochemical data in the nebivolol group were significantly lower as compared with the other groups (P < 0.05). Conclusion: Nebivolol may be a useful agent in early restenosis after vascular reconstructive procedures.
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    An intelligent system for the classification of postoperative pleural effusion between 4 and 30 days using medical knowledge discovery.
    (Allied Acad, 2017) Guldogan, Emek; Arslan, Ahmet Kadir; Colak, M. Cengiz; Colak, Cemil; Erdil, Nevzat
    Objective: Pleural Effusion (PE) is a considerable and a common health problem. The classification of this condition is of great importance in terms of clinical decision making. The purpose of the study is to design an intelligent system for the classification of postoperative pleural effusion between 4 and 30 days after surgery by medical knowledge discovery (MKD) methods. Materials and methods: This study included 2309 individuals diagnosed with coronary artery disease for elective coronary artery bypass grafting (CABG) operation. The results of chest x-ray were used to diagnose PE. The subjects were allocated to two groups: PE group (n=81) and non-PE group (n=2228), consecutively. In the preprocessing step, outlier analysis, data transformation and feature selection processes were performed. In the data mining step, Naive Bayes, Bayesian network and Random Forest algorithms were utilized. Accuracy and area under receiver operating characteristics (ROC) curve (AUC) were calculated as evaluation metrics. Results: In the preprocessing step, 85 outlier observations were removed from the study. The rest of the data consisted of 2224 subjects: 2149 of these individuals were in non-PE group, and the 75 were in PE group. Random Forest yielded the best classification performance with 97.45% of accuracy and 0.990 of AUC for 0.7 of the optimal split ratio by Grid search algorithm. Conclusion: The achieved results pointed out that the best classification performance was obtained from the RF ensemble model. Therefore, the suggested intelligent system can be used as a clinical decision making tool.
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    An intelligent system for the classification of postoperative pleural effusion between 4 and 30 daysusing medical knowledge discovery.
    (Scıentıfıc publıshers ındıa, 87-greater azad enclave, p o quarsı, alıgarh, 00000, ındıa, 2017) Guldogan, Emek; Arslan, Ahmet Kadir; Colak, M. Cengiz; Colak, Cemil; Erdil, Nevzat
    Objective: Pleural Effusion (PE) is a considerable and a common health problem. The classification of this condition is of great importance in terms of clinical decision making. The purpose of the study is to design an intelligent system for the classification of postoperative pleural effusion between 4 and 30 days after surgery by medical knowledge discovery (MKD) methods. Materials and methods: This study included 2309 individuals diagnosed with coronary artery disease for elective coronary artery bypass grafting (CABG) operation. The results of chest x-ray were used to diagnose PE. The subjects were allocated to two groups: PE group (n=81) and non-PE group (n=2228), consecutively. In the preprocessing step, outlier analysis, data transformation and feature selection processes were performed. In the data mining step, Naive Bayes, Bayesian network and Random Forest algorithms were utilized. Accuracy and area under receiver operating characteristics (ROC) curve (AUC) were calculated as evaluation metrics. Results: In the preprocessing step, 85 outlier observations were removed from the study. The rest of the data consisted of 2224 subjects: 2149 of these individuals were in non-PE group, and the 75 were in PE group. Random Forest yielded the best classification performance with 97.45% of accuracy and 0.990 of AUC for 0.7 of the optimal split ratio by Grid search algorithm. Conclusion: The achieved results pointed out that the best classification performance was obtained from the RF ensemble model. Therefore, the suggested intelligent system can be used as a clinical decision making tool.
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    Perioperative High-Dose Amiodarone Elevates Nitric Oxide Levels in Patients Undergoing Coronary Artery Bypass Surgery.
    (Allied Acad, 2013) Uysal, Ayhan; Azak, Soner; Colak, M. Cengiz; Burma, Oktay; Ozguler, I. Murat; Ustundag, Bilal; Bayar, Mustafa Kemal
    The aim of the current study was to assess the effects of the Class III antiarrhythmic drug amiodarone on arterial blood Nitric oxide (NO) levels together with malondialdehyde (MDA), superoxide dismutase (SOD), glutathione peroxidase (GSH-px), and catalase (CAT) levels in patients undergoing coronary artery bypass surgery (CABG). Twenty patients undergoing CABG were included in the study. The patients were divided into control and amiodarone groups (n=10 in each group). The patients in group 1 did not receive any drugs. The patients in group II received 4X400 mg/day amiodarone on the day before surgery, 2X600 mg/day amiodarone on the day of surgery, and 2X400 mg/day amiodarone for the first consecutive four days after the surgery. NO, MDA, SOD, GSH-px, and CAT values were measured for biochemical evaluation of oxidative stress before the induction of anesthesia (T-A), before CPB (T-CPB), five minutes after the clamp was removed (T-c), after protamine (T-P), and on postoperative days 1 (T-1), 3 (T-3), and 5 (T-5). Hemodynamic changes of all patients were recorded at before the induction of anesthesia (TA), before CPB (TCPB), after protamine (T-P), and on postoperative day 1 (T1). Amiodarone elevated NO levels at all times during the study period but did not cause changes in MDA, SOD, GSH-px, or CAT. In addition, amiodarone decreased mean pulmonary artery pressure, pulmonary capillary wedge pressure, and heart rate in these patients. No side effect due to drug was observed. Heart rate was found more decreased in amiodarone group at T-1 and T-2 stages when compared with controls (p<0.05). Perioperative high- dose amiodarone might be beneficial for patients who are pulmonary hypertensive and are undergoing CABG.
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    Prediction of Postcoronary Artery Bypass Grafting Atrial Fibrillation: POAFRiskScore Tool
    (Georg Thieme Verlag Kg, 2023) Arslan, Ahmet Kadir; Erdil, Nevzat; Guldogan, Emek; Colak, Cemil; Akca, Baris; Colak, M. Cengiz
    Background Atrial fibrillation (AF), a condition that might occur after a heart bypass procedure, has caused differing estimates of its occurrence and risk. The current study analyses the possible risk factors of post-coronary artery bypass grafting (post-CABG) AF (postoperative AF [POAF]) and presents a software for preoperative POAF risk prediction. Methods This retrospective research was performed on 1,667 patients who underwent CABG surgery using the hospital database. The associations between the variables of the patients and AF risk factors after CABG were examined using multivariable logistic regression (LR) after preprocessing the relevant data. The tool was designed to predict POAF risk using Shiny, an R package, to develop a web-based software. Results The overall proportion of post-CABG AF was 12.2%. According to the results of univariate tests, in terms of age ( p < 0.001), blood urea nitrogen ( p = 0.005), platelet ( p < 0.001), triglyceride ( p = 0.0026), presence of chronic obstructive pulmonary disease (COPD; p = 0.01), and presence of preoperative carotid artery stenosis (PCAS; p < 0.001), there were statistically significant differences between the POAF and non-POAF groups. Multivariable LR analysis disclosed the independent risk factors associated with POAF: PCAS (odds ratio [OR] = 2.360; p = 0.028), COPD (OR = 2.243; p = 0.015), body mass index (OR = 1.090; p = 0.006), age (OR = 1.054, p < 0.001), and platelet (OR = 0.994, p < 0.001). Conclusion The experimental findings from the current research demonstrate that the suggested tool ( POAFRiskScore v.1.0 ) can help clinicians predict POAF risk development in the preoperative period after validated on large sample(s) that can represent the related population(s). Simultaneously, since the updated versions of the proposed tool will be released periodically based on the increases in data dimensions with continuously added new samples and related factors, more robust predictions may be obtained in the subsequent stages of the current study in statistical and clinical terms.