Browsing by Author "Tanriover, Mine Durusu"

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The Changing Trends of Peritoneal Dialysis Related Peritonitis and Novel Risk Factors
(2015) Ozisik, Lale; Ozdemir, Fatma Nurhan; Tanriover, Mine Durusu; 0000-0002-5682-0943; 0000-0002-3494-8997; 26042343; AAK-1697-2021
Aim: Continuous ambulatory peritoneal dialysis (PD) has become a treatment modality for end stage renal disease with a peak of its use in 1990s. The aim of this study was to examine the peritonitis rates, causative organisms and the risk factors of peritonitis in a large group of patients in our center. Methods: The study was conducted in the Nephrology Department of a University Hospital in Turkey. Patients in the PD programme between January 2000 and January 2006 were included. Cohort-specific and subject specific peritonitis incidence, and peritonitisfree survival were calculated. Causative organisms and risk factors were evaluated. Results: Totally 620 episodes of peritonitis occurred in 440 patients over the six years period. Peritonitis rates showed a decreasing trend through the years (0.79 episodes/patient-year 2000-2003 and 0.46 episodes/patient-year 2003-2006). Cohort-specific peritonitis incidence was 0.62 episodes/patient-years and median subject-specific peritonitis incidence was 0.44 episodes/patient-years. The median peritonitis-free survival was 15.25 months (% 95 CI, 9.45-21.06 months). The proportion of gram-negative organisms has increased from 9.8% to 17.3%. There was a significant difference in the percentage of culture negative peritonitis between the first three and the last three years (53.1% vs. 43.2%, respectively). Peritonitis incidence was higher in patients who had been transferred from HD, who had catheter related infection and who had HCV infection without cirrhosis. Conclusions: Our study showed significant trends in the peritonitis rates, causative organisms and antibiotic resistance. Prior HD therapy, catheter related infections and HCV infection were found to be risk factors for peritonitis.
Evaluation of Machine Learning Algorithms for Renin-Angiotensin-Aldosterone System Inhibitors Associated Renal Adverse Event Prediction
(2023) Guven, Alper Tuna; Ozdede, Murat; Sener, Yusuf Ziya; Yildirim, Ali Osman; Altintop, Sabri Engin; Yesilyurt, Berkay; Uyaroglu, Oguz Abdullah; Tanriover, Mine Durusu; 0000-0002-6310-4240; 37217407
Background: Renin-angiotensin-aldosterone system inhibitors (RAASi) are commonly used medications. Renal adverse events associated with RAASi are hyperkalemia and acute kidney injury. We aimed to evaluate the performance of machine learning (ML) algorithms in order to define event associated features and predict RAASi associated renal adverse events.Materials and Methods: Data of patients recruited from five internal medicine and cardiology outpatient clinics were evaluated retrospectively. Clinical, laboratory, and medication data were acquired via electronic medical records. Dataset balancing and feature selection for machine learning algorithms were performed. Random forest (RF), k-nearest neighbor (kNN), naive Bayes (NB), extreme gradient boosting (xGB), support vector machine (SVM), neural network (NN), and logistic regression (LR) were used to create a prediction model.Results: 409 patients were included, and 50 renal adverse events occurred. The most important features predicting the renal adverse events were the index K and glucose levels, as well as having uncontrolled diabetes mellitus. Thiazides reduced RAASi associated hyperkalemia. kNN, RF, xGB and NN algorithms have the highest and similar AUC (> 98%), recall (> 94%), specifity (> 97%), precision (> 92%), accuracy (> 96%) and F1 statistics (> 94%) performance metrics for prediction.Conclusion: RAASi associated renal adverse events can be predicted prior to medication initiation by machine learning algorithms. Further prospective studies with large patient numbers are needed to create scoring systems as well as for their validation.
Turkish Doctors' Cohort: Healthy Despite Low Screening
(2017) Unal, Serhat; Tanriover, Mine Durusu; Ascioglu, Sibel; Demirkazik, Ahmet; Ertenli, Ihsan; Eskioglu, Erdal; Guler, Kerim; Kiraz, Sedat; Ozbakkaloglu, Mert; Ozer, Birol; Tukek, Tufan; Akyar, Serra; Erdem, Yunus; 27960640
Objectives: We aimed to determine the prevalence of chronic diseases and unhealthy lifestyle behaviors of Turkish doctors as compared with the general population and the frequency of compliance with preventive clinical practices among doctors. Methods: This was an observational, prospective cohort study that enrolled graduates between 1975 and 2004 from six medical schools in Turkey. Data on demographics, disease conditions, and unhealthy lifestyle behaviors were gathered. Preventive care practices were analyzed with regards to age and gender. Results: A total of 7228 doctors participated in the study. Comparison with the national data revealed higher hyperlipidemia and coronary artery disease rates. While 54.5% of the doctors had a doctor visit in the last 12months, only 31.5% of those over 40years of age reported a recent blood pressure measurement. Colon cancer screening rate over 50years of age with any of the acceptable methods was only 3%. One-fourth of the female doctors over 40years of age underwent mammography within the last two years. Only 7.1% of the doctors over 65years of age and 10% of the doctors having an indication for a chronic disease had a pneumococcal vaccine, while nearly one-fifth had no hepatitis B vaccine. Conclusion: In this cohort of mainly middle-aged Turkish doctors, the age-standardized rates of chronic diseases were lower than the rates in the general population except for the rates of hyperlipidemia and coronary artery disease. However, doctors did show quite low rates of receipt of screening practices. These results might provoke questions about how to use Turkish doctors' health behaviors to further improve doctors' and, relatedly, patients' health.