2-Makale
Bu koleksiyon için kalıcı URI
Güncel Gönderiler
Öğe Machine Learning and Shock Indices-Derived Score for Predicting Contrast-Induced Nephropathy in ACS Patients(Ovid Technologies (Wolters Kluwer Health), 2025-02-13) Yunus Emre Yavuz; Sefa Tatar; Hakan Akıllı; Muzaffer Aslan; Abdullah İçliBackground Contrast-induced nephropathy (CIN) is a serious complication following acute coronary syndrome (ACS), leading to increased morbidity and mortality. Machine learning (ML), combined with parameters such as shock indices, can potentially improve CIN risk prediction by analyzing complex variable interactions and creating accessible, clinically applicable models. Methods This retrospective case-control study included 719 ACS patients who underwent percutaneous coronary intervention (PCI). Patients were divided into two groups (CIN and non-CIN), and clinical, procedural, and hemodynamic parameters, including shock indices, were analyzed using machine learning algorithms. A new predictive model, CIN-Predict 5, was developed using the Gradient Boosting Machine (GBM) algorithm, incorporating clinically relevant and statistically significant variables. Correlations between model predictions and secondary outcomes, including in-hospital mortality and hospitalization duration, were evaluated. Results Among the variables used in the GBM algorithm, the Modified Shock Index emerged as the most significant predictor, with an importance score of 0.25. The CIN-Predict 5 model achieved an AUC of 0.87, outperforming the Mehran Risk Score (AUC = 0.75) for predicting CIN. The secondary outcomes showed that CIN-Predict 5 correlated significantly with in hospital mortality (r = 0.16, p < 0.001) and hospitalization duration (r = 0.20, p < 0.001). Conclusions The GBM-based model we developed, utilizing shock indices and derived through ML, provides a practical tool for early identification of high-risk CIN patients post-ACS, enabling timely preventive strategies and improving clinical decision-making. © 2025 Wolters Kluwer Health, Inc. All rights reserved.Öğe Music Therapy may Decrease Radial Artery Spasm Rates and Increase Satisfaction during Coronary Angiography(Bentham Science Publishers Ltd., 2025-02-04) Muzaffer Aslan; Doğaç Okşen; Yunus Emre Yavuz; Çağdaş KaynakIntroduction: With the widespread use of the radial artery in catheterization procedures, radial artery spasm (RAS) is frequently considered an undesirable event. It is known that anxiety increases RAS, and listening to music helps individuals control anxiety during the procedure. This study aimed to investigate the effects of music concerts on RAS. Methods: In this prospective study, imaging and interventional coronary catheterization procedures using the radial artery were included. One group listened to a musical recital during the procedure, while the other group was treated in a quiet environment. The demographics, procedural parameters, and complications of both groups were compared. Results: The study included a total of 147 patients, with an average age of 51.6 ± 11.1 years. Of these, 78 patients (53%) listened to music, while 69 patients (46.9%) underwent catheterization in a quiet environment. The impact of music therapy on the RAS was found to be significant (11.5% vs. 20.3%; p=0.035). While music therapy showed a potential to reduce RAS rates, its effect was not statistically significant in multivariate analysis (p=0.055). Conclusion: Music is a feasible, simple, and inexpensive method for reducing anxiety levels in patients. Listening to music during catheterization can reduce procedural discomfort and the frequency of undesirable events by helping people control their anxiety.Öğe Do current indices predict cardioversion success in patients with atrial fibrillation? A retrospective observational study(Walter de Gruyter GmbH, 2024) Sefa Tatar; Yunus Emre Yavuz; Emirhan Feyzullahoglu; Ahmet Lütfi Sertdemir; Abdullah Icli; Hakan AkilliObjective: Atrial fibrillation (AF) is one of the leading arrhythmias that causes serious complications. Our aim is to investigate the factors predicting the success of cardioversion in patients who underwent the procedure due to AF. Methods: A total of 107 patients who underwent cardioversion were included in the study. Patients were divided into groups based on cardioversion success. Demographic, echocardiographic, and laboratory characteristics were compared between the groups. Results: Hypertension and diabetes mellitus were more frequent in patients with successful cardioversion, but no statistically significant difference was found between the groups (p > 0.05). The pre-procedure leukoglycemic index (LGI) was found to be higher in the successful cardioversion group. However, this difference was not statistically significant between the groups (p > 0.05). Although the fibrosis-4 (FIB-4) index and systemic immune-inflammation index (SII) were numerically higher in the group with unsuccessful cardioversion, no statistically significant difference was observed between the groups (p > 0.05). Echocardiographic parameters such as left atrial diameter and mitral regurgitation rate were higher in patients with successful cardioversion, but no significant difference was detected between the groups (p > 0.05). Conclusion: AF is a significant arrhythmia that may lead to high mortality and morbidity. Various scoring systems have been developed to predict cardioversion success. The LGI, FIB-4 index, and SII are potential predictors of cardioversion success. However, these parameters alone are insufficient to predict cardioversion success. Further large-scale randomized studies are needed to clarify the effectiveness of these parameters.
