Lipopolysaccharides is well-known in the acute renal injury process. It causes widespread activation of inflammatory cascades. Tumor necrosis factor (TNF)-α and interleukin (Il)-6 are essential proinflammatory cytokines that can induce the production of other cytokines in host response. Adalimumab suppresses TNF-α, IL-1β, and IL-6. We aimed to evaluate whether adalimumab would prevent the toxicity of lipopolysaccharide on the rat renal tissue.

This study aimed to evaluate the impact of preprocedural neutrophil-to-albumin ratio (NAR) on survival among patients undergoing tunneled hemodialysis catheter (THC) placement. We retrospectively reviewed 60 consecutive patients who underwent right-internal-jugular THC placement between July 2021 and October 2023. Demographics, laboratory variables and survival were collected. NAR and neutrophil-percentage-to-albumin ratio (NPAR) were calculated. Cox regression and Kaplan - Meier analyses explored associations with mortality; receiver-operating-characteristic (ROC) curves defined optimal cutoffs. Mean age was 70 ± 12 years; 24 patients (40%) died, yielding one-year survival of 62.5%. On multivariate Cox regression analysis, after adjustment for all covariates, higher NAR remained an independent predictor of mortality (p 175.4 had markedly lower one-year survival than those below the threshold (30.2% vs 88.2%, p <0.001). Catheter patency at one year was 84.8%. Among patients receiving a tunneled hemodialysis catheter, elevated preprocedural NAR levels were associated with increased mortality. NAR, which is an easily and routinely measurable parameter, may serve as a prognostic biomarker in this patient population.

Patient-prosthesis mismatch after aortic valve replacement: Effects on left ventricular structure - Turkish Journal of Thoracic and Cardiovascular Surgery

Aim: This study aimed to analyze the specialization theses in the field of cardiovascular surgery in Türkiye, and examine their rates of conversion to scientific publications.Material and Methods: Specialization in medicine theses in the field of cardiovascular surgery published in Türkiye from 2015 to 2020 were evaluated using the Council of Higher Education Thesis Center database. For each specialization thesis, details such as the year, institution, city, study design, advisor’s title, and author information were recorded. The conversion of theses into scientific publications was assessed using Google Scholar, PubMed, Dergipark, and TR Index databases based on the thesis title, advisor, and author information. Results: A total of 204 specialization theses in medicine were examined in the study. Of the thesis authors, 171 were men (83.3%) and 33 were women (16.2%). When categorized by institutions, 130 theses (63.7%) were affiliated with institutions in the three major cities. It was observed that 79 of the evaluated theses (38.7%) were turned into scientific publications. The conversion rate into scientific publications was significantly higher in institutions affiliated with the University of Health Sciences (p=0.002). A significant relationship was observed between the study design, the index of the publishing journal, and the citation status (p=0.029, p<0.001, respectively).Conclusion: The findings obtained in the present study showed that the majority of specialization theses in cardiovascular surgery were not turned into scientific publications. We believe that collaboration with professional associations and the Medical Specialty Board may contribute positively to the publication rate of specialization theses.

Preoperative Pulmonary Artery Systolic Pressure and Survival in Patients Undergoing Valve Replacement for Mitral Stenosis - Istanbul Medical Journal

Objective: Vascular access is a key component of effective hemodialysis treatment. Patient education regarding selection, complications, and daily care remains challenging. Recently, large language models (LLMs) have been explored as supportive tools in this field. This study compared three widely used LLMs (ChatGPT-5, Gemini-2.5, and DeepSeek-V3) in addressing patient-centered questions on hemodialysis vascular access. Methods: Twenty-five frequently asked patient questions were compiled from literature, educational materials, and expert input. Each question was submitted to the three LLMs in standardized sessions, and answers were anonymized. Four cardiovascular surgeons independently evaluated responses in a blinded manner using 5-point Likert scales for accuracy, clarity, and scientificity. Statistical analyses compared model performances. Results: DeepSeek-V3 provided significantly responses with a higher word count and achieved higher scientific depth scores compared to ChatGPT-5 and Gemini-2.5 (P<0.01). Accuracy scores showed ChatGPT-5 demonstrated significantly lower than both Gemini-2.5 and DeepSeek-V3 (P<0.001). No significant differences were observed among models regarding clarity. Overall, DeepSeek achieved the highest mean scores across all criteria. Conclusion: DeepSeek-V3 demonstrated superior scientific depth and overall reliability, whereas ChatGPT-5 showed relative weaknesses in accuracy. The comparable clarity across models highlights LLMs’ potential as supportive tools for patient education. Future studies should further validate these tools in real-world clinical settings and define appropriate safeguards for their use.