İstanbul Sağlık ve Teknoloji Üniversitesi Kurumsal Akademik Arşivi
DSpace@İSTÜN, Üniversite mensupları tarafından doğrudan ve dolaylı olarak yayınlanan; kitap, makale, tez, bildiri, rapor, araştırma verisi gibi tüm akademik kaynakları uluslararası standartlarda dijital ortamda depolar, Üniversitenin akademik performansını izlemeye aracılık eder, kaynakları uzun süreli saklar ve telif haklarına uygun olarak Açık Erişime sunar.
Güncel Gönderiler
Examination of infant mortality risk in Turkey with spatio-temporal Bayesian models
(PAGEPress, 2025) Kılıç Yıldırım, Sade; Alpar, Celal Reha
The infant mortality rate in Turkey declined from 13.9 deaths per 1,000 live births in 2009 to 9.3 deaths per 1,000 live births in 2017. This study explored the role of spatio-temporal Bayesian models in explaining this decline. Parametric, nonparametric spatio- temporal Bayesian models, and a Bayesian generalized linear model without space, time, and space-time interaction were applied using the Integrated Nested Laplace Approximation (INLA) method. Exceedance probabilities were used for detecting significant risk clusters. The unstructured spatial and structured temporal interaction random effect of the best-fitting spatio-temporal Bayesian model contributed more to explaining variation in the relative risk of infant mortality than the other random effects. From 2009 to 2017, in each year, significant risk clusters were consistently detected in the eastern and south-eastern Anatolia regions. An increase of 1,000 USD in the Gross Domestic Product (GDP) per capita reduced the relative risk of infant mortality by 2.8%. When determining the factors that may affect infant mortality in Turkey, it is also essential to consider the effects of space, time, and space-time interaction. In addition, decision-makers should consider the increase in GDP per capita as a factor in reducing infant mortality in Turkey by focusing on these significant risk clusters in the eastern and south-eastern Anatolia regions.
Logistical requirements for high-resolution anoscopy: Pre-procedure preparation and materials – A video vignette
(Wiley, 2025) Arslan, Çiğdem
High-resolution anoscopy (HRA) is a diagnostic procedure that in-volves examining the anus, anal canal and perianal region with amicroscope, utilizing 5% acetic acid and Lugol's solution to detectabnormal epithelial changes and early precursors of anal cancer.Vital stains cause epithelial and vascular changes that distinguishnormal tissue from lesions, aiding in clinical decision-making forbiopsy.
Gender differences in the distribution of IDL, LDL, and HDL lipoprotein subfractions in MODY compared to type 2 diabetes: Data from the MODY-Ist study
(Elsevier, 2025) Yılmaz Aydoğan, Hülya; Kanca Demirci, Deniz; Gül, Nurdan; Yanar, Fatih; Poyrazoğlu, Şükran; Güleç Yılmaz, Seda; Tüzüner, Mete Bora; İsbir, Turgay; Öztürk, Oğuz; Satman, İlhan
Background: The distribution of intermediate-density lipoprotein (IDL), low-density lipoprotein (LDL) and high density lipoprotein (HDL) subfractions specific to diabetes types and changes under dyslipidemia conditions have been well characterised. Research into the distribution of lipoprotein subfractions in Maturity-Onset Diabetes of the Young (MODY) has hitherto been confined to certain subtypes, with gender-based differences remaining to be elucidated. The objective of this study was to comparatively evaluate the distribution of lipoprotein subfractions according to gender in MODY, T2DM patients, and control groups. Methods: Lipoprotein subfractions in 119 serum samples of the study groups were analyzed using the Lipoprint System. Results: The midbands of IDL (MID-A to C) in female MODY cases, and the HDL-small fraction in male MODY cases, were found to be lower compared to female and male T2DM cases, respectively. In the T2DM group, age was positively correlated with MID-C and MID-B in both genders, while it was negatively correlated with MID-A in female cases. ROC analysis demonstrated that the decrease in the MID-C fraction in female MODY subjects (AUC:0.809, p = 0.0001) and the decrease in the HDL-small fraction in male MODY subjects (AUC:0.818, p = 0.002) were significantly associated with the likelihood of MODY. Conclusion: Given that a considerable proportion of MODY patients are frequently misdiagnosed as T2DM, low levels of MID-C and HDL-small fractions, both of which are triglyceride-rich, may have potential as a diagnostic value for female and male MODY patients, respectively.
Cytolytic vaginosis in women with vaginitis: Prevalence, diagnosis, and treatment
(Karger, 2025) Kömeç, Selda; Tercan, Can; Ceylan, Ayşe Nur; Durmuş, Mehmet Akif; Donbaloğlu, Gizem Şirin; Aydın, Mustafa Derya
Objectives: Vaginitis is an inflammatory condition of the vagina, which often manifests with symptoms like discharge, foul odor, and pruritus. The most commonly recognized forms are candidiasis, bacterial vaginosis (BV), and trichomoniasis, but conditions like cytolytic vaginosis (CV) remain under-recognized and frequently misdiagnosed in clinical practice despite its notable prevalence. This study aims to evaluate the prevalence of CV in patients with vaginitis, assess the specificity of the diagnostic criteria for CV, and investigate the efficacy of CV treatments. Design: This study is a prospective diagnostic study. Participants/Materials, Setting: A total of 81 patients (aged 20–55 years) with symptoms of vaginitis, and 30 control participants without these symptoms were enrolled. Methods: Vaginal samples were analyzed for Trichomonas vaginalis, vulvovaginal candidiasis (VVC), and BV and CV. Vaginal samples were evaluated using Gram staining, pH measurement, and microbiological culture to identify causative agents. CV was diagnosed based on the low vaginal pH, presence of abundant lactobacilli, cytolysis of the vaginal epithelium, false clue cells, and naked nuclei in Gram staining. Results: The study found that CV was the most prevalent diagnosis, accounting for 32.1% of cases. This was followed by BV (22.2%) and VVC (14.8%). The most common symptoms among CV patients were vaginal discharge, pruritus, and dysuria. Vaginal discharge characteristics did not significantly distinguish CV from other forms of vaginitis. A recurrence rate of 61.5% was observed in CV patients, highlighting the recurrent nature of the condition. Sodium bicarbonate sitz baths effectively relieved symptoms in many patients (58.8%). Limitations: The number of patients receiving treatment is low, and the treatment follow-ups could have been conducted over a longer period, considering the menstrual cycle. Conclusions: The study highlights the diagnostic challenge of CV, where common symptoms overlap with other forms of vaginitis, leading to potential treatment failures. CV treatment, including NaHCO3 sitz baths, showed moderate efficacy, but further research is needed to establish more effective therapeutic strategies. Our findings underscore the importance of considering CV in the differential diagnosis of vaginitis as it remains an overlooked condition that significantly contributes to recurrent vaginitis. Further studies with larger sample sizes and better treatment protocols are needed to enhance the management of this condition.
AI-powered digital assistant for chronic disease and elderly care management
(IEEE, 2025) Bayram, Hatice Merve; Gürcan, Zehra; Ayrıç, Esmanur; Gözüaçık, Necip
The increasing prevalence of chronic diseases and the aging population pose significant challenges to healthcare systems worldwide, necessitating innovative technological solutions to alleviate the burden. Previous studies have explored telemedicine and the integration of AI in healthcare, yet there remains a gap in comprehensive systems that integrate health monitoring, advisory services, and emergency alerts. This research aims to address this gap by developing an AI-powered digital assistant designed to enhance chronic disease management and elderly care. Utilizing a user-centered design approach, the study employs mobile health applications, AI-driven decision support systems, and a hybrid health tracking model that combines automatic and manual data entry. The system architecture includes a mobile application developed with Flutter, backend services using ASP.NET Core, and AI functionalities powered by Microsoft Azure's OpenAI models. Key findings demonstrate the system's effectiveness in improving user engagement in health management, providing timely alerts, and offering personalized health insights, thereby challenging existing assumptions about the limitations of digital health platforms. The study contributes to the field by offering a scalable, user-friendly solution that empowers individuals in managing their health, with practical implications for reducing healthcare dependency and enhancing patient autonomy. Future work will focus on expanding the system's capabilities and conducting real-world user testing to further refine its accessibility and usability.
