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
Dual etiology vs. MetALD: how MAFLD and MASLD address liver diseases coexistence
(OAE Publishing, 2025) Zerehpooshnesfchi, Shadi; Lonardo, Amedeo; Fan, Jian-Gao; Elwakil, Reda; Tanwandee, Tawesak; Altarrah, Munira; Örmeci, Necati; Eslam, Mohammed
Fatty liver disease associated with metabolic dysfunction has emerged as a significant global health challenge. This condition often coexists with other liver diseases, such as alcohol-related liver disease and viral hepatitis, complicating both diagnosis and management. To address the limitations of the non-alcoholic fatty liver disease (NAFLD) classification, two alternative frameworks have been proposed: metabolic dysfunction-associated fatty liver disease (MAFLD) in 2020 and metabolic dysfunction-associated steatotic liver disease (MASLD) in 2023. A key difference between these definitions is how they consider fatty liver disease in relation to the coexistence of other liver conditions. MAFLD adopts a dual etiology concept, creating a unified classification system that aligns with contemporary clinical and epidemiological needs. In contrast, MASLD introduces a new term, MetALD (metabolic and alcohol-related/associated liver disease), to describe patients who have both metabolic dysfunction and excessive alcohol intake. This review critically examines the clinical, research, and epidemiological implications of the differing approaches of MAFLD and MASLD, offering insights into their potential to enhance the understanding and management of multi-etiology liver diseases.
A comprehensive morphological and morphometric study of the spinoglenoid notch and ligament/ membrane: Possible clinical relevance of suprascapular nerve entrapment
(Istanbul University Faculty of Medicine, 2025) Coşkun, Osman; Gürses, İlke Ali; Gayretli, Özcan; Kale, Ayşin; Kına, Adnan; Usta, Ahmet; Şahinoğlu, Kayıhan; Öztürk, Adnan
Objective: This study aimed to determine the anatomical fea tures and clinical significance of the spinoglenoid notch and spinoglenoid ligament-membrane as well as the branches of the suprascapular nerve to the infraspinatus muscle as these struc tures may cause compression of this nerve. Material and Methods: Fifty sides (25 right and 25 left) were studied on 26 fixed cadavers belonging to the Department of Anatomy, İstanbul University, İstanbul Faculty of Medicine. The suprascapular nerve branches to the infraspinatus muscle and spinoglenoid ligament-membrane were examined in cadavers, and the spinoglenoid notch was investigated in 50 dry scapulae. Result: The suprascapular nerve had two branches to the in fraspinatus muscle in 22 cadavers on 37 sides (74%) and three branches to this muscle in 11 cadavers on 13 sides (26%). On 31 sides the spinoglenoid membrane and on 19 sides the spinoglenoid ligament were observed. Related to the spinoglenoid notch, the mean width was 17.17±2.17 mm, and the mean depth was 17.45±2.03 mm in calliper measurements on dry bones, while the mean width was 16.99±1.88 mm, the mean depth was 17.73±2 mm and the mean area was 282.04±55.27 mm² in com puted tomography measurements. Conclusion: The presented data regarding the spinoglenoid notch in which the suprascapular nerve is frequently compressed and the branches of the suprascapular nerve to the infraspinatus muscle may guide the surgical treatment of the related entrap ment syndrome.
Enhanced nearest centroid model tree classifer
(Springer Nature Link, 2025) Özçelik, Mehmet Hamdi; Duman, Ekrem; Bağrıyanık, Selami; Bulkan, Serol
In this study, frst, we improved an existing variant of the Nearest Centroid algorithm. In this new version, the predic tive power of features and within-class variances are used as weights in distance calculation. This version is called the Enhanced Nearest Centroid (ENC). Second, we proposed a new model tree algorithm for binary classifcation. It is named as the Enhanced Nearest Centroid Model Tree (ENCMT). The model tree is built using ENC at each leaf node of the decision tree. To evaluate the performance of the new model tree, we used an independent test platform and ran the algorithm on 30 binary datasets available therein. Results showed that ENCMT improves the performance of the decision tree algorithm. We also compared ENCMT with the Logistic Model Tree (LMT) algorithm and showed that it outperforms LMT as well. We also designed a bagging algorithm where ENCMT is used to build a random forest. Our comparison results show that its performance is signifcantly better than the Random Forest (RF) algorithm.
Segurança do paciente idoso e gerenciamento de serviços de enfermagem em instituições de longa permanência
(Science Editorial, 2025) Aydoğdu, Ana Luiza Ferreira; Türkmen, Meryem Feyza
O envelhecimento populacional é uma realidade global. Nesse contexto, as instituições de longa permanência para idosos surgem como alternativas viáveis para garantir assistência e suporte contínuo a essa população. A presente reflexão teórica teve como objetivo analisar o papel essencial da gerência em Enfermagem na garantia da segurança dos residentes de Instituições de Longa Permanência para Idosos (ILPIs). Para tanto, foi realizada uma pesquisa bibliográfica em diversas bases de dados (Web of Science (WoS) Core Collection, Scopus, PubMed e Google Acadêmico) no mês de março de 2023. As principais ameaças à saúde dos residentes das ILPIs estão relacionadas à ocorrência de úlceras por pressão, quedas e infecções, especialmente, infecções urinárias. Esses eventos adversos estão associados a condições inadequadas de higiene, ao número insuficiente de cuidadores e profissionais na equipe de Enfermagem e à falta de treinamento de pessoal. Diante disso, determinou-se que o papel desempenhado pelos administradores das instituições de longa permanência, e pelos gerentes de Enfermagem, é essencial para garantir a segurança dos residentes. Para isso, é fundamental a implementação de programas de educação continuada, a promoção de um ambiente seguro e saudável, a contratação e retenção de um número adequado de profissionais qualificados, além do estabelecimento de diretrizes e orientações para a prevenção de eventos adversos.
Early stage effectiveness of the automated insulin delivery system—is artificial intelligence really effective?
(AVES, 2025) Çetin, Ferhat; Göncüoğlu, Enver Şükrü; Abalı, Saygın; Arslanoğlu, İlknur; Deyneli, Oğuzhan; Telci Çaklılı, Özge; Yalın Turna, Hülya; Şahiner, Elif; Güzel, Dila; Yılmaz, Mehmet Temel
Objective: This study aimed to evaluate the effectiveness of the self-learning capabilities of artificial intelligence (AI) algorithms. The hypothesis was that if the success of closed-loop insulin delivery is mainly attributed to AI algorithms, then the improvement in glycemic control would be more signifi cant just after the “learning” phase. Methods: The Medtrum A8 TouchCare® Nano system was used on 15 patients with type 1 diabetes. Daily continuous glucose monitoring (CGM) data pre-automated insulin delivery (AID) was statisti cally compared with the post-AID period. Results: Patients (median age 32 (6-54) years, 40% female) had a median HbA1c of 8.4% (5.3-10.7) before initiation of AID and a median GMI of 6.6% (5.8-8.3) after 2 weeks. The shifts in glycemia and glycemic variability between the 5-day period pre-AID vs. the first day and the 3 5-day periods post-AID were significant (pre-AID vs. 1-5-10-15 days; time in range (TIR, %): 55.9 vs. 76.6-81.7-83.8- 81.5 (P=.001); Q1 (mg/dL): 123 vs. 112-108-106-110 (P=.009); Q3 (mg/dL): 204 vs. 176-173-168-169 (P=.004); inter-quarter range (IQR, mg/dL): 78 vs. 57.2-56.6-53-55 (P=.002)). The biggest shift in TIR was achieved in the first day (10.1%). Comparative analysis of the 5-day intervals post-AID was insig nificant by means of the improvement in glycemia (P > .05). No significant change in glycemic param eters between 15, 30, and 90 days were noted (P > .05). Conclusion: Artificial intelligence-augmented AID becomes effective at the very early stages of initia tion. There is a need for further research into glycemic changes in the early days of AID initiation to better define the principles of initiating AID systems.
