Balıkesir Üniversitesi Kurumsal Akademik Arşivi
DSpace@Balıkesir, Balıkesir Üniversitesi 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 yayınların etkisini artırmak için telif haklarına uygun olarak Açık Erişime sunar.
Güncel Gönderiler
Ardıçtepe Baraj Havzası’nda erozyon hassasiyet analizinin belirlenmesinde yağış ve arazi yüzey kapalılık etkileşiminin MPSIAC yöntemiyle analizi
(Jeomorfoloji Derneği, 2026) Soykan, Abdullah; Sarıduran, Ayşe
Baraj havzalarında erozyon süreçleri, rezervuara taşınan sediment miktarını artırarak barajların depolama kapasitesini ve ekonomik ömrünü doğrudan etkilemektedir. Bu çalışmada, Ardıçtepe Baraj Havzası’nda erozyon hassasiyetinin belirlenmesinde, MPSIAC (Modified Pacific Southwest Interagency Committee) modeli kullanılarak özellikle yağış (X₃) ve arazi yüzey kapalılığı (X₆) faktörlerinin mekânsal etkileşimi analiz edilmiştir. MPSIAC modelinde yer alan dokuz parametre arasından bu iki faktörün seçilmesinin temel gerekçesi; yağış erozivitesi ve bitki örtüsü kapalılığının kısa ve orta vadede değişkenlik gösterebilen, iklimsel dalgalanmalara ve arazi kullanımına doğrudan bağlı dinamik faktörler olmasıdır. Buna karşılık litoloji, toprak yapısı ve topoğrafya gibi diğer parametreler büyük ölçüde statik nitelikte olup baraj işletme süresi boyunca sınırlı değişim göstermektedir. Çalışma kapsamında, İvrindi Meteoroloji İstasyonu’na ait uzun yıllar ortalama yağış verileri hesaplanarak arazi yüzeylerine paralel olacak şekilde yağış miktarı artışı belirlenmiştir; arazi yüzey kapalılığı ise güncel orman ve arazi kullanım verileri kullanılarak sınıflandırılmıştır. Elde edilen raster katmanlar çakıştırılarak, yüksek yağış erozivitesi ile düşük kapalılık oranlarının kesiştiği kritik erozyon zonları belirlenmiştir. Bulgular; havza genelinde yüksek yağış erozivitesi ile düşük kapalılık oranlarının kesiştiği kritik zonların, sediment taşınımı açısından başlıca risk bölgelerini oluşturduğunu ortaya koymaktadır. Sonuç olarak bu çalışma; havza genelinin %27,58’ini temsil eden 7.036 hektarlık bir alanın 'yüksek' ve 'çok yüksek' erozyon riski altında olduğunu ortaya koymuştur. Elde edilen bulgular, erozyonun yalnızca çok sayıda faktörün toplam etkisiyle değil, özellikle yağışın tetikleyici gücü ile arazi örtüsünün koruyucu kapasitesi arasındaki dinamik dengenin bozulmasıyla şiddetlendiğini göstermektedir. Bu iki faktöre odaklanılarak yapılan analizler, barajın uzun vadeli sürdürülebilirliği açısından öncelikli müdahale alanlarının belirlenmesine olanak tanımakta ve havza yönetimi için stratejik bir karar destek altyapısı sunmaktadır.
Retrospective assessment of Neutrophil/Lymphocyte Ratio and CRP value correlation with infections in cancer patients
(Wiley, 2026) Tüz, Mehmet Ali; Aydemir, Hande; Çelebi, Güven; Engin, Hüseyin; Büyükuysal, Mustafa Çağatay; Pişkin, Nihal
Recent studies have pointed out that CRP and NLR levels are important in determining the prognosis for cancer and diagnosis ofinfection, but there are few studies on cut-of levels in patients with solid tumours. In this study, the relationship between CRP cut-of levels with infection and NLR with infection has investigated in adult solid organ cancer patients receiving inpatient treatment.Patients with solid cancer hospitalised in ZBEU Oncology and Infectious Diseases between 2013 and 2018 were included to studyretrospectively. Patients were separated into 2 groups: 240 patients with clinical and radiological or microbiological evidence ofinfection as group 1 and 240 patients with no signs of infection as group 2. Both groups were subdivided into patients withmetastatic cancer and nonmetastatic cancer. The mean CRP at admission and 24th hour in the group 1 (170.0 and 157.5 mg/L,respectively) were found to be statistically higher than group 2 (51.0 and 47.5 mg/L, respectively) (p < 0.001 and p < 0.001). Thebest cut-of value of CRP at admission was found to be 108 mg/L with %72.08 sensitivity, %75.42 specifcity (p < 0.001) and 88 mg/L24th hour CRP (p < 0.001). Mean values of NLR on admission and 24th hour were signifcantly higher in group 1 than in group 2(p < 0.001 and p < 0.001). The best NLR cut-of value was found to be 7.823 at admission (p < 0.001) and 8.4 at 24th hours(p < 0.001). Although both tests are used to detect infection in patients with solid cancer, it is important to know that the cut-ofvalues are high. In patients with solid cancer who do not have clinical signs of infection, unnecessary antibiotherapy should not beperformed because of high CRP or NLR.
A LASSO-Based nomogram for predicting focal complications in brucellosis: A multicenter retrospective cohort study
(MDPI, 2026) Dalmanoğlu, Enes; Al, Sevda Özdemir; Bağın, Ünsal
Background: Up to one-third of brucellosis patients develop focal organ involvement,
contributing to increased morbidity and therapeutic failure, yet no clinically validated
instrument exists to stratify risk at presentation.
Methods: In this three-center retro
spective cohort from Türkiye (2015–2025), 355 adults with confirmed brucellosis were
enrolled. Thirty-two candidate variables spanning demographics, comorbidities, symp
toms, routine laboratory values, and composite inflammation indices underwent LASSO
penalized regression with 10-fold cross-validation for predictor selection, after which a
nomogram wasconstructed and internally validated via 1000-iteration bootstrap resam
pling.
Results: Ninety-two patients (25.9%) developed focal complications. Five predictors
were retained by LASSO—prognostic nutritional index (PNI), erythrocyte sedimentation
rate (ESR), C-reactive protein (CRP), chronic disease stage, and hypertension—and com
bined with age and sex (retained a priori) into a seven-predictor nomogram. PNI was
the strongest contributor (OR = 0.901, 95% CI: 0.857–0.948). Apparent C-statistic reached
0.782 (optimism-corrected 0.762), with a calibration slope of 0.894 and Brier score of 0.154.
Decision curve analysis indicated net clinical benefit over the 5–55% threshold probability
range. Conclusions: This PNI-anchored LASSO nomogram offers a practical bedside risk
stratification instrument for brucellosis-related focal involvement. Prospective external vali
dation across geographically diverse endemic regions is warranted before clinical adoption.
Anesthesia for vertebral compression fractures treated with percutaneous kyphoplasty: Comparison of erector spinae plane block, extrapedicular infiltration anesthesia, and conventional local infiltration anesthesia
(Turkish Assoc Orthopaedics Traumatology, 2026) Özhan, Mehmet Özgür; Eşkin, Mehmet Burak; Eksert, Sami; Ceylan, Ayşegül; Başak, Ali Murat; Şimşek, Fatih
Objective: Local anesthesia with sedoanalgesia and general anesthesia are widely used in percutaneous kyphoplasty (PKP) for vertebral compression fractures (VCF). The aim of this study was to compare erector spinae block (ESP) with conventional local infiltration anes-thesia (CLIA) and extrapedicular infiltration anesthesia (EPIA) with respect to analgesic efficacy in patients who underwent elective PKP for VCF.Methods: A total of 90 American Society of Anesthesiologists (ASA) 1-3 patients were randomly assigned into 3 groups: group CLIA (n = 30), group EPIA (n = 30), and group ESP (n = 30). The same amount of local anesthetic mixture (6 mL lidocaine 1% and 14 mL bupiva-caine 0.5%) was used for regional anesthetic techniques in all groups. Fentanyl 0.1 μg/kg and midazolam 0.1 mg/kg were administered intravenously (IV) before prone positioning. Pain was evaluated using the visual analog scale (VAS) and sedation level using the Ramsay Sedation Scale (RSS) during the procedure. Primary outcome measure were VAS and RSS scores. Secondary outcome measures were hemodynamic changes and additional analgesic and sedative consumptions.Results: Mean baseline VAS scores were similar between groups (5.62 ± .39; P> .05). Intraoperative mean VAS scores were significantly higher in group CLIA compared to EPIA and ESP groups at all timepoints (P< .01). Time-bound changes in VAS scores showed a progres-sive decrease from baseline until the end of the procedure in EPIA (5.60 ± 1.38 to 1.10 ± 0.85; P< .01) and ESP groups (5.30 ± 1.44 to 1.17 ± 0.95; P< .01), while an increase was detected from baseline to the 20th minute in group CLIA (5.97 ± 1.35 to 7.07 ± 0.94; P< .01) that followed a decrease until the end of the procedure (3.47 ± 0.86; P< .01). The mean RSS scores were similar at baseline and at the end of the procedure in all groups (P> .01), but significantly lower in group CLIA compared to EPIA and ESP groups at the other timepoints (P< .001). Time-bound changes in RSS scores showed a progressive increase from baseline until the 20th minute of the procedure that followed a decrease until the end of the procedure in EPIA (5.60 ± 1.38 to 1.10 ± 0.85; P< .01) and ESP groups (5.30 ± 1.44 to 1.17 ± 0.95; P< .01).Conclusion: Better anesthetic advantages of ESP and EPIA over CLIA concerning intra-operative analgesia, analgesic and sedative con-sumption were demonstrated. ESP and EPIA can be used as a suitable anesthetic method in VCF patients undergoing single-level PKP, with stable hemodynamic parameters and analgesia in the intra-operative period.
Automated classification of pediatric acute lymphoblastic leukemia: A ResNet-50 deep learning approach
(Ramazan Yaman, 2026) Özdemir, Necati; Okundalaye, Oluwaseun Olumide; Onuoha, Oluwaseun Abiodun; Raso, Mario; Akinsunmade, Akintayo Emmanuel
Early detection of acute lymphoblastic leukemia (ALL) is crucial for improving
survival outcomes in children. Manual diagnosis through microscopic examination
is often time-consuming and subject to human error. This study presents
an automated classification framework for pediatric ALL using a fine-tuned
Residual Network (ResNet)-50 deep learning architecture. The model was
trained and validated on 15,135 segmented blood smear images collected from
118 pediatric patients in the publicly available ALL IDB Version 2 dataset.
Data augmentation and patient-wise splitting were applied to ensure model
generalization and prevent data leakage. The fine-tuned ResNet-50 achieved
a mean classification accuracy of 99.60%, with precision, recall, and F1-score
of 99.45%, 99.40%, and 99.42%, respectively, outperforming baseline convolutional
neural network models. Statistical validation (p < 0.0015) confirmed
that these performance improvements are highly significant. This study highlights
the potential of ResNet-50 for reliable, automated, and reproducible
leukemia diagnosis, offering clinical decision support for early detection and
treatment planning.
