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    EVALUATION OF SOCIO-DEMOGRAPHIC FACTORS AND COMORBIDITIES IN ADULT HEMOPHILIA PATIENTS
    (Dokuz Eylul Univ Inst Health Sciences, 2024) Karadag, Fatma Keklik; Demirci, Zuhal; Koseoglu, Fatos Dilan; Saydam, Guray; Sahin, Fahri
    Purpose: The association between socio-demographic factors and hemophilia status with the prevalence of comorbidities was evaluated. Material and Methods: Patients with hemophilia A (n=111) and B (n=24) who completed the questionnaire form about their socio-demographic factors were included in our study. Factor and inhibitor levels, comorbidities, factor replacement therapies, hemophilic arthropathy, viral status and annual bleeding episodes were recorded. Results: The median age was 39 years among 135 hemophilia patients, and 63.1% of all patients had severe hemophilia, which was significantly higher among hemophilia A (p=0.002). Most patients (74.8%) were treated with prophylactic factor replacement therapy. The inhibitor status was positive in 8.9% of all patients. The unemployment rate was found to be 33.3%. Annual bleeding episodes were higher in workers. Most patients (60%) had graduated from at least high school. Patients with severe hemophilia were significantly less educated than those with moderate to mild hemophilia (p=0.045). The prevalence of cardiovascular disease, hypertension, diabetes mellitus, and obesity was 6.7%; 17.8%, 13.3%, and 11.9% respectively. Although there was no association between obesity and annual bleeding episodes, right ankle was the most affected joint in overweight/obese patients. Conclusion: Age -related comorbidities and the relationship between hemophilia status and social life need further investigation.
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    Hemoglobin to red cell distribution width ratio in patients with heart failure with preserved ejection fraction
    (Elsevier Ireland Ltd, 2024) Koseoglu, Fatos Dilan; Zlek, Buelent
    [Abstract Not Available]
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    The importance of hemoglobin levels and red blood cell transfusion in patients with sepsis
    (W B Saunders Co-Elsevier Inc, 2023) Koseoglu, Fatos Dilan
    [Abstract Not Available]
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    Machine learning approaches in the interpretation of endobronchial ultrasound images: a comparative analysis
    (Springer, 2023) Koseoglu, Fatos Dilan; Alici, Ibrahim Onur; Er, Orhan
    BackgroundThis study explores the application of machine learning (ML) in analyzing endobronchial ultrasound (EBUS) images for the detection of lymph node (LN) malignancy, aiming to augment diagnostic accuracy and efficiency. We investigated whether ML could outperform conventional classification systems in identifying malignant involvement of LNs, based on eight established sonographic features.MethodsRetrospective data from two tertiary care hospital bronchoscopy units were utilized, encompassing healthcare reports of patients who had undergone EBUS between January 2017 and March 2023. The ML model was trained and tested using MATLAB, with 80% of the data allocated for training/validation, and 20% for testing. Performance was evaluated based on validation and testing accuracy, and receiver operating characteristic curves with comparing trained models and existing classification rules.ResultsThe study analyzed 992 LNs, with 42.3% malignancy prevalence. Malignant LNs showed characteristic features such as larger size and distinct margins. The fine tuned models achieved testing accuracies of 95.9% and 96.4% for fine Gaussian SVM and KNN, respectively. Corresponding AUROC's were 0.955 and 0.963, outperforming other similar studies and conventional analyses.ConclusionFine tuned ML applications like SVM and KNN, can significantly enhance the analysis of EBUS images, improving diagnostic accuracy.
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    Prediction of anemia with thoracic computed tomography findings
    (Turkish Assoc Trauma Emergency Surgery, 2024) Ocal, Zeynep Ayvat; Koseoglu, Fatos Dilan
    BACKGROUND: This study explored the potential of non-contrast thoracic computed tomography (CT) to predict anemia by correlating CT parameters with hemoglobin (Hb) levels in patients who underwent non-contrast thoracic CT for various indications. METHODS: This retrospective study included 150 patients who underwent non-contrast thoracic CT scans and complete blood counts within 24 hours at our center between January and June 2023. Exclusion criteria included acute bleeding, iron accumulation disorders, recent transfusions, pregnancy, and certain thoracic CT artifacts. Hounsfield Unit (HU) measurements were obtained from the ascending aorta, left ventricular cavity, and descending aorta, and compared with Hb and hematocrit (Htc) values. Anemia indicators such as the Aortic Ring Sign (ARS) and the Hyperdense Septum Sign (HSS) were also evaluated. RESULTS: Anemic patients (48%) exhibited significantly lower HU measurements at all three CT scan locations and higher instances of ARS and HSS compared to non-anemic patients. Notably, the presence of HSS and ARS was strongly associated with anemia. Thresholds for HU measurements corresponding to anemia were determined using receiver operating characteristic curve analysis, which also revealed strong positive correlations between HU measurements and Hb/Htc levels. CONCLUSION: The study concludes that non-contrast thoracic CT parameters, particularly HU measurements and the presence of ARS and HSS, are significantly associated with anemia. These CT indicators could serve as reliable, non-invasive markers for predicting anemia in patients, potentially aiding in the early diagnosis and management of the condition.