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    Can copeptin predict the severity of coronavirus disease 2019 infection?
    (Associação Médica Brasileira, 2021) İn, Erdal; Kuluöztürk, Mutlu; Telo, Selda; Toraman, Zülal Aşçı; Karabulut, Ercan
    Objetive: Coronavirus disease 2019 (COVID-19) has quickly turned into a health problem globally. Early and effective predictors of disease severity are needed to improve the management of the patients affected with COVID-19. Copeptin, a 39-amino acid glycopeptide, is known as a C-terminal unit of the precursor pre-provasopressin (pre-proAVP). Activation of AVP system stimulates copeptin secretion in equimolar amounts with AVP. This study aimed to determine serum copeptin levels in the patients with COVID-19 and to examine the relationship between serum copeptin levels and the severity of the disease. Methods: The study included 90 patients with COVID-19. The patients with COVID-19 were divided into two groups according to disease severity as mild/moderate disease (n=35) and severe disease (n=55). All basic demographic and clinical data of the patients were recorded and blood samples were collected. Results: Copeptin levels were significantly higher in the patients with severe COVID-19 compared with the patients with mild/moderate COVID-19 (p<0.001). Copeptin levels were correlated with ferritin and fibrinogen levels positively (r=0.32, p=0.002 and r=0.25, p=0.019, respectively), and correlated with oxygen saturation negatively (r=-0.37, p<0.001). In the multivariate logistic regression analysis, it was revealed that copeptin (OR: 2.647, 95%CI 1.272-5.510; p=0.009) was an independent predictor of severe COVID-19 disease. A cutoff value of 7.84 ng/mL for copeptin predicted severe COVID-19 with a sensitivity of 78% and a specificity of 80% (AUC: 0.869, 95%CI 0.797-0.940; p<0.001). Conclusion: Copeptin could be used as a favorable prognostic biomarker while determining the disease severity in COVID-19.
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    Effect of Altered Iron Metabolism on Hyperinflammation and Coagulopathy in Patients with Critical COVID-19: A Retrospective Study
    (JAMP, 15.01.2022) Kıran,Tuğba Raika; Otlu, Önder; Erdem, Mehmet; Korkmaz, Kübranur; Ota Günay, Özge; İn, Erdal; Bay Karabulut, Aysun
    Abstract: A novel coronavirus disease 2019 (COVID-19) outbreak has started in Wuhan, China, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The relationship between altered iron homeostasis and hyperinflammation may be hallmarks of COVID-19 disease. We aimed to compare some iron (ferritin and iron), inflammation (C-reactive protein [CRP], hemoglobin, lactate dehydrogenase [LDH], neutrophil) and coagulation (prothrombin time [PT], activated partial thromboplastin time [APTT], D-dimer, platelet) marker results of critical COVID-19 patients with healthy controls results. In this single center retrospective study, 50 critical patients diagnosed with COVID-19 were included, demographic, clinical characteristics, severity of disease and laboratory test results were elicited from electronic medical records and compared to 50 healthy people. A statistically significant increase in CRP, LDH, neutrophil, PT, APTT, D-dimer ferritin levels was observed in critical COVID-19 patients compared with healthy people while a statistically significant decrease was observed in hemoglobin and iron levels. In addition, no statistically significant change in platelet levels was observed. Ferroptosis may be a significant cause of multiple organ failure in critical COVID-19 patients. Ferroptosis inhibitors might have potential to combat ferroptosis in COVID-19. Therefore, larger studies are needed to ferroptosis in COVID-19 in vivo and in vitro.
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    Effect of Altered Iron Metabolism on Hyperinflammation and Coagulopathy in Patients with Critical COVID-19: A Retrospective Study
    (2022) Otlu, Önder; Erdem, Mehmet; Korkmaz, Kübranur; Günay, Özge Ota; İn, Erdal; Kıran, Tuğba Raika; Bay Karabulut, Aysun
    Abstract: A novel coronavirus disease 2019 (COVID-19) outbreak has started in Wuhan, China, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The relationship between altered iron homeostasis and hyperinflammation may be hallmarks of COVID-19 disease. We aimed to compare some iron (ferritin and iron), inflammation (C-reactive protein [CRP], hemoglobin, lactate dehydrogenase [LDH], neutrophil) and coagulation (prothrombin time [PT], activated partial thromboplastin time [APTT], D-dimer, platelet) marker results of critical COVID-19 patients with healthy controls results. In this single center retrospective study, 50 critical patients diagnosed with COVID-19 were included, demographic, clinical characteristics, severity of disease and laboratory test results were elicited from electronic medical records and compared to 50 healthy people. A statistically significant increase in CRP, LDH, neutrophil, PT, APTT, D-dimer ferritin levels was observed in critical COVID-19 patients compared with healthy people while a statistically significant decrease was observed in hemoglobin and iron levels. In addition, no statistically significant change in platelet levels was observed. Ferroptosis may be a significant cause of multiple organ failure in critical COVID-19 patients. Ferroptosis inhibitors might have potential to combat ferroptosis in COVID-19. Therefore, larger studies are needed to ferroptosis in COVID-19 in vivo and in vitro.
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    MTU-COVNet: A hybrid methodology for diagnosing the COVID-19 pneumonia with optimized features from multi-net
    (Elsevier, 2022) Kavuran, Gürkan; İn, Erdal; Altıntop Geçkil, Ayşegül; Şahin, Mahmut; Kırıcı Berber, Nurcan
    COVID-19PneumoniaArtificial intelligence (AI)Deep learningComputed tomography (CT)
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    MTU-COVNet: A hybrid methodology for diagnosing the COVID-19 pneumonia with optimized features from multi-net
    (elsevier, 2022) Kavuran, Gürkan; İn, Erdal; Altıntop Geçkil, Ayşegül; Şahin, Mahmut; Kırıcı Berber, Nurcan
    Purpose The aim of this study was to establish and evaluate a fully automatic deep learning system for the diagnosis of COVID-19 using thoracic computed tomography (CT). Materials and methods In this retrospective study, a novel hybrid model (MTU-COVNet) was developed to extract visual features from volumetric thoracic CT scans for the detection of COVID-19. The collected dataset consisted of 3210 CT scans from 953 patients. Of the total 3210 scans in the final dataset, 1327 (41%) were obtained from the COVID-19 group, 929 (29%) from the CAP group, and 954 (30%) from the Normal CT group. Diagnostic performance was assessed with the area under the receiver operating characteristic (ROC) curve, sensitivity, and specificity. Results The proposed approach with the optimized features from concatenated layers reached an overall accuracy of 97.7% for the CT-MTU dataset. The rest of the total performance metrics, such as; specificity, sensitivity, precision, F1 score, and Matthew Correlation Coefficient were 98.8%, 97.6%, 97.8%, 97.7%, and 96.5%, respectively. This model showed high diagnostic performance in detecting COVID-19 pneumonia (specificity: 98.0% and sensitivity: 98.2%) and CAP (specificity: 99.1% and sensitivity: 97.1%). The areas under the ROC curves for COVID-19 and CAP were 0.997 and 0.996, respectively. Conclusion A deep learning–based AI system built on the CT imaging can detect COVID-19 pneumonia with high diagnostic efficiency and distinguish it from CAP and normal CT. AI applications can have beneficial effects in the fight against COVID-19.
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    The role of endobronchial ultrasound-guided transbronchial needle aspiration in the differential diagnosis of isolated mediastinal and/or hilar lymphadenopathy
    (Wiley, 2021) Temiz, Dilek; İn, Erdal; Kuluöztürk, Mutlu; Kırkıl, Gamze; Artaş, Gökhan; Turgut, Teyfik; Deveci, Figen
    Introduction: Isolated mediastinal and/or hilar lymphadenopathy (IMHL) has become an increasingly common finding as a result of the increased use of thoracic imaging modalities. Endobronchial ultrasound-guided transbronchial needle aspiration (EBUS-TBNA) is accepted as the first step diagnostic method in the differential diagnosis of IMHL. Objective: To determine the diagnostic yield of the procedure and to analyze clinical and sonographic findings that can be used to differentiate the etiology of lymph node pathologies. Methods: Patients who underwent EBUS-TBNA procedure between March 2017 and March 2020 were included in this retrospective study. Demographic data, symptoms, comorbid diseases, and EBUS findings were obtained from the records of the patients. Results: EBUS-TBNA provided a diagnosis in 88 patients out of 120 patients (granulomatous diseases n = 54, malignant diseases n = 21, and anthracotic lymph nodes n = 13), and 32 patients had a negative EBUS-TBNA. 22/32 negative EBUS-TBNA samples were true negatives (reactive lymphadenopathy). The sensitivity of the procedure was 89.8% while negative predict value was 68.7%, diagnostic yield of 91.6%. Patients with reactive lymph nodes had significantly more comorbidities (77.3%–19.4%, p <.001) and a lower number of lymph node stations (1.6 ± 0.8–2.7 ± 0.9, p <.001). Patients with anthracotic lymph nodes were older and mostly consisted of females (11/13, p <.001). Conclusion: EBUS-TBNA has high-diagnostic efficiency in the differential diagnosis of IMHL. The number and size of lymph node stations can provide useful information for differential diagnosis. Clinical follow-up can be a more beneficial approach in patients with reactive and anthracotic lymph nodes before invasive sampling.