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    Differentiation of Acute Rhinosinusitis From Chronic Rhinosinusitis Using Multidetector Computed Tomography
    (2019) Erkoç, Mustafa Fatih; Öztoprak, Bilge; Doğan, Mansur; Göksungur, Gürol
    It is difficult to differentiate acute from chronic rhinosinusitis clinically, and to date they are assessedradiologically via air-fluid level or opacification, which can appear similar in both cases. Our purpose was toexamine whether air density analysis combined with classical radiological approaches can be used as a newtool to differentiate between acute and chronic sinusitis.This retrospective study included a total of 2419 sinuses in 550 patients who underwent paranasal sinusmultidetector computed tomography (MDCT). Patients were divided into three groups according to clinicaldiagnosis of sinus status: acutely inflamed as group 1 (n=176), the chronic sinusitis as group 2 (n=191) andhealthy sinuses (n=183) as group 3, the control group. The mean air density and standard deviations (SD)within the paranasal sinuses in each group were calculated by the measurements of air density with a regionof interest (ROI) of 0.5 cm2, located in the center of the air-filled sinus avoiding the sinus wall, and repeatedthe measurement in 4-6 consequent CT slices, where available.The mean air density was significantly higher in group 1 compared with group 2 and 3 (- 810 HU,-973 HUand -1010 HU respectively; p < 0.05), as well as SD (89.3 HU, 21.1 HU and 20.9 HU respectively; p < 0.05).In conclusion; increased air density in paranasal sinuses may aid in distinguishing acute from chronicrhinosinusitis.
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    Öğe
    Evaluating the clinical, radiological, microbiological, biochemical parameters and the treatment response in COVID-19 pneumonia
    (2022) Mutlu, Pınar; Mirici, Nihal Arzu; Gönlügür, Uğur; Öztoprak, Bilge; Özer, Şule; Resorlu, Mustafa; Akçalı, Alper
    Aim: The coronavirus disease (COVID-19) has led to over 200,000,000 confirmed cases and over 4,250,000 confirmed deaths worldwide. The present study aimed to explore the links between epidemiological, clinical, biochemical, microbiological, and radiological data and treatment responses of inpatients with COVID-19 pneumonia. Material and Method: The study included 131 patients hospitalized for COVID-19 pneumonia. Laboratory values such as complete blood count, coagulation profile, AST, LDH, sedimentation, CRP, BUN, creatinine, and D-dimer of the patients were analyzed. The diagnosis of COVID-19 was established by RT-PCR testing of respiratory tract samples. Thoracic CT images were used to determine the severity of involvement in patients. Statistical analyses were performed to establish the differences between the groups and the relationships between the variables. Results: The most common comorbidities of the patients were hypertension (35.1%) and diabetes mellitus (24.5%). The patients with fever, cough, and dyspnea and who were PCR positive had the highest radiological involvement severity score. The involvement severity scores were negatively correlated with the lymphocyte count, lymphocyte percentage, and albumin levels (p<0.05). Concerning prognostic risk factors, the mean percentages of lymphocytes and eosinophils were significantly higher in the fully recovered patients than those in the intensive care unit (p<0.05). Conclusion: Our study identified the percentages of lymphocytes and eosinophils as prognostic factors. Identifying the risk factors that predict the possibility of disease progression on admission may contribute to physicians' patient management, increase the therapeutic effect, and reduce the COVID-19 mortality rate.