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Background/aim: The COVID-19 infection, which started in Wuhan City, China, in December 2019, turned into a pandemic in a very short time, affecting mainly the elderly and those with serious chronic illnesses. COVID-19 infections have been observed to have a high mortality rate, especially in patients undergoing maintenance hemodialysis. Materials and methods: Forty-two patients over 18 years of age who underwent a maintenance hemodialysis program at our unit, who tested positive for COVID-19 by PCR from nasopharyngeal swabs, and/or who were observed to have disease-related signs in their CTs were included in the study. Results: In this study, 23 of 42 patients receiving hemodialysis support in our clinic were included. The median age was 67 years old (min: 35; max: 91 years), and all of our patients had primary hypertension and other comorbidities. Their clinical evaluation showed that dry cough (47.8%) and shortness of breath (47.8%) were the most common symptoms. Fever was less pronounced (30.4%). The median time from the onset of symptoms to hospitalization was 1 day (min: 0; max:), and the time from hospitalization to death was 18 days (min: 1; max: 22). Transfer from the inpatient ward to the ICU took a median of 7 days (min: 1; max: 13). Among the 23 patients, 3 died during follow-up, and 20 were discharged with full recovery. Baseline ferritin, procalcitonin levels, and CRP/albumin rates were higher, and neutrophil/lymphocyte levels were lower in patients who eventually died. In these patients, despite being nonsignificant, there were more diabetic patients, and the D-dimer levels were higher than 1000 ugFEU/L. Conclusion: The COVID-19 infection is associated with increased mortality in chronic kidney diseases patients. Despite being nonsignificant, there was a trend towards increased mortality in patient with diabetes, D-dimer levels >1000 ugFEU/L, higher ferritin and prokalsitonin levels, an increased CRP/albumin ratio, and a lower neutrophil/lymphocyte ratio.
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COVID-19/fisiopatología , Fallo Renal Crónico/terapia , Adulto , Anciano , Anciano de 80 o más Años , Proteína C-Reactiva/metabolismo , COVID-19/complicaciones , COVID-19/metabolismo , COVID-19/mortalidad , Tos/fisiopatología , Estudios Transversales , Disnea/fisiopatología , Femenino , Ferritinas/metabolismo , Fiebre/fisiopatología , Mortalidad Hospitalaria , Humanos , Fallo Renal Crónico/complicaciones , Tiempo de Internación , Recuento de Leucocitos , Recuento de Linfocitos , Masculino , Persona de Mediana Edad , Neutrófilos , Polipéptido alfa Relacionado con Calcitonina/metabolismo , Pronóstico , Diálisis Renal , SARS-CoV-2 , Albúmina Sérica/metabolismo , Factores de TiempoRESUMEN
Aim Magnetic resonance imaging (MRI)-induced anxiety is not infrequent with a reported incidence as high as 37% and the rate of failed MRI imaging due to claustrophobia ranges between 0.5% and 14.5%. The objective of this study was to evaluate the quality and reliability of YouTubeTM videos on MRI claustrophobia. Methods Sixty-five videos were included in the final analysis. Video information analyzed included video length (minutes), video content, qualification of the video uploaders, time of upload, time since upload, the number of total views and the mean daily views, and like counts. We divided the videos according to the uploaders into professional and non-professional groups and further grouped the videos as useful and misleading. Data obtained from the videos were evaluated with three tools including subjective evaluation, Quality Criteria for Consumer Health Information (DISCERN), and Global Quality Scale (GQS) tools. Results The mean video duration was found as 4.14±4.45 minutes. The mean view count was 104.59±408,788.68 and the mean like count was found as 272.55±1096.25. Seventeen (26.15%) videos were uploaded by professionals and 48 (73.85%) by non-professionals. Twenty-eight (43.08%) of the videos were useful and 37 (56.92%) were useless. The mean DISCERN and GQS scores were statistically significantly higher in the professional videos compared to the non-professional videos and in useful videos compared to non-useful videos (for all, p<0.001). Conclusion A majority of the YouTubeTM videos concerning MRI claustrophobia were uploaded by non-professionals. Physicians and other healthcare personnel should be encouraged to provide useful and accurate videos and to direct patients appropriately.
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BACKGROUND/AIM: Determining the severity of acute pancreatitis (AP) is crucial for patient management. The aim of our study was to assess the accuracy and limitations of the Revised Atlanta Criteria (RAC) in determining the severity of AP. MATERIALS AND METHODS: The study was retrospectively conducted on AP patients admitted to the Gastroenterology Department of Sakarya University Faculty of Medicine. The severity, morphology and local complications of AP were evaluated according to the RAC. Laboratory parameters, clinical scores predicting disease severity and Computer Tomography Severity Index scores were assessed. RESULTS: The study group included 113 patients. Ninety-eight (86.7%) had interstitial edematous, and 15 (13.3%) had necrotizing pancreatitis. AP pancreatitis was mild in 69 (61.1%), moderate in 33 (29.2%), and severe in 11 (9.7%). Compared to the moderate group, patients in the severe group had a higher hematocrit, creatinine, SIRS and BISAP scores at admission and more length of hospital stay, more ICU requirements, and higher mortality rates ( P â <â 0.05). Eleven patients had single or multiple persistent organ failure (POF). The mortality rate of patients who developed early POF (nâ =â 6) was higher compared to the group of patients who developed late POF (nâ =â 2) (83.3% and 40%, respectively). CONCLUSION: Severity assessment using the RAC in patients with AP is consistent with laboratory parameters and scoring systems predicting severity. Severe pancreatitis cases who develop early POF may be classified separately.
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Pancreatitis , Humanos , Pancreatitis/diagnóstico por imagen , Estudios Retrospectivos , Enfermedad Aguda , Índice de Severidad de la Enfermedad , Pronóstico , Insuficiencia MultiorgánicaRESUMEN
BACKGROUND: Due to many different reasons such as possible coronavirus colonization in tonsillar tissue, decreased enzymatic antiviral activity, decreased cytokine activity from palatine tonsil tissue and reduced humoral and cellular immune response, tonsillectomy may alter the incidence of Covid-19. AIMS/OBJECTIVES: To reveal the frequency of Covid-19 in patients who underwent tonsillectomy and to analyze the effect of tonsillectomy on the severity of the disease. MATERIALS AND METHODS: Patients aged between 15 and 65 and had a history of tonsillectomy were compared with control group in terms of incidence and severity of Covid-19 disease. RESULTS: A 4% Covid rRT-PCR test positivity rate was detected in patients with tonsillectomy whereas; it was 6.8% in the control group with a statistically significant difference. However, in terms of disease severity there was no difference between the two groups. CONCLUSIONS AND SIGNIFICANCE: It has been proven that tonsillectomy surgery does not pose an additional risk in terms of COVID 19 disease severity. The positive effect of tonsillectomy in terms of disease frequency has been even demonstrated for the first time in the literature.
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COVID-19/epidemiología , Tonsilectomía , Tonsilitis/cirugía , Adolescente , Adulto , Anciano , COVID-19/diagnóstico , Prueba de Ácido Nucleico para COVID-19 , Estudios de Casos y Controles , Femenino , Humanos , Incidencia , Masculino , Persona de Mediana Edad , Pronóstico , Reacción en Cadena de la Polimerasa de Transcriptasa Inversa , Tonsilitis/diagnóstico , Tonsilitis/etiología , Turquía , Adulto JovenRESUMEN
The presented study aims to design a computer-aided detection and diagnosis system for breast dynamic contrast enhanced magnetic resonance imaging. In the proposed system, the segmentation task is performed in two stages. The first stage is called breast region segmentation in which adaptive noise filtering, local adaptive thresholding, connected component analysis, integral of horizontal projection, and breast region of interest detection algorithms are applied to the breast images consecutively. The second stage of segmentation is breast lesion detection that consists of 32-class Otsu thresholding and Markov random field techniques. Histogram, gray level co-occurrence matrix and neighboring gray tone difference matrix based feature extraction, Fisher score based feature selection and, tenfold and leave-one-out cross-validation steps are carried out after segmentation to increase the reliability of the designed system while decreasing the computational time. Finally, support vector machines, k- nearest neighbor, and artificial neural network classifiers are performed to separate the breast lesions as benign and malignant. The average accuracy, sensitivity, specificity, and positive predictive values of each classifier are calculated and the best results are compared with the existing similar studies. According to the achieved results, the proposed decision support system for breast lesion segmentation distinguishes the breast lesions with 86%, 100%, 67%, and 85% accuracy, sensitivity, specificity, and positive predictive values, respectively. These results show that the proposed system can be used to support the radiologists during a breast cancer diagnosis.