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Background: The coronavirus disease (COVID-19) pandemic has made a great impact on health-care services. The prognosis of the severity of the disease help reduces mortality by prioritizing the allocation of hospital resources. Early mortality prediction of this disease through paramount biomarkers is the main aim of this study. Materials and Methods: In this retrospective study, a total of 205 confirmed COVID-19 patients hospitalized from June 2020 to March 2021 were included. Demographic data, important blood biomarkers levels, and patient outcomes were investigated using the machine learning and statistical tools. Results: Random forests, as the best model of mortality prediction, (Matthews correlation coefficient = 0.514), were employed to find the most relevant dataset feature associated with mortality. Aspartate aminotransferase (AST) and blood urea nitrogen (BUN) were identified as important death-related features. The decision tree method was identified the cutoff value of BUN >47 mg/dL and AST >44 U/L as decision boundaries of mortality (sensitivity = 0.4). Data mining results were compared with those obtained through the statistical tests. Statistical analyses were also determined these two factors as the most significant ones with P values of 4.4 × 10 −7 and 1.6 × 10 −6 , respectively. The demographic trait of age and some hematological (thrombocytopenia, increased white blood cell count, neutrophils [%], RDW-CV and RDW-SD), and blood serum changes (increased creatinine, potassium, and alanine aminotransferase) were also specified as mortality-related features ( P < 0.05). Conclusions: These results could be useful to physicians for the timely detection of COVID-19 patients with a higher risk of mortality and better management of hospital resources.

Background<br />This paper mainly focuses on patients with ruptured pulmonary Echinococcus granulosus infections (alveolar hydatid disease), who suffered from ruptured alveolar hydatid cyst. In this study we aimed to remove these ruptured central and peripheral pulmonary hydatid cysts by the bronchoscopic saline injection method (ME Hejazi method). <br /><br />Case description<br />In this retrospective study, we evaluated eight patients from an endemic area who were non-surgically treated for ruptured pulmonary hydatid cysts at Imam Reza hospital between 2016-2017. By the bronchoscopic saline injection method (ME Hejazi method), we extracted the entire hydatid cysts of all patients by fiber optic bronchoscopy for the detachment of the underlying membrane from the cavity wall. There were three female and five male patients, with a mean age of 40 ± 23 years (range 17–63 years). Ruptured cysts were located in the peripheral (2) and central (6) parts of the lungs. All of our experiences have been successful without any complications and residual cyst membrane. During the follow-ups, clinical and radiological recovery were seen in these patients.<br /><br />Conclusions<br />In the peripheral ruptured hydatid cysts, accurate recognition and location of the cyst is essential and the blind approach is not recommended because it needs several bronchoscopic interventions. Therefore the Hejazi method will be a beneficial and suitable alternative method for surgery in the treatment of patients with ruptured pulmonary hydatid cyst with cyst membrane adhesions.