Introduction:Recently, a new strain of coronaviruses, which originated from Wuhan City, Hubei Province, China has been identified. According to the high prevalence of new coronavirus, further investigation on the clinical and paraclinical features of this disease seems essential. Hence, we carried out this systematic review and meta-analysis to figure out the unknown features. Methods:This study was performed using databases of Web of Science, Scopus and PubMed.We considered English cross-sectional and case-series papers which reported clinical, radiological, and laboratory characteristics of patients with COVID-19. We used STATA v.11 and random effect model for data analysis. Results:In the present meta-analysis, 32 papers including 49504 COVID-19 patients were studied.The most common clinical symptoms were fever (84%), cough (65%) and fatigue (42%), respectively. The most common radiological and paraclinical features were bilateral pneumonia (61%), ground-glass opacity (50%), thrombocytopenia (36%) and lymphocytopenia (34%). The study also showed that the frequency of comorbidities and early symptoms was higher in critically severe patients. Moreover, we found the overall mortality rate of three percent.Conclusion: According to that there are many cases without Computed Tomography Scan findings or clear clinical symptoms, it is recommended to use other confirming methods such RNA sequencing in order to identification of suspicious undiagnosed patients. Moreover, while there is no access to clinical and paraclinical facilities in in public places such as airports and border crossings, it is recommended to consider factors such as fever, cough, sputum and fatigue.

Introduction: Recently, a new strain of coronaviruses, which originated from Wuhan City, Hubei Province, China has been identified. According to the high prevalence of new coronavirus, further investigation on the clinical and paraclinical features of this disease seems essential. Hence, we carried out this systematic review and meta-analysis to figure out the unknown features. Methods:  This study was performed using databases of Web of Science, Scopus and PubMed. We considered English cross-sectional and case-series papers which reported clinical, radiological, and laboratory characteristics of patients with COVID-19. We used STATA v.11 and random effect model for data analysis. Results: In the present meta-analysis, 32 papers including 49504 COVID-19 patients were studied. The most common clinical symptoms were fever (84%), cough (65%) and fatigue (42%), respectively. The most common radiological and paraclinical features were bilateral pneumonia (61%), ground-glass opacity (50%), thrombocytopenia (36%) and lymphocytopenia (34%). The study also showed that the frequency of comorbidities and early symptoms was higher in critically severe patients. Moreover, we found the overall mortality rate of three percent. Conclusion: According to that there are many cases without Computed Tomography Scan findings or clear clinical symptoms, it is recommended to use other confirming methods such RNA sequencing in order to identification of suspicious undiagnosed patients. Moreover, while there is no access to clinical and paraclinical facilities in in public places such as airports and border crossings, it is recommended to consider factors such as fever, cough, sputum and fatigue.

This study was performed to systematically asses the risk of secondary malignancies in patients with ovarian cancer. We conducted a systematic search in PubMed, Web of Science, and Scopus databases up to September 2019 to find target studies. In this study, the overall SIR has been calculated with fixed/random-effects models. Sixteen cohort studies including 122715 ovarian cancer patients with 4458 secondary malignancies have been included in this meta-analysis. Combined SIRs showed an increased risk of secondary malignancies prevalence (SIR: 1.81, 95%CI 1.58-2.03). The most prevalence diagnosed malignancies were as follows: breast cancer (1.34, 95%CI 1.5-1.18), intestine (2.36, 95%CI 1.11-3.61), colorectal (1.73, 95%CI 1.44-2.02), pancreatic (1.42, 95%CI 1.13-1.71), cervical cancer (11.57, 95%CI 6.94-16.21), renal (1.43, 95%CI 1.11-1.74), bladder (2.13, 95%CI 1.77-2.50), leukemia (3.33, 95%CI 2.23-4.43), connective tissue (2.61, 95%CI 1.56-3.66), and thyroid (1.59, 95%CI 1.13-2.04). In regards to the results, various malignancies have a greater prevalence in patients with ovarian cancer in comparison to the general public. Corpus cancer, leukemia cancer, endometrium cancer, connective tissue malignancy, and bladder cancer are among the high risks in these patients and need to be considered for them. Hence, the survival rate of the patients can be increased through prevention and early diagnosis.