Background: The effect of related factors on recovery or death rates may vary from country to country. Therefore, we aimed to investigate the relationship between demographic, clinical, laboratory factors on the survival rates of confirmed cases of COVID-19 in Shahroud, Iran. Methods: This is an analytical study of the estimation of the survival of patients with COVID-19. Patients who had positive PCR test were considered as COVID-19 cases, and the 2-month survival of these patients was estimated. Among the diseases, heart disease and diabetes were considered as separate variables, and the patients' histories of other diseases were included in the model as comorbidities. Results: Of 396 confirmed patients hospitalized, 109 patients (27.5%) had a history of heart disease, 100 (25.3%) were diabetic, and 80 (20.2%) had a history of other comorbidities. The number of deaths due to the disease was 59 (14.9%). The median age of those who died was 76 years. The multivariate Cox regression analysis shows that heart disease increases hazard ratio more than two times (HR=2.37, 95% CI: 1.33-4.23). The neutrophil-to-lymphocyte ratio (NLR) factor, (HR=1.15, 95% 1.08-1.22), and older age (HR=1.06, 95% CI: 1.03-1.08) increases the risk of death significantly. Conclusion: The heart disease history, NLR factor and older age are associated with death of COVID-19 and may be helpful for the early warning and prediction of disease progression.

A green synthesis approach was conducted to prepare amine-functionalized bio-graphene (AFBG) as an efficient and low cost adsorbent that can be obtained from agricultural wastes. In this study, bio-graphene was successfully used to remove Ciprofloxacin (CIP) from synthetic solutions. The efficacy of adsorbent as a function of operating variables (i.e. pH, time, AFBG dose and CIP concentration) was described by a polynomial model. A optimal99.3% experimental removal was achieved by adjusting the mixing time, AFBG dose, pH and CIP concentration to 58.16, 0.99, 7.47, and 52.9, respectively. Kinetic model revealed that CIP diffusion into the internal layers of AFBG controls the rate of the process. Furthermore, the sorption process was in monolayer with a maximum monolayer capacity of 172.6 mg/g. Adsorption also found to be favored under higher CIP concentrations. The thermodynamic parameters (ΔG˚<0, ΔH˚>0, and ΔS˚>0) demonstrated that the process is endothermic and spontaneous in nature. The regeneration study showed that the AFBG could simply regenerated without significant lost in adsorption capacity.

No abstract

No abstract

Background: Early diagnosis and supportive treatments are essential to patients with coronavirus disease 2019 (COVID-19). Therefore, the current study aimed to determine different patterns of syndromic symptoms and sensitivity and specificity of each of them in the diagnosis of COVID-19 in suspected patients. Study Design: Cross-sectional study Methods: In this study, the retrospective data of 1,539 patients suspected of COVID-19 were obtained from a local registry under the supervision of the officials at Shahroud University of Medical Sciences, Shahroud, Iran. A Latent Class Analysis (LCA) was carried out on syndromic symptoms, and the associations of some risk factors and latent subclasses were accessed using one-way analysis of variance and Chi-square test. Results: The LCA indicated that there were three distinct subclasses of syndromic symptoms among the COVID-19 suspected patients. The age, former smoking status, and body mass index were associated with the categorization of individuals into different subclasses. In addition, the sensitivity and specificity of class 2 (labeled as "High probability of polymerase chain reaction [PCR]+ ") in the diagnosis of COVID-19 were 67.43% and 76.17%, respectively. Furthermore, the sensitivity and specificity of class 3 (labeled as "Moderate probability of PCR+ ") in the diagnosis of COVID-19 were 75.92% and 50.23%, respectively. Conclusions: The findings of the present study showed that syndromic symptoms, such as dry cough, dyspnea, myalgia, fatigue, and anorexia, might be helpful in the diagnosis of suspected COVID-19 patients.