Comparing the severity of Outcomes of SARS-CoV-2 between RT-PCR-positive and RT-PCR-negative Individuals in Iran Comparing the severity of Outcomes of SARS-CoV-2 between RT-PCR-positive and RT-PCR-negative Individuals in Iran (preprint)

The aim of this study was to compare the outcomes of SARS-CoV-2 RT-PCR-positive and RT-PCR negative Patients in Iran. This cohort study performed on 81393 patients with COVID-19 in six provinces of Iran during 2020. The studied variables include demographic and clinical. To examine the associations between RT-PCR test and death or ICU admission as dependent variable the multiple Bayesian logistic regression model was used by R software. 81393 individual (44.9 % female) with a mean age of 52.98 ± 20.8 years were included to the analysis. At all, 25434 tests (31.2 %) were positive RT-PCR, including 10772 men (44.9%) and 14662 women (55.1%). The multiple Bayesian logistic regression model showed a significant positive association between RT-PCR test results and COVID-19 mortality rate (OR: 1.46; 95% Crl: 1.29- 1.64). Also, males, older age, individual with chronic disease have higher risk of COVID-19 death, however, negative association observed between history of contact and COVID-19 death. We observed a significant inverse association between RT-PCR test results and ICU admission, while, the risk of ICU admission increased significantly by 1.2 times (95% Crl for odds ratio: 1.09, 1.34) among patients with negative RT-PCR test compared to positive RT-PCR test. People with positive RT-PCR test, male gender, older age, having a history of underlying disease have a higher risk of death and hospitalization in the ICU. Therefore, paying attention to these factors will be effective in reducing the risk of death and hospitalization in ICU.

Health States Utility Value in COVID-19 (preprint)

Background: The main aim of the study was extract the health utility value of coronavirus 2019 (COVID-19) disease.Methods: In a cross-sectional study in Iran, 320 randomly selected treated patients from COVID-19 is studied. To collect the required data, we applied a questionnaire that included socio-demographic factors, clinical characteristics, and questions on the patients’ Health-Related Quality of Life (HRQoL). Time trade-off (TTO) approach is used to measure the lost HRQoL attributed to COVID-19. Besides, we applied a two-limit Tobit regression model to determine the effects of the socio-demographic factors on the patients’ health utility and used the visual analogue scale approach to estimate the perceived total current health status.Results: The overall mean (SE) and median (IQR) of the health utility values were 0.863 (0.01) and 0.909 (0.21), respectively. This values for those who were willing to trade time in exchange for perfect health estimated at 0.793 (0.01) and 0.848 (0.17), respectively. The lowest amount of utility value were belonged to the elderly (mean (SE) = 0.742 (0.04); median (IQR) = 0.765 (0.42)) and those lived in rural (mean (SE)) = 0.804 (0.03); median (IQR) = 0.877 (0.30)). The univariate analysis shows that age, location living, and household size factors have a statistically significant effect on the health utility. The regression model's findings indicate that the participants' age and hospitalization status were the key determinants of COVID-19 health utility value.Conclusion: COVID-19 is associated with a substantial and measurable diminution in HRQoL. This diminution in HRQoL can be directly compared with that induced by systemic health states.

Association of olfactory dysfunction with hospitalization for COVID-19: a multicenter study in Kurdistan (preprint)

Objective: To evaluate the association of olfactory dysfunction (OD) with hospitalization for COVID-19. Study Design: Multi-center cohort study. Setting: Emergency departments of thirteen COVID-19-designed hospitals in Kurdistan province, Iran. Subjects and Methods: Patients presenting with flu-like symptoms who tested positive by RT-PCR for COVID-19 between May 1st and 31st, 2020. At the time of presentation and enrollment, patients were asked about the presence of OD, fever, cough, shortness of breath, headache, rhinorrhea and sore throat. The severity of OD was assessed on an 11-point scale from 0 (none) to 10 (anosmia). Patients were either hospitalized or sent home for outpatient care based on standardized criteria. Results: Of 203 patients, who presented at a mean of 6 days into the COVID-19 disease course, 25 patients (12.3%) had new OD and 138 patients (68.0%) were admitted for their COVID-19. Patients admitted for COVID-19 had a higher prevalence of all symptoms assessed, including OD (p<0.05 in all cases), and OD identified admitted patients with 84.0% sensitivity and 34.3% specificity. On univariate logistic regression, hospitalization was associated with OD (odds ratio [OR] = 2.47, 95%CI: 1.085-6.911, p=0.049). However, hospitalization for COVID-19 was not associated with OD (OR=3.22, 95% CI: 0.57-18.31, p=0.188) after controlling for confounding demographics and comorbidities. Conclusion: OD may be associated with hospitalization for (and therefore more severe) COVID-19. However, this association between OD and COVID-19 severity is more likely driven by patient characteristics linked to OD, such as greater numbers of COVID-19 symptoms experienced or high-risk comorbidities.

Clinical Manifestation and Maternal Complications and Neonatal outcomes in Pregnant Women with COVID 19: An Update a Systematic Review and Meta-analysis (preprint)

Background Existing evidence indicates that the risk of obstetric and perinatal outcomes is higher in women with coronavirus infection. outbreaks suggest that pregnant women and their fetuses are particularly susceptible to poor outcomes. However, there is little known about pregnancy related complications and co-morbidity in this group of women. Therefore, this, systematic review and meta-analysis performed in order to find out whether COVID-19 may cause different manifestations and outcomes in antepartum and postpartum period or not.Methods We searched databases, including Medline (PubMed), Embase, Scopus, Web of sciences, Cochrane library, Ovid and CINHAL to retrieve all articles reporting the prevalence of maternal and neonatal complications, in addition clinical manifestations, in pregnant women with COVID 19 that published with English language from January to April 2020. Results 11 studies with total 177 pregnant women included in this systematic review.Results show that the pooled prevalence of neonatal mortality, lower birth weight, stillbirth, premature birth, and intrauterine fetal distress in women with COVID 19 were 4% (95% Cl: 1 - 9%), 21% (95% Cl: 11 – 31%), 2% (95% Cl: 1 - 6%), 28% (95% Cl: 12 - 44%), and 15% (95% Cl: 4 - 26%); respectively. Also the pooled prevalence of fever, cough, diarrhea and dyspnea were 56% (95% Cl: 30 - 83%), 30% (95% Cl: 21 - 39%), 9% (95% Cl: 2 - 16%), and 3% (95% Cl: 1 - 6%) in the pregnant women with COVID-19.Conclusion According to this systematic review and meta-analysis, the pregnant women with COVID-19 with or without pneumonia, are at a higher risk of pre-eclampsia, preterm birth, miscarriage and cesarean delivery. Furthermore, the risk of LBW and intrauterine fetal distress seems increased in neonates.

Can judgments according to case fatality rate be correct all the time during epidemics? Some lessons from Coronavirus 2019-nCoV case fatality rate index in Iran (preprint)

Background: Coronavirus 2019-nCoV was first identified in China in 2019. One of the most important indices noticed by experts, policymakers and managers which is daily evaluated in epidemics and a lot of judgments are made based on it, is case fatality rate (CFR) index of the disease. CFR can change during epidemics. This study aims to calculate CFR index for nCov-2019 in Iran and answer the following question: Is it right to base judgment on CFR all the time during epidemics and is it right to judge based on that since the outbreak of an epidemic?Methods: This research is a descriptive study. Its required data was obtained from the website of The Ministry of Health and Medical Education of Iran from February 20th 2020 until March 14th 2020. CFR index was calculated when the death toll of a disease is divided by the total number of people infected by that disease. Excel 2013 software was used to a1nalyze the data.Results: According to the findings of this study, In Iran, until March 14th 2020, 11364 people have been infected by Coronavirus 2019-nCoV and 514 people died of it. CFR index had a descending trend and it was 100%, 18.6%, 8.8%, 3.1%, 3.3%, 4.5% on the first, fifth, tenth, fifteenth, twentieth and twenty fifth day, respectively. Conclusion: In emerging epidemics, an index must not be based to judge a health system’s performance until that epidemics condition has not been clarified. It would be suggested that in the outbreak of an epidemic, specifically emerging diseases, CFR must not be the base of judgment. Making judgments, specifically, in the outbreak of emerging epidemics based on fatality rate can lead to an information bias.

A model for COVID-19 prediction in Iran based on China parameters (preprint)

Background: The rapid spread of COVID-19 virus from China to other countries and outbreaks of disease require an epidemiological analysis of the disease in the shortest time and an increased awareness of effective interventions. The purpose of this study was to estimate the COVID-19 epidemic in Iran based on the SIR model. The results of the analysis of the epidemiological data of Iran from January 22 to March 8, 2020 were investigated and the prediction was made until March 29, 2020. Methods: By estimating the three parameters of time-dependent transmission rate, time-dependent recovery rate, and time-dependent mortality rate from Covid-19 outbreak in China, and using the number of Covid-19 infections in Iran, we predicted the number of patients for the next month in Iran. Each of these parameters was estimated using GAM models. All analyses were conducted in R software using the mgcv package. Findings: On average, 925 people with COVID-19 are expected to be infected daily in Iran. The epidemic peaks within one week (15.03.2020 to 03.21.2020) and reaches its highest point on 03.18.2020 with 1126 infected cases. Conclusion: The most important point is to emphasize the timing of the epidemic peak, hospital readiness, government measures and public readiness to reduce social contact.