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Background: The outbreak of acute respiratory syndrome with novel coronavirus 2019 (COVID-19) in December 2019 in Wuhan, China, caused a worldwide outbreak of the disease. To treat the disease, some drugs were identified and introduced that did not show a significant effect on the recovery of the disease. Due to the need to manage inpatient beds, this study was conducted to evaluate the effectiveness of Remdesivir in the treatment of outpatients with moderate to severe COVID-19. Method(s): The present study was a retrospective cohort with a convenience sampling method. It was conducted by referring to the records of COVID-19 patients who were referred to the respiratory clinic of Shahid Beheshti Hospital as outpatients in the period from April to August 2021. Result(s): This study was conducted on 263 COVID-19 patients with a mean age of 51.16+/-14.39 years from 19 and 90 years old. Data were collected through a researcher-made checklist and analyzed using SPSS 20. Kolmogorov-Smirnov test, paired t-test, and Mc Nemar's test were used to evaluate the data. The significance level was considered at the level of 0.05. Conclusion(s): Findings revealed that no clear correlation was found between hospitalization and death rate compared to other patients. In our study, the risk factors for severe COVID-19 did not affect the rate of hospitalization or death of patients.Copyright © 2023 Bentham Science Publishers.
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Objective: To report the maternal death due to COVID-19. Method(s): A total of 14 maternal deaths due to severe and critical COVID-19 who were referred to the obstetric department of Nekouie-Forghani-Hedayati Hospital, Qom, Iran from December 2019 to May 2022 were collected. The clinical manifestations and maternal and perinatal outcomes were analyzed. Result(s): Dexamethasone was used in 7 cases, while remdesivir was used in 5 cases. Acute respiratory distress syndrome, multiple organ failure, and sepsis were the main cause of mother death. The pregnancy in 8 cases were terminated by caesarean and only one neonatal death was reported from a mother at 13th week of gestational age, while all other fetus delivered were healthy and alive. Conclusion(s): COVID-19 in pregnancy is an emergency. Critical appraisal is needed to detect the other comorbidities and positive PCR test by throat swap should be performed as soon as possible. Copyright ©2022 Journal of Acute Disease Produced by Wolters Kluwer-Medknow.
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Background and Objectives: Black myrobalan drug, known as "Imam Kazem drug" in Iran, is used by most of Iranian people to prevent and treat the coronavirus disease 2019 (COVID-19). This study aims to investigate the consumption pattern of black myrobalan by people in Qom, Iran and their attitudes towards it.
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Background: Coronavirus is one of the major pathogens of the human respiratory system and a major threat to the human health. Objectives: This modeling study aimed to project the epidemics trend of coronavirus disease 2019 (COVID-19) in Qom, Iran Methods: This study projected the COVID-19 outbreak in Qom using a modified susceptible-exposed-infectious-recovered (SEIR) compartmental model by the end of December 2020. The model was calibrated based on COVID-19 epidemic trend in Qom from 1 January to 11 July. The number of infected, hospitalized, and death cases were projected by 31 December. A Monte Carlo uncertainty analysis was applied to obtain 95% uncertainty interval (UI) around the estimates. Results: According to the results, the reduced contact rate and increased isolation rate were effective in reducing the size of the epidemic in all scenarios. By reducing the contact rate from eight to six, the number of new cases on the peak day, as well as the total number of cases admitted to the hospital by the end of the period (31 December), decreased. For example, in Scenario A, compared to Scenario E, with a decrease in contact rate from eight to six, the number of new cases on peak days decreased from 15,700 to 1,100. The largest decrease in the number of new cases on peak days was related to Scenario F with 270 cases. Also, the total number of cases decreased from 948,000 to 222,000 between the scenarios, and the largest decrease in this regard was related to Scenario F, with 188,000 cases. Conclusions: The parameters of contact rate and isolation rate can reduce the number of infected cases and prevent the outbreak, or at least delay the onset of the peak. This can help health policymakers and community leaders to upgrade their health care
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Objective: To identify the incidence rate, relative risk, hotspot regions and incidence trend of COVID-19 in Qom province, northwest part of Iran in the first stage of the pandemic. Methods: The study included 1 125 officially reported PCR-confirmed cases of COVID-19 from 20 February 2020 to 20 April 2020 in 90 regions in Qom city, Iran. The Bayesian hierarchical spatial model was used to model the relative risk of COVID-19 in Qom city, and the segmented regression model was used to estimate the trend of COVID-19 incidence rate. The Poisson distribution was applied for the observed number of COVID-19, and independent Gamma prior was used for inference on log-relative risk parameters of the model. Results: The total incidence rate of COVID-19 was estimated at 89.5 per 100 000 persons in Qom city (95% CI: 84.3, 95.1). According to the results of the Bayesian hierarchical spatial model and posterior probabilities, 43.33% of the regions in Qom city have relative risk greater than 1;however, only 11.11% of them were significantly greater than 1. Based on Geographic Information Systems (GIS) spatial analysis, 10 spatial clusters were detected as active and emerging hotspot areas in the south and central parts of the city. The downward trend was estimated 10 days after the reporting of the first case (February 7, 2020);however, the incidence rate was decreased by an average of 4.24% per day (95%CI:-10.7, -3.5). Conclusions: Spatial clusters with high incidence rates of COVID-19 in Qom city were in the south and central regions due to the high population density. The GIS could depict the spatial hotspot clusters of COVID-19 for timely surveillance and decision-making as a way to contain the disease.