ABSTRACT
Background: Governments adopt different policies and strategies to control and reduce the mortality rate of COVID-19. In order to investigate the effect of the adopted policies on the reduction of mortality caused by this disease, the policies implemented by the Regional Headquarter for the Control of COVID-19 Epidemic in Hamedan Province were evaluated. Materials and Methods: The required information was obtained from the Vice-Chancellor of Health of Hamadan University of Medical Sciences and the minutes of the meetings of the Headquarter for the Control of COVID-19 Epidemic in Hamadan Governorate. All the information obtained dates to the period from April to August 2021. A Bayesian network model was used in GeNIe software version 2.2 for the analysis of the information. Results: In this study, seven models were used to evaluate the impact of the adopted strategies. The first model included social distancing, including travel restriction and limiting gatherings, and the mortality rate was estimated to reach 4.72% by implementing the model. The second model includes observing personal hygiene, wearing masks, and vaccination, and the mortality rate was estimated to reach 4.92% by its implementation. The third model encompassed both travel restrictions and business closures, and the mortality rate reached 6.41% after its implementation. Models 4, 5, and 6, which are a combination of the first, second, and third models, have estimated the mortality rate to reach 1.95%, 2.77%, and 2.26%, respectively. In addition, model 7, which combines the above conditions, made the mortality rate reach 2.35%. In the present study, model 6 was selected as the most suitable model with five policies and RMES=0.03005. Conclusion: According to the results obtained in this study, the simultaneous implementation of five policies, including travel restrictions, business closures, personal hygiene, wearing masks and vaccination, can greatly reduce the risk of mortality. © 2022, Bushehr University of Medical Sciences. All rights reserved.
ABSTRACT
Background: Multisystem inflammatory syndrome in children (MIS-C) was first warned by the National Health Service in England following coronavirus disease 2019 (COVID-19) pandemic. Objectives: We aimed to evaluate the clinical and laboratory findings of MIS-C to be used for timely diagnosis and preventing possible complications. Methods: This descriptive study was conducted on 47 patients under 21 years old diagnosed with MIS-C. Results: We found that 25 (53.2%) patients were male, and the median age of participants was 5.58 years. The most common clinical manifestations were fever, rash, conjunctival injection, mucous membrane changes, periorbital edema, gastrointestinal symptoms, respiratory distress, tachycardia, and swollen hands and feet. C-reactive protein and erythrocyte sedimentation rate were elevated in 85 and 45.5% of cases at presentation, respectively. Chest X-ray (CXR) was performed for all cases, and a computed tomography (CT) scan was carried out for patients with severe pulmonary symptoms or abnormal CXR. The results of most CT scans were normal. Decreased myocardial function in echocardiography was detected in more than half of the cases. All patients received intravenous immunoglobulins, and more than 90% received steroids as co-administration therapy or second-line treatment. Conclusions: According to our findings, simultaneous fever, diarrhea, vomiting, and limb or periorbital edema is a key feature for MIS-C diagnosis. Moreover, the evidence of COVID-19 should be assessed in suspected cases of toxic shock syndrome or Kawasaki disease due to highly similar manifestations of these two diseases with MIS-C secondary to COVID-19. © 2022, Author(s). This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/) which permits copy and redistribute the material just in noncommercial usages, provided the original work is properly cited.
ABSTRACT
Background: Identifying the potential risk factors of the length of stay in hospital (LOSH) in COVID-19 patients could help the health system meet future demand for hospital beds. Objectives: This study aimed to determine the factors affecting the length of stay in hospital in COVID-19 patients in Hamadan, the west of Iran. Methods: This cross-sectional study recruited 512 hospitalized COVID-19 patients in Hamadan city. Demographic, clinical, and medical laboratory characteristics of the patients and their survival status were assessed by a checklist. Univariate and multiple negative binomial regressions were used by Stata 12. Results: The median hospitalization length for COVID-19 patients was five days (range: 0 to 47). In the discharged patients, the adjusted incidence rate ratios (95% CI) of LOSH for females, rural residents, patients with a history of diabetes and cardiovascular disease, SPO2 less than 88%, prothrombin time higher than 13 s, platelet count lower than 130 x 1000 mu L, blood sugar higher than 105 mg/dL, and intensive care unit experience were 1.16 (1.03, 1.44), 1.22 (1.03, 1.44), 1.43 (1.07, 1.92), 1.41 (1.23, 1.61), 0.82 (0.71, 0.93), 1.32 (1.11, 1.56), 1.18 (1.03, 1.36), and 1.85 (1.59, 2.17) compared to their references, respectively. Conclusions: Our study added new insight into LOSH determining factors that could be used for future planning in combating the need for hospital beds. The present study revealed that some demographic, social, and clinical variables could increase the IRR of a more extended hospital stay.
ABSTRACT
The coronavirus disease 2019 (COVID-19) pandemic as an emergency public health concern has caused hundreds of thousands of deaths in the world. Identifying predictors of death in COVID-19 patients is a key to improving survival and helping patients triage, better management, and assist physicians and health care. The present study was conducted on 512 positive COVID-19 patients confirmed by real-time PCR hospitalized in Sina Hospital, Hamadan, in 2020. The data of demographic characteristics, clinical manifestations, laboratory findings, chest examination, and disease outcome were collected. The logistic regression model was performed to explore the predictors of in-hospital mortality. Among 512 patients, 57 (11.1%) deaths have occurred. The adjusted odds ratios (OR) estimate of death in COVID-19 for patients with age more than 60 years versus those lower than 60 years was 3.15 (95% CI: 1.06, 9.37). The adjusted OR estimate of death in patients with hypertension comorbidity versus those with no comorbidity was 3.84 (95% CI: 1.27, 11.59). In addition, the adjusted OR estimate (95% CI) of death in patients with respiratory rate above 30 per minute, BUN >20 mg/dL, LDH >942 U/L and SGOT >45 U/L against lower than those values was respectively 10.72 (1.99, 57.68), 5.85 (2.19, 15.63), 13.42 (2.17, 83.22) and 2.86 (1.02, 8.05). The risk of death was higher among the patients with multiple comorbidity diseases, systolic BP lower than 90 mmHg, SPO2 lower than 88 and more than ten days hospitalization in comparison with COVID-19 patients with no comorbidity disease (P=0.002), systolic BP higher than 90 mmHg (P=0.002), SPO2 higher than 88 (P<0.001) and hospitalization for lower than ten days (P=0.012). Our findings suggest that older age, pre-existing hypertension and/or multiple co-morbidities, high respiratory rate, elevated BUN, LDH and SGOT, low systolic BP, and hypoxemia were independently associated with in-hospital mortality in COVID-19 patients. These results can be helpful for physicians and health care workers to improve clinical management and appropriate medical care of COVID-19 patients.