METHODS: A total of 828 confirmed cases of COVID-19 with definite outcomes were retrospectively identified from open access individual-level worldwide data. Univariate followed by multivariable regression analysis were used to evaluate the association between potential risk factors and mortality.
RESULTS: Majority of the patients were males 59.1% located in Asia 69.3%. Based on the data, older age (adjusted odds ratio (aOR), 1.079; 95% confidence intervals (95% CI), 1.064-1.095 per year increase), males (aOR, 1.607; 95% CI, 1.002-2.576), patients with hypertension (aOR, 3.576; 95% CI, 1.694-7.548), diabetes mellitus (aOR, 12.234; 95% CI, 4.126-36.272), and patients located in America (aOR, 7.441; 95% CI, 3.546-15.617) were identified as the risk factors of mortality among COVID-19 patients.
CONCLUSIONS: Males, advanced age, hypertension patients, diabetes mellitus patients, and patients located in America were the independent risk factors of death among COVID-19 patients. Extra attention is required to be given to these factors and additional studies on the underlying mechanisms of these effects.
METHODS: Electronic databases and country-specific healthcare databases were searched to identify relevant studies/reports. The quality assessment of individual studies was conducted using the Newcastle-Ottawa Scale. Country-specific proportion of individuals with COVID-19 who developed ARDS and reported death were combined in a random-effect meta-analysis to give a pooled mortality estimate of ARDS.
RESULTS: The overall pooled mortality estimate among 10,815 ARDS cases in COVID-19 patients was 39% (95% CI: 23-56%). The pooled mortality estimate for China was 69% (95% CI: 67-72%). In Europe, the highest mortality estimate among COVID-19 patients with ARDS was reported in Poland (73%; 95% CI: 58-86%) while Germany had the lowest mortality estimate (13%; 95% CI: 2-29%) among COVID-19 patients with ARDS. The median crude mortality rate of COVID-19 patients with reported corticosteroid use was 28.0% (lower quartile: 13.9%; upper quartile: 53.6%).
CONCLUSIONS: The high mortality in COVID-19 associated ARDS necessitates a prompt and aggressive treatment strategy which includes corticosteroids. Most of the studies included no information on the dosing regimen of corticosteroid therapy, however, low-dose corticosteroid therapy or pulse corticosteroid therapy appears to have a beneficial role in the management of severely ill COVID-19 patients.
MATERIAL AND METHODS: A validated database was used to generate data related to countries with declared lockdown. Simple regression analysis was conducted to assess the rate of change in infection and death rates. Subsequently, a k-means and hierarchical cluster analysis was done to identify the countries that performed similarly. Sweden and South Korea were included as counties without lockdown in a second-phase cluster analysis.
RESULTS: There was a significant 61% and 43% reduction in infection rates 1-week post lockdown in the overall and India cohorts, respectively, supporting its effectiveness. Countries with higher baseline infections and deaths (Spain, Germany, Italy, UK, and France-cluster 1) fared poorly compared to those who declared lockdown early on (Belgium, Austria, New Zealand, India, Hungary, Poland and Malaysia-cluster 2). Sweden and South Korea, countries without lock-down, fared as good as the countries in cluster 2.
CONCLUSION: Lockdown has proven to be an effective strategy is slowing down the SARS-CoV-2 disease progression (infection rate and death) exponentially. The success story of non-lock-down countries (Sweden and South Korea) need to be explored in detail, to identify the variables responsible for the positive results.
METHODS: This is an international, multicenter, hospital-based study on stroke incidence and outcomes during the COVID-19 pandemic. We will describe patterns in stroke management, stroke hospitalization rate, and stroke severity, subtype (ischemic/hemorrhagic), and outcomes (including in-hospital mortality) in 2020 during COVID-19 pandemic, comparing them with the corresponding data from 2018 and 2019, and subsequently 2021. We will also use an interrupted time series (ITS) analysis to assess the change in stroke hospitalization rates before, during, and after COVID-19, in each participating center.
CONCLUSION: The proposed study will potentially enable us to better understand the changes in stroke care protocols, differential hospitalization rate, and severity of stroke, as it pertains to the COVID-19 pandemic. Ultimately, this will help guide clinical-based policies surrounding COVID-19 and other similar global pandemics to ensure that management of cerebrovascular comorbidity is appropriately prioritized during the global crisis. It will also guide public health guidelines for at-risk populations to reduce risks of complications from such comorbidities.
MATERIALS AND METHODS: Lethality was calculated as the rate of deaths in a determinate moment from the outbreak of the pandemic out of the total of identified positives for COVID-19 in a given area/nation, based on the COVID-John Hopkins University website. Lethality of countries located within the 5th parallels North/South on 6 April and 6 May 2020, was compared with that of all the other countries. Lethality in the European areas of The Netherlands, France and the United Kingdom was also compared to the territories of the same nations in areas with a non-temperate climate.
RESULTS: A lower lethality rate of COVID-19 was found in Equatorial countries both on April 6 (OR=0.72 CI 95% 0.66-0.80) and on May 6 (OR=0.48, CI 95% 0.47-0.51), with a strengthening over time of the protective effect. A trend of higher risk in European vs. non-temperate areas was found on April 6, but a clear difference was evident one month later: France (OR=0.13, CI 95% 0.10-0.18), The Netherlands (OR=0.5, CI 95% 0.3-0.9) and the UK (OR=0.2, CI 95% 0.01-0.51). This result does not seem to be totally related to the differences in age distribution of different sites.
CONCLUSIONS: The study does not seem to exclude that the lethality of COVID-19 may be climate sensitive. Future studies will have to confirm these clues, due to potential confounding factors, such as pollution, population age, and exposure to malaria.