ABSTRACT
BackgroundThere is inconclusive evidence whether pregnancy exacerbates COVID-19 symptoms or not, and scarce data from the Middle East and North Africa region. The aim of this study was to investigate the association between pregnancy and COVID-19 symptoms in Qatar. MethodsThis cross-sectional study was carried out using data of all women with confirmed COVID-19, comparing pregnant and non-pregnant women of child-bearing age (18-49 years). Data of all COVID-19 cases were collected by the Ministry of Public Health (MoPH) in Qatar, between March and September 2020. Symptoms were compared by pregnancy status and classified into moderate and severe. Multivariable logistic and poisson regression was carried out to investigate the association between pregnancy and severity of COVID-19 symptoms. ResultsDuring the study period, 105744 individuals were diagnosed with COVID-19, 16908 were women of childbearing age. From that sample, 799 women who were pregnant (mean age 29.9 years (SD 5.2)) and 16109 women who were not pregnant (mean age 33.1 years (SD 7.8)). After multivariable logistic regression, pregnancy was associated with a 1.4-fold higher odds of reporting any symptoms of COVID-19 (OR 1.41, 95% CI 1.18-1.68), and 1.3-fold higher odds of reporting shortness of breath (OR 1.29, 95% CI 1.02-1.63). After multivariable poisson regression, pregnancy was also associated with a higher number of symptoms (IRR 1.03, 95%CI 0.98-1.08). ConclusionOur findings suggest that, in this setting, pregnant women are more likely to have symptomatic COVID-19, and shortness of breath, compared to non-pregnant women of childbearing age.
ABSTRACT
ObjectiveTo synthesize findings from systematic reviews and meta-analyses on the efficacy and safety of chloroquine (CQ) and hydroxychloroquine (HCQ) with or without Azithromycin for treating COVID-19, and to update the evidence using a meta-analysis. MethodsA comprehensive search was carried out in electronic databases for systematic reviews, meta-analyses and experimental studies which investigated the efficacy and safety of CQ, HCQ with or without Azithromycin to treat COVID-19. Findings from the reviews were synthesised using tables and forest plots and the quality effect model was used for the updated meta-analysis. The main outcomes were mortality, the need for intensive care services, disease exacerbation, viral clearance and occurrence of adverse events. ResultsThirteen reviews with 40 primary studies were included. Two meta-analyses reported a high risk of mortality, with ORs of 2.2 and 3.0, and the two others found no association between HCQ and mortality. Findings from two meta-analyses showed that HCQ with Azithromycin increased the risk of mortality, with similar ORs of 2.5. The updated meta-analysis of experimental studies showed that the drugs were not effective in reducing mortality (RR 1.1, 95%CI 1.0-1.3, I2 =0.0%), need for intensive care services (OR 1.1, 95%CI 0.9-1.4, I2 =0.0%), virological cure (OR 1.5, 95%CI 0.5-4.4, I2 =39.6%) or disease exacerbation (OR 1.2, 95%CI 0.3-5.9, I2 =31.9%) but increased the odds of adverse events (OR 12,3, 95%CI 2.5-59.9, I2 =76.6%). ConclusionThere is conclusive evidence that CQ and HCQ, with or without Azithromycin are not effective in treating COVID-19 or its exacerbation. RegistrationPROSPERO: CRD42020191353
ABSTRACT
BackgroundThe reported crude case fatality rate (CFR) for COVID-19 varies considerably across countries. Crude CFRs could by biased by larger proportions of older COVID-19 cases in population data, who are also at increased mortality risk. Such distorted age case structures are a common feature of selective COVID 19 testing strategies in many countries, and they potentially mask underlying differences arising from other important factors such as health system burden. MethodsWe used the method of direct case-age standardisation to evaluate the effects of age variations on CFRs. Data on cases and death by age from Italy, Spain, China, Australia and South Korea were analysed to derive standardised CFRs. Findings were compared across different case age distribution references as standards. ResultsUsing the South Korean case age distribution as a standard, the fivefold higher crude CFR for Italy is reduced to less than two-fold after adjustment, while the crude CFR difference for Spain is virtually eliminated. The adjusted CFR for Australia is the lowest among all countries. DiscussionMortality differences based on crude CFRs are exaggerated by age structures, which are effectively controlled by case age standardization. Residual CFR differences could be attributed to health and health system factors. The South Korean case age distribution is an appropriate reference standard, given its robust case detection and contact tracing program. Till reliable population level indicators of incidence and mortality are available, the age-standardized CFR could be a viable option for international comparison of the impact of the COVID 19 epidemic. SummaryO_ST_ABSThe knownC_ST_ABSThere are intense debates around the magnitude of and reasons for wide variations in observed case fatality rates (CFRs) from COVID 19 across countries. Age is commonly speculated as a reason, but this has not been technically quantified or explained. The newThe technique of direct standardization using reference distributions of case age structures eliminates the effects of age on CFR, thus enhancing the comparability as well as understanding of differentials The implicationsResidual differences between adjusted CFRs can be used to infer health and health system factors that influence mortality in COVID 19 cases in different populations
ABSTRACT
BackgroundCOVID19 is worldwide pandemic that is mild in the majority of patients but can result in a pneumonia like illness with progression to acute respiratory distress syndrome and death. Predicting the disease severity at time of diagnosis can be helpful in prioritizing hospital admission and resources. MethodsWe prospectively recruited 1096 consecutive patients with COVID19 from the Jaber Hospital, a COVID19 facility in Kuwait, between 24 February and 20 April 2020. The primary endpoint of interest was disease severity defined algorithmically. Predefined risk variables were collected at the time of PCR based diagnosis of the infection. Prognostic model development used 5-fold cross-validated regularized logit regression. The cohort was divided into a training and validation cohort and all model development proceeded on the training cohort. ResultsThere were 643 patients with clinical course data of whom 94 developed severe COVID19. In the final model, age, CRP, procalcitonin, lymphocyte and monocyte percentages and serum albumin were independent predictors of a more severe illness course. The final prognostic model demonstrated good discrimination, calibration and internal validity. ConclusionWe developed and validated a simple score calculated at time of diagnosis that can predict patients with severe COVID19 disease.
