OBJECTIVE: The present study intends to monitor variations in deaths and identify the growth phases such as pre-growth, growth, and post-growth phases in Pakistan due to the COVID-19 pandemic.
METHODS: New approaches are needed that display the death patterns and signal an alarming situation so that corrective actions can be taken before the condition worsens. To meet this purpose, secondary data on daily reported deaths due to the COVID-19 pandemic have been considered, and the $c$ and exponentially weighted moving average (EWMA) control charts are used To meet this purpose, secondary data on daily reported deaths in Pakistan due to the COVID-19 pandemic have been considered. The $ c$ and exponentially weighted moving average (EWMA) control charts have been used for monitoring variations.
RESULTS: The chart shows that Pakistan switches from the pre-growth to the growth phase on 31 March 2020. The EWMA chart demonstrates that Pakistan remains in the growth phase from 31 March 2020 to 17 August 2020, with some indications signaling a decrease in deaths. It is found that Pakistan moved to a post-growth phase for a brief period from 27 July 2020 to 28 July 2020. Pakistan switches to re-growth phase with an alarm on 31/7/2020, right after the short-term post-growth phase. The number of deaths starts decreasing in August in that Pakistan may approach the post-growth phase shortly.
CONCLUSION: This amalgamation of control charts illustrates a systematic implementation of the charts for government leaders and forefront medical teams to facilitate the rapid detection of daily reported deaths due to COVID-19. Besides government and public health officials, it is also the public's responsibility to follow the enforced standard operating procedures as a temporary remedy of this pandemic in ensuring public safety while awaiting a suitable vaccine to be discovered.
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: A total of three databases were searched on September 15, 2020: PubMed, Web of Science, and Science Direct. The searches were conducted using a pre-specified search strategy to record studies reported the reproductive number of coronavirus from its inception in December 2019. It includes keywords of coronavirus and its reproductive number, which were combined using the Boolean operators (AND, OR). Based on the included studies, we estimated a summary reproductive number by using the meta-analysis. We used narrative synthesis to explain the results of the studies where the reproductive number was reported, however, were not possible to include in the meta-analysis because of the lack of data (mostly due to confidence interval was not reported).
RESULTS: Total of 42 studies included in this review whereas 29 of them were included in the meta-analysis. The estimated summary reproductive number was 2.87 (95% CI, 2.39-3.44). We found evidence of very high heterogeneity (99.5%) of the reproductive number reported in the included studies. Our sub-group analysis was found the significant variations of reproductive number across the country for which it was estimated, method and model that were used to estimate the reproductive number, number of case that was considered to estimate the reproductive number, and the type of reproductive number that was estimated. The highest reproductive number was reported for the Diamond Princess Cruise Ship in Japan (14.8). In the country-level, the higher reproductive number was reported for France (R, 6.32, 95% CI, 5.72-6.99) following Germany (R, 6.07, 95% CI, 5.51-6.69) and Spain (R, 3.56, 95% CI, 1.62-7.82). The higher reproductive number was reported if it was estimated by using the Markov Chain Monte Carlo method (MCMC) method and the Epidemic curve model. We also reported significant heterogeneity of the type of reproductive number- a high-value reported if it was the time-dependent reproductive number.
CONCLUSION: The estimated summary reproductive number indicates an exponential increase of coronavirus infection in the coming days. Comprehensive policies and programs are important to reduce new infections as well as the associated adverse consequences including death.
METHODS: We recruited and analyzed SARS-CoV-2-infected adult patients (age ≥18 years) who were admitted to the ICU at Jaber Al-Ahmad Al Sabah Hospital, Kuwait, between March 1, 2020, and April 30, 2020. The risk factors associated with in-hospital mortality were assessed using multiple regression analysis.
RESULTS: We recruited a total of 103 ICU patients in this retrospective cohort. The median age of the patients was 53 years and the fatality rate was 45.6%; majority (85.5%) were males and 37% patients had more than 2 comorbidities. Preexisting hypertension, moderate/severe acute respiratory distress syndrome, lymphocyte count <0.5 × 109, serum albumin <22 g/L, procalcitonin >0.2 ng/mL, D-dimer >1,200 ng/mL, and the need for continuous renal replacement therapy were significantly associated with mortality.
CONCLUSION: This study describes the clinical characteristics and risk factors for mortality among ICU patients with CO-VID-19. Early identification of risk factors for mortality might help improve outcomes.
OBJECTIVE: To design and evaluate a molecular diagnostic tool for detection and identification of all currently recognized and potentially future emergent CoVs from the Orthocoronavirinae subfamily.
STUDY DESIGN AND RESULTS: We designed a semi-nested, reverse transcription RT-PCR assay based upon 38 published genome sequences of human and animal CoVs. We evaluated this assay with 14 human and animal CoVs and 11 other non-CoV respiratory viruses. Through sequencing the assay's target amplicon, the assay correctly identified each of the CoVs; no cross-reactivity with 11 common respiratory viruses was observed. The limits of detection ranged from 4 to 4 × 102 copies/reaction, depending on the CoV species tested. To assess the assay's clinical performance, we tested a large panel of previously studied specimens: 192 human respiratory specimens from pneumonia patients, 5 clinical specimens from COVID-19 patients, 81 poultry oral secretion specimens, 109 pig slurry specimens, and 31 aerosol samples from a live bird market. The amplicons of all RT-PCR-positive samples were confirmed by Sanger sequencing. Our assay performed well with all tested specimens across all sample types.
CONCLUSIONS: This assay can be used for detection and identification of all previously recognized CoVs, including SARS-CoV-2, and potentially any emergent CoVs in the Orthocoronavirinae subfamily.
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.