Clinicodemographic profile, intensive care unit utilization and mortality rate among COVID-19 patients admitted during the second wave in Bangladesh.

Introduction: The second wave of COVID-19 arrived in Bangladesh in March 2021. This pilot research from a tertiary care COVID-dedicated hospital observed the clinicodemographic profile, intensive care unit (ICU) utilization, and mortality rate among COVID-19 patients admitted during the second wave. Methods: Reverse transcription-polymerase chain reaction or chest high-resolution computed tomography confirmed 972 COVID-19 cases included in this cross-sectional study from 24 March to 23 June 2021, recruited using convenience sampling. Data regarding clinicodemographic profile, ICU utilization and mortality rate were analyzed. Results: The mean study cohort age was 54.47±12.73 years, with most patients (48.3%) aged 41-60; 64.1% were men. Fever (77.9%) and cough (75.9%) were the most common symptoms, and hypertension (43.6%) and diabetes (42.15%) the most common comorbidities. Nearly half of patients had total lung involvement of 26%-50%, and 23.8% required ICU. Overall mortality was 16.5%, whereas the mortality rate among ICU admitted patients was 56.1%. The most important predictors of mortality were older age, chronic renal illness, the proportion of lung involvement and ICU requirement. Conclusions: We found higher mortality and ICU utilization rate and greater total lung involvement during the second wave. The mortality rate among the elderly and ICU patients was also higher than earlier.

Identification of host transcriptome-guided repurposable drugs for SARS-CoV-1 infections and their validation with SARS-CoV-2 infections by using the integrated bioinformatics approaches.

Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) is one of the most severe global pandemic due to its high pathogenicity and death rate starting from the end of 2019. Though there are some vaccines available against SAER-CoV-2 infections, we are worried about their effectiveness, due to its unstable sequence patterns. Therefore, beside vaccines, globally effective supporting drugs are also required for the treatment against SARS-CoV-2 infection. To explore commonly effective repurposable drugs for the treatment against different variants of coronavirus infections, in this article, an attempt was made to explore host genomic biomarkers guided repurposable drugs for SARS-CoV-1 infections and their validation with SARS-CoV-2 infections by using the integrated bioinformatics approaches. At first, we identified 138 differentially expressed genes (DEGs) between SARS-CoV-1 infected and control samples by analyzing high throughput gene-expression profiles to select drug target key receptors. Then we identified top-ranked 11 key DEGs (SMAD4, GSK3B, SIRT1, ATM, RIPK1, PRKACB, MED17, CCT2, BIRC3, ETS1 and TXN) as hub genes (HubGs) by protein-protein interaction (PPI) network analysis of DEGs highlighting their functions, pathways, regulators and linkage with other disease risks that may influence SARS-CoV-1 infections. The DEGs-set enrichment analysis significantly detected some crucial biological processes (immune response, regulation of angiogenesis, apoptotic process, cytokine production and programmed cell death, response to hypoxia and oxidative stress), molecular functions (transcription factor binding and oxidoreductase activity) and pathways (transcriptional mis-regulation in cancer, pathways in cancer, chemokine signaling pathway) that are associated with SARS-CoV-1 infections as well as SARS-CoV-2 infections by involving HubGs. The gene regulatory network (GRN) analysis detected some transcription factors (FOXC1, GATA2, YY1, FOXL1, TP53 and SRF) and micro-RNAs (hsa-mir-92a-3p, hsa-mir-155-5p, hsa-mir-106b-5p, hsa-mir-34a-5p and hsa-mir-19b-3p) as the key transcriptional and post- transcriptional regulators of HubGs, respectively. We also detected some chemicals (Valproic Acid, Cyclosporine, Copper Sulfate and arsenic trioxide) that may regulates HubGs. The disease-HubGs interaction analysis showed that our predicted HubGs are also associated with several other diseases including different types of lung diseases. Then we considered 11 HubGs mediated proteins and their regulatory 6 key TFs proteins as the drug target proteins (receptors) and performed their docking analysis with the SARS-CoV-2 3CL protease-guided top listed 90 anti-viral drugs out of 3410. We found Rapamycin, Tacrolimus, Torin-2, Radotinib, Danoprevir, Ivermectin and Daclatasvir as the top-ranked 7 candidate-drugs with respect to our proposed target proteins for the treatment against SARS-CoV-1 infections. Then, we validated these 7 candidate-drugs against the already published top-ranked 11 target proteins associated with SARS-CoV-2 infections by molecular docking simulation and found their significant binding affinity scores with our proposed candidate-drugs. Finally, we validated all of our findings by the literature review. Therefore, the proposed candidate-drugs might play a vital role for the treatment against different variants of SARS-CoV-2 infections with comorbidities, since the proposed HubGs are also associated with several comorbidities.

Demographic profile and outcome of patients admitted to a COVID dedicated hospital in Bangladesh during the second wave.

ABSTRACT: In December 2019, with pneumonia-like clinical manifestations, a new severe acute respiratory syndrome coronavirus 2 emerged and quickly escalated into a pandemic. Since the first case detected in early March of last year, 8668 have died with an infection mortality rate of 1.52%, as of March 20, 2021. Bangladesh has been struck by the 2nd wave from mid-march 2021. As data on the second wave are sparse, the present study observed the demographic profile, symptoms, and outcomes of Coronavirus Disease 2019 (COVID-19) patients during this wave.The study was conducted at Sheikh Russel National Gastroliver Institute on 486 admitted cases during the 2nd wave of COVID-19 in Bangladesh (March 24-April 24, 2021) using a cross-sectional study design and a convenient sampling technique.Out of 486 cases, 306 (62.9%) were male, and 180 were female, with a mean age of 53.47 ±â€Š13.86. The majority of patients (32.5%) were between the ages of 51 and 60. While fever and cough being the predominant symptoms (>70% cases), the most common co-morbidities were hypertension (41.4) and diabetes mellitus (39.4). Intensive care unit utilization rate was 25%, and a half of the patients had 51% to 70% tomographic lung involvement with an overall mortality rate of 19.3%. Older age, chronic renal disease, percentage of lung involvement, and intensive care unit necessity were important mortality determinants.The present study gives an insight into the demographic profiles and outcomes of admitted patients with COVID-19 during the second wave at a covid dedicated hospital in Bangladesh.

Virtual screening and molecular dynamics simulation study of plant-derived compounds to identify potential inhibitors of main protease from SARS-CoV-2.

The new coronavirus (SARS-CoV-2) halts the world economy and caused unbearable medical emergency due to high transmission rate and also no effective vaccine and drugs has been developed which brought the world pandemic situations. The main protease (Mpro) of SARS-CoV-2 may act as an effective target for drug development due to the conservation level. Herein, we have employed a rigorous literature review pipeline to enlist 3063 compounds from more than 200 plants from the Asian region. Therefore, the virtual screening procedure helps us to shortlist the total compounds into 19 based on their better binding energy. Moreover, the Prime MM-GBSA procedure screened the compound dataset further where curcumin, gartanin and robinetin had a score of (-59.439, -52.421 and - 47.544) kcal/mol, respectively. The top three ligands based on binding energy and MM-GBSA scores have most of the binding in the catalytic groove Cys145, His41, Met165, required for the target protein inhibition. The molecular dynamics simulation study confirms the docked complex rigidity and stability by exploring root mean square deviations, root mean square fluctuations, solvent accessible surface area, radius of gyration and hydrogen bond analysis from simulation trajectories. The post-molecular dynamics analysis also confirms the interactions of the curcumin, gartanin and robinetin in the similar binding pockets. Our computational drug designing approach may contribute to the development of drugs against SARS-CoV-2.