COVID-19 complicating pregnancy: A retrospective study of nine intensive care unit patients

Background: With the emergence of the coronavirus 2019 (COVID-19) pandemic, it was essential to determine the impact of this disease on pregnant women and neonatal outcomes. In this study, we present a series of nine cases of pregnant women with COVID-19 disease requiring intensive care unit (ICU) admission. Method(s): We retrospectively collected clinical data of pregnant women with COVID-19 disease admitted to ICU between September 2020 and September 2021. Result(s): Most common presenting symptom was cough. Two patients had no respiratory symptoms at presentation. Five of the nine patients required invasive mechanical ventilation. Seven patients required caesarean section, four of whom delivered preterm. There were no maternal or neonatal deaths. Conclusion(s): Although maternal and neonatal outcomes reported in our study are encouraging, it is imperative to emphasize the importance of an individualized, multidisciplinary approach, and good healthcare infrastructure for optimal management of this group of patients.Copyright © The Author(s) 2023.

Monoclonal antibody designed for SARS-nCoV-2 spike protein of receptor binding domain on antigenic targeted epitopes for inhibition to prevent viral entry.

SARS, or severe acute respiratory syndrome, is caused by a novel coronavirus (COVID-19). This situation has compelled many pharmaceutical R&D companies and public health research sectors to focus their efforts on developing effective therapeutics. SARS-nCoV-2 was chosen as a protein spike to targeted monoclonal antibodies and therapeutics for prevention and treatment. Deep mutational scanning created a monoclonal antibody to characterize the effects of mutations in a variable antibody fragment based on its expression levels, specificity, stability, and affinity for specific antigenic conserved epitopes to the Spike-S-Receptor Binding Domain (RBD). Improved contacts between Fv light and heavy chains and the targeted antigens of RBD could result in a highly potent neutralizing antibody (NAbs) response as well as cross-protection against other SARS-nCoV-2 strains. It undergoes multipoint core mutations that combine enhancing mutations, resulting in increased binding affinity and significantly increased stability between RBD and antibody. In addition, we improved. Structures of variable fragment (Fv) complexed with the RBD of Spike protein were subjected to our established in-silico antibody-engineering platform to obtain enhanced binding affinity to SARS-nCoV-2 and develop ability profiling. We found that the size and three-dimensional shape of epitopes significantly impacted the activity of antibodies produced against the RBD of Spike protein. Overall, because of the conformational changes between RBD and hACE2, it prevents viral entry. As a result of this in-silico study, the designed antibody can be used as a promising therapeutic strategy to treat COVID-19.

Humoral efficacy of the third SARS-CoV-2 vaccine dose in Multiple Sclerosis subjects undergoing different disease-modifying therapies.

BACKGROUND: It remains unclear how vaccine doses and combinations of vaccination and infection affect the magnitude and quality of immune responses, particularly against novel SARS-CoV-2 variants in subjects with immune-related disorders, such as people with multiple sclerosis (pwMS). Several studies have evaluated the duration of anti-SARS-CoV-2 immune protection in healthy individuals; however clinical data suggest an attenuated short-term humoral response to SARS-CoV-2 vaccines in pwMS receiving disease-modifying therapies (DMTs). METHODS: In this prospective study, we evaluated the humoral response to the third (3rd) BNT162b2 vaccine (booster) dose in a monocentric cohort of pwMS undergoing eight different DMTs, all without previous SARS-CoV-2 infection. Quantitative determination of SARS-CoV-2 IgG Spike titre was carried out by anti-SARS-CoV-2 S assay in 65 pwMS and 9 healthy controls, all without previous SARS-CoV-2 infection. Moreover, these measurements were also compared to their relative levels at 21 days (T1) and ∼6 months (T2) after the second (2nd) vaccination. RESULTS: We observed that the humoral response to the booster dose in Interferon ß-1a-, Dimethyl fumarate- and Teriflunomide-treated pwMS is comparable to healthy controls, while increased in Cladribine-treated pwMS. Additionally, the 3rd dose elicits a seroconversion in the 100% of pwMS under Fingolimod and in the 65% of those under Ocrelizumab. Moreover, multivariate regression analysis showed that treatment with Interferon ß-1a, Dimethyl fumarate and Cladribine positively associates with an increased humoral response. CONCLUSIONS: Taken together this evidence strongly indicates the importance of the booster dose to enhance SARS-CoV-2-specific immunity especially in immunocompromised subjects, such as pwMS under DMTs.

A Novel Rolling Circle Amplification-Based Detection of SARS-CoV-2 with Multi-Region Padlock Hybridization.

SARS-CoV-2 has remained a global health burden, primarily due to the continuous evolution of different mutant strains. These mutations present challenges to the detection of the virus, as the target genes of qPCR, the standard diagnostic method, may possess sequence alterations. In this study, we develop an isothermal one-step detection method using rolling circle amplification (RCA) for SARS-CoV-2. This novel strategy utilizes a multi-padlock (MP-RCA) approach to detect viral-RNA via a simplified procedure with the reliable detection of mutated strains over other procedures. We designed 40 padlock-based probes to target different sequences across the SARS-CoV-2 genome. We established an optimal one-step isothermal reaction protocol utilizing a fluorescent output detected via a plate reader to test a variety of padlock combinations. This method was tested on RNA samples collected from nasal swabs and validated via PCR. S-gene target failure (SGTF)-mutated strains of SARS-CoV-2 were included. We demonstrated that the sensitivity of our assay was linearly proportional to the number of padlock probes used. With the 40-padlock combination the MP-RCA assay was able to correctly detect 45 out 55 positive samples (81.8% efficiency). This included 10 samples with SGTF mutations which we were able to detect as positive with 100% efficiency. We found that the MP-RCA approach improves the sensitivity of the MP-RCA assay, and critically, allows for the detection of SARS-CoV-2 variants with SGTF. Our method offers the simplicity of the reaction and requires basic equipment compared to standard qPCR. This method provides an alternative approach to overcome the challenges of detecting SARS-CoV-2 and other rapidly mutating viruses.

Patient and Clinical Factors at Admission Affect the Levels of Neutralizing Antibodies Six Months after Recovering from COVID-19.

The rate of decline in the levels of neutralizing antibodies (NAbs) greatly varies among patients who recover from Coronavirus disease 2019 (COVID-19). However, little is known about factors associated with this phenomenon. The objective of this study is to investigate early factors at admission that can influence long-term NAb levels in patients who recovered from COVID-19. A total of 306 individuals who recovered from COVID-19 at the Tongji Hospital, Wuhan, China, were included in this study. The patients were classified into two groups with high (NAbhigh, n = 153) and low (NAblow, n = 153) levels of NAb, respectively based on the median NAb levels six months after discharge. The majority (300/306, 98.0%) of the COVID-19 convalescents had detected NAbs. The median NAb concentration was 63.1 (34.7, 108.9) AU/mL. Compared with the NAblow group, a larger proportion of the NAbhigh group received corticosteroids (38.8% vs. 22.4%, p = 0.002) and IVIG therapy (26.5% vs. 16.3%, p = 0.033), and presented with diabetes comorbidity (25.2% vs. 12.2%, p = 0.004); high blood urea (median (IQR): 4.8 (3.7, 6.1) vs. 3.9 (3.5, 5.4) mmol/L; p = 0.017); CRP (31.6 (4.0, 93.7) vs. 16.3 (2.7, 51.4) mg/L; p = 0.027); PCT (0.08 (0.05, 0.17) vs. 0.05 (0.03, 0.09) ng/mL; p = 0.001); SF (838.5 (378.2, 1533.4) vs. 478.5 (222.0, 1133.4) µg/L; p = 0.035); and fibrinogen (5.1 (3.8, 6.4) vs. 4.5 (3.5, 5.7) g/L; p = 0.014) levels, but low SpO2 levels (96.0 (92.0, 98.0) vs. 97.0 (94.0, 98.0)%; p = 0.009). The predictive model based on Gaussian mixture models, displayed an average accuracy of 0.7117 in one of the 8191 formulas, and ROC analysis showed an AUC value of 0.715 (0.657-0.772), and specificity and sensitivity were 72.5% and 67.3%, respectively. In conclusion, we found that several factors at admission can contribute to the high level of NAbs in patients after discharge, and constructed a predictive model for long-term NAb levels, which can provide guidance for clinical treatment and monitoring.

In-silico strategies to combat COVID-19: A comprehensive review.

The novel coronavirus SARS-CoV-2 since its emergence at Wuhan, China in December 2019 has been creating global health turmoil despite extensive containment measures and has resulted in the present pandemic COVID-19. Although the virus and its interaction with the host have been thoroughly characterized, effective treatment regimens beyond symptom-based care and repurposed therapeutics could not be identified. Various countries have successfully developed vaccines to curb the disease-transmission and prevent future outbreaks. Vaccination-drives are being conducted on a war-footing, but the process is time-consuming, especially in the densely populated regions of the world. Bioinformaticians and computational biologists have been playing an efficient role in this state of emergency to escalate clinical research and therapeutic development. However, there are not many reviews available in the literature concerning COVID-19 and its management. Hence, we have focused on designing a comprehensive review on in-silico approaches concerning COVID-19 to discuss the relevant bioinformatics and computational resources, tools, patterns of research, outcomes generated so far and their future implications to efficiently model data based on epidemiology; identify drug targets to design new drugs; predict epitopes for vaccine design and conceptualize diagnostic models. Artificial intelligence/machine learning can be employed to accelerate the research programs encompassing all the above urgent needs to counter COVID-19 and similar outbreaks.

Cardiac Troponin I association with critical illness and death risk in 726 seriously ill COVID-19 patients: A retrospective cohort study.

Background: For coronavirus disease 2019 (COVID-19), early identification of patients with serious symptoms at risk of critical illness and death is important for personalized treatment and balancing medical resources. Methods: Demographics, clinical characteristics, and laboratory tests data from 726 patients with serious COVID-19 at Tongji Hospital (Wuhan, China) were analyzed. Patients were classified into critical group (n = 174) and severe group (n= 552), the critical group was sub-divided into survivors (n = 47) and non-survivors (n = 127). Results: Multivariable analyses revealed the risk factors associated with critical illness in serious patients were: Advanced age, high respiratory rate (RR), high lactate dehydrogenase (LDH) level, high hypersensitive cardiac troponin I (hs-cTnI) level, and thrombocytopenia on admission. High hs-cTnI level was the independent risk factor of mortality among critically ill patients in the unadjusted and adjusted models. ROC curves demonstrated that hs-cTnI and LDH were predictive factors for critical illness in patients with serious COVID-19 whereas procalcitonin and D-Dimer with hs-cTnI and LDH were predictive parameters in mortality risk. Conclusions: Advanced age, high RR, LDH, hs-cTnI, and thrombocytopenia, constitute risk factors for critical illness among patients with serious COVID-19, and the hs-cTnI level helps predict fatal outcomes in critically ill patients.

A narrative review of non-pharmacological management of SARS-CoV-2 respiratory failure: a call for an evidence based approach.

A novel severe acute respiratory syndrome coronavirus (SARS-CoV-2) belonging to genus beta-coronavirus has been associated with an acute respiratory disease termed coronavirus disease 2019 (COVID-19). As of September 3, 2020, SARS-CoV-2 had caused 867,219 fatalities in 188 nations across the globe. Rapid progression to bronchopneumonia manifesting with severe hypoxemia and eventual evolution into acute respiratory distress syndrome (ARDS) necessitating mechanical ventilation is the hallmark of this disease. The novel nature of COVID-19 pneumonia and the high morbidity and mortality associated with the same has vexed the critical care community. A cultural shift away from evidence-based medicine, and the impetus to attempt newer unproven therapies like awake proning, interleukin receptor 6 antagonists, inhaled nitric oxide, empiric anticoagulation etc. over modalities that have been tested over the decades is slowly gaining ground. The suggestions to delay intubations and liberalize tidal volumes have polarized the medical field like never before. The lack of consistency in management practices and establishing practices based on anecdotes and experiences can lead to devastating outcomes in the patients affected by this deadly virus. In this narrative review, we attempt to re-emphasize the need for an evidence-based approach to the management of COVID-19 related ARDS and review treatment strategies that have been established after rigorous trials and have stood the test of time.