Clinical manifestation and disease progression in COVID-19 infection

Enhancing RNA detection and breast cancer subtyping with a universal 3D-hybridization chain reaction system

Breast cancer, a globally prevalent malignancy, is characterized by pronounced heterogeneity. Accurate subtyping requires the simultaneous detection of different biomarkers, which is crucial for personalized treatment strategies. However, existing methodologies are hindered by limited versatility and sensing performance. To overcome these hurdles, this study presents a universal 3D-Hybridization Chain Reaction (3D-HCR) system for RNA detection and subtype-specific diagnosis of breast cancer. The system integrated a universal trigger for HCR, thereby circumventing the need for complex sequence design and enabling the analysis of various RNA targets. Leveraging the spatial-confinement effect offered by DNA nanocarriers, this system exhibited superior amplification efficiency, achieving detection limits of 3.83 pM and 4.96 pM for PD-L1 mRNA and miR-21, respectively. Importantly, the system could differentiate between triple-negative breast cancer and estrogen receptor-positive breast cancer in both living cells and clinical tissues. These findings underscore the potential of the universal 3D-HCR system as a promising tool in clinical diagnostics. With its proven proficiency in breast cancer diagnostics and versatility in RNA analysis, this system holds the promise of broadening the horizons of precision medicine.

Interplay of Demographic Influences, Clinical Manifestations, and Longitudinal Profile of Laboratory Parameters in the Progression of SARS-CoV-2 Infection: Insights from the Saudi Population

Understanding the factors driving SARS-CoV-2 infection progression and severity is complex due to the dynamic nature of human physiology. Therefore, we aimed to explore the severity risk indicators of SARS-CoV-2 through demographic data, clinical manifestations, and the profile of laboratory parameters. The study included 175 patients either hospitalized at King Abdulaziz Medical City-Riyadh or placed in quarantine at designated hotels in Riyadh, Saudi Arabia, from June 2020 to April 2021. Hospitalized patients were followed up through the first week of admission. Demographic data, clinical presentations, and laboratory results were retrieved from electronic patient records. Our results revealed that older age (OR: 1.1, CI: [1.1-1.12]; p < 0.0001), male gender (OR: 2.26, CI: [1.0-5.1]; p = 0.047), and blood urea nitrogen level (OR: 2.56, CI: [1.07-6.12]; p = 0.034) were potential predictors of severity level. In conclusion, the study showed that apart from laboratory parameters, age and gender could potentially predict the severity of SARS-CoV-2 infection in the early stages. To our knowledge, this study is the first in Saudi Arabia to explore the longitudinal profile of laboratory parameters among risk factors, shedding light on SARS-CoV-2 infection progression parameters.

The Immune Response of OAS1, IRF9, and IFI6 Genes in the Pathogenesis of COVID-19

COVID-19 is characterized by a wide range of clinical manifestations, where aging, underlying diseases, and genetic background are related to worse outcomes. In the present study, the differential expression of seven genes related to immunity, IRF9, CCL5, IFI6, TGFB1, IL1B, OAS1, and TFRC, was analyzed in individuals with COVID-19 diagnoses of different disease severities. Two-step RT-qPCR was performed to determine the relative gene expression in whole-blood samples from 160 individuals. The expression of OAS1 (p < 0.05) and IFI6 (p < 0.05) was higher in moderate hospitalized cases than in severe ones. Increased gene expression of OAS1 (OR = 0.64, CI = 0.52-0.79; p = 0.001), IRF9 (OR = 0.581, CI = 0.43-0.79; p = 0.001), and IFI6 (OR = 0.544, CI = 0.39-0.69; p < 0.001) was associated with a lower risk of requiring IMV. Moreover, TGFB1 (OR = 0.646, CI = 0.50-0.83; p = 0.001), CCL5 (OR = 0.57, CI = 0.39-0.83; p = 0.003), IRF9 (OR = 0.80, CI = 0.653-0.979; p = 0.03), and IFI6 (OR = 0.827, CI = 0.69-0.991; p = 0.039) expression was associated with patient survival. In conclusion, the relevance of OAS1, IRF9, and IFI6 in controlling the viral infection was confirmed.

Effect of polyphenols against complications of COVID-19: current evidence and potential efficacy

The COVID-19 pandemic that started in 2019 and resulted in significant morbidity and mortality continues to be a significant global health challenge, characterized by inflammation, oxidative stress, and immune system dysfunction.. Developing therapies for preventing or treating COVID-19 remains an important goal for pharmacology and drug development research. Polyphenols are effective against various viral infections and can be extracted and isolated from plants without losing their therapeutic potential. Researchers have developed methods for separating and isolating polyphenols from complex matrices. Polyphenols are effective in treating common viral infections, including COVID-19, and can also boost immunity. Polyphenolic-based antiviral medications can mitigate SARS-CoV-2 enzymes vital to virus replication and infection. Individual polyphenolic triterpenoids, flavonoids, anthraquinonoids, and tannins may also inhibit the SARS-CoV-2 protease. Polyphenol pharmacophore structures identified to date can explain their action and lead to the design of novel anti-COVID-19 compounds. Polyphenol-containing mixtures offer the advantages of a well-recognized safety profile with few known severe side effects. However, studies to date are limited, and further animal studies and randomized controlled trials are needed in future studies. The purpose of this study was to review and present the latest findings on the therapeutic impact of plant-derived polyphenols on COVID-19 infection and its complications. Exploring alternative approaches to traditional therapies could aid in developing novel drugs and remedies against coronavirus infection.

AI-powered COVID-19 forecasting: a comprehensive comparison of advanced deep learning methods

BACKGROUND

The coronavirus disease 2019 (COVID-19) pandemic continues to pose significant challenges to the public health sector, including that of the United Arab Emirates (UAE). The objective of this study was to assess the efficiency and accuracy of various deep-learning models in forecasting COVID-19 cases within the UAE, thereby aiding the nation's public health authorities in informed decision-making.

METHODS

This study utilized a comprehensive dataset encompassing confirmed COVID-19 cases, demographic statistics, and socioeconomic indicators. Several advanced deep learning models, including long short-term memory (LSTM), bidirectional LSTM, convolutional neural network (CNN), CNN-LSTM, multilayer perceptron, and recurrent neural network (RNN) models, were trained and evaluated. Bayesian optimization was also implemented to fine-tune these models.

RESULTS

The evaluation framework revealed that each model exhibited different levels of predictive accuracy and precision. Specifically, the RNN model outperformed the other architectures even without optimization. Comprehensive predictive and perspective analytics were conducted to scrutinize the COVID-19 dataset.

CONCLUSION

This study transcends academic boundaries by offering critical insights that enable public health authorities in the UAE to deploy targeted data-driven interventions. The RNN model, which was identified as the most reliable and accurate for this specific context, can significantly influence public health decisions. Moreover, the broader implications of this research validate the capability of deep learning techniques in handling complex datasets, thus offering the transformative potential for predictive accuracy in the public health and healthcare sectors.

SARS-CoV-2 outbreak: role of viral proteins and genomic diversity in virus infection and COVID-19 progression

The severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection is the cause of coronavirus disease 2019 (COVID-19); a severe respiratory distress that has emerged from the city of Wuhan, Hubei province, China during December 2019. COVID-19 is currently the major global health problem and the disease has now spread to most countries in the world. COVID-19 has profoundly impacted human health and activities worldwide. Genetic mutation is one of the essential characteristics of viruses. They do so to adapt to their host or to move to another one. Viral genetic mutations have a high potentiality to impact human health as these mutations grant viruses unique unpredicted characteristics. The difficulty in predicting viral genetic mutations is a significant obstacle in the field. Evidence indicates that SARS-CoV-2 has a variety of genetic mutations and genomic diversity with obvious clinical consequences and implications. In this review, we comprehensively summarized and discussed the currently available knowledge regarding SARS-CoV-2 outbreaks with a fundamental focus on the role of the viral proteins and their mutations in viral infection and COVID-19 progression. We also summarized the clinical implications of SARS-CoV-2 variants and how they affect the disease severity and hinder vaccine development. Finally, we provided a massive phylogenetic analysis of the spike gene of 214 SARS-CoV-2 isolates from different geographical regions all over the world and their associated clinical implications.

Vascular cutaneous manifestations of COVID-19 and RNA viral pathogens: a systematic review

BACKGROUND

COVID-19, the widely recognized and highly contagious respiratory tract infection, has had a substantial impact on the field of dermatology since its emergence in 2019. SARS-CoV-2, the causative virus of COVID-19, is classified as an RNA virus. Various skin-related symptoms have been reported in patients with COVID-19, most notably the distinctive purple-red acral rash resembling chilblain lesions, commonly referred to as 'COVID toe'; similarly, skin-related symptoms have been observed in connection with other RNA viruses.

OBJECTIVES

To explore the relationship between RNA viruses and their associated vascular cutaneous manifestations vs. those observed in patients infected with SARS-CoV-2.

METHODS

A systematic literature review was conducted using PubMed and medical subject heading terms related to RNA viruses and related skin manifestations.

RESULTS

In total, 3994 patients diagnosed with COVID-19 presenting with skin rashes were included. Chilblain-like lesions were most frequently observed (30.2%), followed by erythematous maculopapular/morbilliform rashes (9.1%) and urticarial rashes (4.7%). Of 8362 patients diagnosed with RNA viruses, more than half of the skin findings reported were erythematous/maculopapular/morbilliform rashes (52.3%), followed by unspecified (11.3%) and purpuric rashes (10.6%).

CONCLUSIONS

When comparing RNA viral infections with COVID-19 infection, we observed similarities in the reported skin manifestations and their presumed pathways, with many implicated in the proinflammatory response. Owing to the wide range of cutaneous symptoms associated with RNA viruses and our currently limited understanding of the underlying mechanisms, additional research is warranted to investigate the pathology behind viral-induced skin lesions.

Performance of oxygenation indices and risk scores to predict invasive mechanical ventilation and mortality in COVID-19

BACKGROUND

Information on the performance of oxygenation indices (OIs) and risk scores in patients requiring invasive mechanical ventilation (IMV) is limited. We determine the performance of the OIs and risk scores in hospitalized patients with COVID-19 to predict the requirement of IMV and death at 28 days after admission.

METHODS

A retrospective study of diagnostic tests in patients admitted to the emergency department, hospitalization, and intensive care unit diagnosed with COVID-19. The receiver operating characteristic curve (ROC-curve) were built with the OIs and risk scores to predict IMV and mortality.

RESULTS

A total of 1402 subjects entered the final analysis, of whom 19.5% (274/1402) received IMV and 23.0% (323/1402) died at 28 days. The ROC-curve of the delta PaO2/FiO2 ratio for the requirement of IMV and mortality at 28-day was 0.589 (95% CI: 0.546-0.632) and 0.567 (95% CI: 0.526-0.608), respectively. PaO2/FiO2 ≤ 300 shows a ROC curve of 0.669 (95% CI: 0.628-0.711) to predict IMV. PaO2/FiO2 ≤ 300 and 4 C mortality score in mortality at 28 days showed an ROC-curve of 0.624 (95% CI: 0.582-0.667) and 0.706 (95% CI: 0.669-0.742), respectively.

CONCLUSION

PaO2/FiO2 ≤ 300, 4 C mortality score ≥ 8, SOFA score ≥ 4 y SaO2/FiO2 ≤ 300 were weak predictors of the IMV requirement from admission, and 4 C mortality score ≥ 8 was weak predictors of the mortality from admission in patients with pulmonary involvement by COVID-19.

Vitamin D Levels as a Marker of Severe SARS-CoV-2 Infection

The SARS-CoV-2 virus may cause severe infection, which is associated with diverse clinical manifestations. Vitamin D has immunomodulating properties and may enhance the body's defense system against invading pathogenic organisms. The aim was to assess 25(OH)D3 levels in patients hospitalized for severe infection from the SARS-CoV-2 virus and explore the relationship between 25(OH)D3 and outcomes. In a group of 88 patients hospitalized for severe infection from the SARS-CoV-2 virus and a control group matched for age and sex, the levels of 25(OH)D3 were analyzed. Levels of 25(OH)D3 were 17.36 ± 8.80 ng/mL (mean ± SD) compared with 24.34 ± 10.34 ng/mL in patients with severe SARS-CoV-2 infection and the control group, respectively, p < 0.001 (Student's t-test). 25(OH)D3 levels were significantly related to outcomes, i.e., survival as opposed to non-survival, as more patients with 25(OH)D3 deficiency (0-10 ng/mL) and insufficiency (10-20 ng/mL) had a fatal outcome as compared with those with vitamin D sufficiency (p < 0.001, chi-square test, p < 0.001, Fisher's exact test). Levels of 25(OH)D3 were inversely related to C-reactive protein (CRP), ferritin, d-dimer, and fibrinogen levels (p < 0.001, linear regression analysis, beta coefficient of variation, -0.176, -0.160, -0.178, and -0.158, respectively). Vitamin D deficiency observed in severe SARS-CoV-2 infection was related to disease outcomes.

COVID-19 Vaccine for Children: Determinants and Beliefs Contributing to Vaccination Decision of Parents in Germany 2021/2022

To reduce the number of COVID-19 cases, vaccines were rapidly made available worldwide. For a strategically targeted response to the COVID-19 pandemic, population vaccination coverage was to be maximized. The target groups also included healthy children. In this context, it is important to understand the determinants and beliefs that lead parents to favor or oppose COVID-19 immunization in children. This study aimed to investigate parents' COVID-19 vaccination willingness in Germany for children aged 5-11 years in 2021/2022. For this purpose, the determinants and beliefs behind parents' vaccination decisions were examined. Descriptive analysis and bivariate correlations were performed on COVID-19 vaccination willingness and parents' mental health status, general vaccination attitudes, and SARS-CoV-2 politics perceptions. In total, 2401 participants fully participated in this cross-sectional study. The COVID-19 vaccination uptake (71.4%) outweighed the vaccination refusal (19.4%). Correlations revealed higher vaccine acceptance in parents presenting full vaccination certificates (90.9%), COVID-19 immunizations (99.9%), or increased COVID-19 fear (93.6%). Vaccination-refusal was associated with higher perceived pressure by COVID-19 vaccination campaigns (87.7%), higher experienced restrictions due to COVID-19 protective measures in parents' social environment (83.6%), and engagement against COVID-19 protective measures (51.6%). Besides general anxiety, no significant correlations were observed between parents' mental health variables and vaccination willingness. Although several factors are ultimately associated with vaccination willingness, future vaccination campaigns should prioritize reducing pressure, increasing trust, and considering parents' differentiation between familiar and unfamiliar pathogens during their vaccination decision-making process.

Spatiotemporal observations of host-pathogen interactions in mucosa during SARS-CoV-2 infection indicate a protective role of ILC2s

IMPORTANCE

Our study revealed the spatial interaction between humanized ACE2 and pseudovirus expressing Spike, emphasizing the role of type 2 innate lymphoid cells during the initial phase of viral infection. These findings provide a foundation for the development of mucosal vaccines and other treatment approaches for both pre- and post-infection management of coronavirus disease 2019.

Activation of PXR causes drug interactions with Paxlovid in transgenic mice

Paxlovid is a nirmatrelvir (NMV) and ritonavir (RTV) co-packaged medication used for the treatment of coronavirus disease 2019 (COVID-19). The active component of Paxlovid is NMV and RTV is a pharmacokinetic booster. Our work aimed to investigate the drug/herb-drug interactions associated with Paxlovid and provide mechanism-based guidance for the clinical use of Paxlovid. By using recombinant human cytochrome P450s (CYPs), we confirmed that CYP3A4 and 3A5 are the major enzymes responsible for NMV metabolism. The role of CYP3A in Paxlovid metabolism were further verified in Cyp3a-null mice, which showed that the deficiency of CYP3A significantly suppressed the metabolism of NMV and RTV. Pregnane X receptor (PXR) is a ligand-dependent transcription factor that upregulates CYP3A4/5 expression. We next explored the impact of drug- and herb-mediated PXR activation on Paxlovid metabolism in a transgenic mouse model expressing human PXR and CYP3A4/5. We found that PXR activation increased CYP3A4/5 expression, accelerated NMV metabolism, and reduced the systemic exposure of NMV. In summary, our work demonstrated that PXR activation can cause drug interactions with Paxlovid, suggesting that PXR-activating drugs and herbs should be used cautiously in COVID-19 patients receiving Paxlovid.

Uncovering the underlying aspects of successful COVID-19 prevention and control in Thailand through factor analysis: Lessons we have not yet learned from village health volunteers

Background

The COVID-19 pandemic has posed a global challenge, leading different nations to adopt diverse strategies for prevention and control. In Thailand, Village Health Volunteers (VHVs) have played a pivotal role in the fight against the virus. As the pandemic unfolded, the critical role of VHVs became apparent, prompting a closer examination of their practices and the underlying factors contributing to their effectiveness.

Objective

This study aimed to uncover the underlying factors and indicators contributing to the successful prevention and control of COVID-19 by VHVs in Thailand.

Methods

The sample group included 10,400 VHVs nationwide. Data were collected from October 2020 to February 2021 using five-point Likert rating scale online questionnaires. Data were analyzed using the Exploratory Factor Analysis technique, with Principal Component Analysis and the orthogonal Varimax method.

Results

The study revealed nine effective factors and 52 indicators contributing to the prevention and control of COVID-19 in Thailand. The identified factors are as follows: 1) Personal precautions, 2) Proactive disease control strategy, 3) Awareness of COVID-19 severity, 4) Pride and job motivation, 5) Adequate medical equipment and support, 6) Communication, planning, and monitoring processes, 7) Self-care for health, 8) Data collection, record maintenance, and report submission, and 9) Proper hand washing.

Conclusion

This research emphasizes the importance of a holistic approach to community-based health interventions. It highlights the crucial role of VHVs in disseminating information, ensuring preparedness, and fostering a sense of responsibility among community members. This strategic approach will effectively contribute to ongoing efforts to successfully prevent and control the spread of COVID-19 and potential future outbreaks.

Spin in randomized controlled trials of pharmacology in COVID-19: A systematic review

Spin, defined as the misrepresentation of the results of a study, could negate the validity of scientific findings. To explore the manifestation of spin, and identify the factors affecting spin in COVID-19 RCTs, a systematic review was performed from PubMed/Medline, National Institutes of Health, EMBASE, Cochrane, and Web of Science. RCTs on pharmacotherapy for COVID-19 with nonsignificant primary outcomes published in 2020 were included. 21 abstracts (33.9%) and 28 main texts (45.2%) were found to contain spin in at least one section. In the conclusion section, other spin strategies beautifying their findings that were not included in the abstract were found in the main texts. More factors influencing the level of spin were found in abstracts than in the main texts, but most of the levels of spin in abstracts were comparable to those in the main texts. Although common factors that affected the manifestation of spin in the main texts and abstracts were the sample size and type of journal, further research to determine multicollinearity between significant factors and the manifestation of spin is required.

Gastrointestinal symptoms among COVID-19 patients presenting to a primary health care center of Nepal: A cross-sectional study

Background and Aim

Coronavirus disease 2019 (COVID-19) is a major public health problem causing significant morbidity and mortality worldwide. Apart from respiratory symptoms, gastrointestinal symptoms like nausea, vomiting, diarrhea, and abdominal discomfort are quite common among COVID-19 patients. The gastrointestinal tract can be a potential site for virus replication and feces a source of transmission. Thus, ignorance of enteric symptoms can hinder effective disease control. The objective of this study is to see the gastrointestinal manifestation of the disease and its effect on morbidity and mortality.

Methods

This observational cross-sectional retrospective study was carried out among 165 laboratory-confirmed COVID-19 patients in primary health care of Gorkha, Nepal from March 1, 2021 to March 1, 2022. A systematic random sampling method was adopted while data were entered and analyzed by Statistical Package for Social Sciences version 21.

Results

Of 165 patients, 97 patients (58.78%) had enteric involvement. Among gastrointestinal symptoms, diarrhea in 67 patients (40.6%) and nausea and/or vomiting in 66 patients (40%) were the most common symptoms, followed by abdominal pain in 27 patients (16.4%) and anorexia in 19 patients (11.5%). Of the majority of cases with gastrointestinal involvement, 63 (63%) were below 50 years of age. Many of the patients who received vaccination had gastrointestinal symptoms (79%). Complications like acute respiratory distress syndrome, shock, and arrhythmia developed in 9.7% of patients, with the death of eight patients. COVID-19 vaccination was associated with 4.32 times higher odds of having gastrointestinal involvement in subsequent COVID-19 infection.

Conclusions

Diarrhea followed by nausea/vomiting was among the most common gastrointestinal symptoms affecting younger age groups in our study. Enteric symptoms were more common among vaccinated people rather than among nonvaccinated ones.

A Comparative Study on Deep Learning Models for COVID-19 Forecast

The COVID-19 pandemic has led to a global health crisis with significant morbidity, mortality, and socioeconomic disruptions. Understanding and predicting the dynamics of COVID-19 are crucial for public health interventions, resource allocation, and policy decisions. By developing accurate models, informed public health strategies can be devised, resource allocation can be optimized, and virus transmission can be reduced. Various mathematical and computational models have been developed to estimate transmission dynamics and forecast the pandemic's trajectories. However, the evolving nature of COVID-19 demands innovative approaches to enhance prediction accuracy. The machine learning technique, particularly the deep neural networks (DNNs), offers promising solutions by leveraging diverse data sources to improve prevalence predictions. In this study, three typical DNNs, including the Long Short-Term Memory (LSTM) network, Physics-informed Neural Network (PINN), and Deep Operator Network (DeepONet), are employed to model and forecast COVID-19 spread. The training and testing data used in this work are the global COVID-19 cases in the year of 2021 from the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University. A seven-day moving average as well as the normalization techniques are employed to stabilize the training of deep learning models. We systematically investigate the effect of the number of training data on the predicted accuracy as well as the capability of long-term forecast in each model. Based on the relative L2 errors between the predictions from deep learning models and the reference solutions, the DeepONet, which is capable of learning hidden physics given the training data, outperforms the other two approaches in all test cases, making it a reliable tool for accurate forecasting the dynamics of COVID-19.

Public Opinions About Palliative and End-of-Life Care During the COVID-19 Pandemic: Twitter-Based Content Analysis

BACKGROUND

Palliative and end-of-life care (PEoLC) played a critical role in relieving distress and providing grief support in response to the heavy toll caused by the COVID-19 pandemic. However, little is known about public opinions concerning PEoLC during the pandemic. Given that social media have the potential to collect real-time public opinions, an analysis of this evidence is vital to guide future policy-making.

OBJECTIVE

This study aimed to use social media data to investigate real-time public opinions regarding PEoLC during the COVID-19 crisis and explore the impact of vaccination programs on public opinions about PEoLC.

METHODS

This Twitter-based study explored tweets across 3 English-speaking countries: the United States, the United Kingdom, and Canada. From October 2020 to March 2021, a total of 7951 PEoLC-related tweets with geographic tags were retrieved and identified from a large-scale COVID-19 Twitter data set through the Twitter application programming interface. Topic modeling realized through a pointwise mutual information-based co-occurrence network and Louvain modularity was used to examine latent topics across the 3 countries and across 2 time periods (pre- and postvaccination program periods).

RESULTS

Commonalities and regional differences among PEoLC topics in the United States, the United Kingdom, and Canada were identified specifically: cancer care and care facilities were of common interest to the public across the 3 countries during the pandemic; the public expressed positive attitudes toward the COVID-19 vaccine and highlighted the protection it affords to PEoLC professionals; and although Twitter users shared their personal experiences about PEoLC in the web-based community during the pandemic, this was more prominent in the United States and Canada. The implementation of the vaccination programs raised the profile of the vaccine discussion; however, this did not influence public opinions about PEoLC.

CONCLUSIONS

Public opinions on Twitter reflected a need for enhanced PEoLC services during the COVID-19 pandemic. The insignificant impact of the vaccination program on public discussion on social media indicated that public concerns regarding PEoLC continued to persist even after the vaccination efforts. Insights gleaned from public opinions regarding PEoLC could provide some clues for policy makers on how to ensure high-quality PEoLC during public health emergencies. In this post-COVID-19 era, PEoLC professionals may wish to continue to examine social media and learn from web-based public discussion how to ease the long-lasting trauma caused by this crisis and prepare for public health emergencies in the future. Besides, our results showed social media's potential in acting as an effective tool to reflect public opinions in the context of PEoLC.

Impact of COVID-19 in individuals with and without pre-existent digestive disorders with a particular focus on elderly patients

Coronavirus disease 2019 (COVID-19) has several extrapulmonary symptoms. Gastrointestinal (GI) symptoms are among the most frequent clinical manifestations of COVID-19, with severe consequences reported in elderly patients. Furthermore, the impact of COVID-19 on patients with pre-existing digestive diseases still needs to be fully elucidated, particularly in the older population. This review aimed to investigate the impact of COVID-19 on the GI tract, liver, and pancreas in individuals with and without previous digestive diseases, with a particular focus on the elderly, highlighting the distinctive characteristics observed in this population. Finally, the effectiveness and adverse events of the anti-COVID-19 vaccination in patients with digestive disorders and the peculiarities found in the elderly are discussed.

Cytokine response and damages in the lungs of aging Syrian hamsters on a high-fat diet infected with the SARS-CoV-2 virus

Hypertriglyceridemia, obesity, and aging are among the key risk factors for severe COVID-19 with acute respiratory distress syndrome (ARDS). One of the main prognostic biomarkers of ARDS is the level of cytokines IL-6 and TNF-α in the blood. In our study, we modeled hyperglyceridemia and hypercholesterolemia on 18-month-old Syrian hamsters (Mesocricetus auratus). By 18 months, the animals showed such markers of aging as weight stabilization with a tendency to reduce it, polycystic liver disease, decreased motor activity, and foci of alopecia. The high-fat diet caused an increase in triglycerides and cholesterol, as well as fatty changes in the liver. On the third day after infection with the SARS-CoV-2 virus, animals showed a decrease in weight in the groups with a high-fat diet. In the lungs of males on both diets, there was an increase in the concentration of IFN-α, as well as IL-6 in both males and females, regardless of the type of diet. At the same time, the levels of TNF-α and IFN-γ did not change in infected animals. Morphological studies of the lungs of hamsters with SARS-CoV-2 showed the presence of a pathological process characteristic of ARDS. These included bronchointerstitial pneumonia and diffuse alveolar damages. These observations suggest that in aging hamsters, the immune response to pro-inflammatory cytokines may be delayed to a later period. Hypertriglyceridemia, age, and gender affect the severity of COVID-19. These results will help to understand the pathogenesis of COVID-19 associated with age, gender, and disorders of fat metabolism in humans.

The psychological impact of COVID-19 pandemic and associated factors among college and university students in Ethiopia: a systematic review and meta-analysis, 2022

Background

The Corona virus disease 19 (COVID-19) pandemic is a human tragedy that occurred in this era. It poses an unprecedented psychological, social, economic, and health crisis. The mental health and well-being of entire societies are suffering as a result of this crisis, but the suffering is greater in students at all levels of education and must be addressed immediately. Thus, this study was aimed to estimate the pooled prevalence and associated factors of the psychological impact of COVID-19 among higher education students.

Methods

The potential studies were searched via PubMed, HINARI, the Cochrane Library, and Google Scholar. Studies were appraised using the Joanna Briggs Institute appraisal checklist. Micro Soft Excel was used to extract the data, which was then exported to Stata version 14 for analysis. Heterogeneity between studies was tested using Cochrane statistics and the I² test, and small-study effects were checked using Egger's statistical test. A random-effects model was employed to estimate the pooled prevalence of the psychological impact of COVID-19 and its associated factor.

Results

After reviewing 227 studies, eight fulfilled the inclusion criteria and were included in the meta-analysis. The pooled prevalence of the psychological impact of Corona virus disease 19 among higher education students in Ethiopia, including depression, anxiety, and stress was 43.49% (95% CI: 29.59, 57.40%), 46.27% (95% CI: 32.77, 59.78%), and 31.43% (95% CI: 22.71, 40.15), respectively. Having a medical illness, being an urban resident, living with parents, having relative death due to pandemics, and having a non-health field of study were identified as significant associated factors for the impact of the pandemic in higher education students.

Conclusion

The COVID-19 pandemic had a significant psychological impact on college and university students. Depression, anxiety, and stress were the most commonly reported psychological impacts across studies among higher education students. Hence, applying tele-psychotherapy using, smartphones, and social media platforms has an effect on reducing the impact. Programs for preventing and controlling epidemics should be developed by the government and higher education institutions that incorporate mental health interventions and build resilience.

Coronavirus disease 2019 and cardiovascular disease

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the virus behind the coronavirus disease 2019 (COVID-19) pandemic, is a type of RNA virus that is nonsegmented. Cardiovascular diseases (CVDs) increase the mortality risk of patients. In this review article, we overview the existing evidence regarding the potential mechanisms of myocardial damage in coronavirus disease 2019 (COVID-19) patients. Having a comprehensive knowledge of the cardiovascular damage caused by SARS-CoV-2 and its underlying mechanisms is essential for providing prompt and efficient treatment, ultimately leading to a reduction in mortality rates. Severe COVID-19 causes acute respiratory distress syndrome and shock in patients. In addition, awareness regarding COVID-19 cardiovascular manifestations has increased, including the adverse impact on prognosis with cardiovascular involvement. Angiotensin-converting enzyme 2 receptor may play a role in acute myocardial injury caused by SARS-CoV-2 infection. COVID-19 patients experiencing heart failure may have their condition exacerbated by various contributing factors and mechanisms. Increased oxygen demand, myocarditis, stress cardiomyopathy, elevated pulmonary pressures, and venous thrombosis are potential health issues. The combination of these factors may lead to COVID-19-related cardiogenic shock, resulting in acute systolic heart failure. Extracorporeal membrane oxygenation (ECMO) and left ventricular assist devices (LVADs) are treatment options when inotropic support fails for effective circulatory support. To ensure effective COVID-19-related cardiovascular disease (CVD) surveillance, it is crucial to closely monitor the future host adaptation, viral evolution, and transmissibility of SARS-CoV-2, given the virus's pandemic potential.

The effects of contemporaneous air pollution on COVID-19 morbidity and mortality

We examine the relationship between contemporaneous fine particulate matter exposure and COVID-19 morbidity and mortality using an instrumental variable approach. Harnessing daily changes in county-level wind direction, we show that arguably exogenous fluctuations in local air quality impact the incidence of confirmed COVID-19 cases and deaths. We find that a one μ g/m 3 increase in PM 2.5, or 15% of the average PM 2.5 concentration in a county, increases the number of same-day confirmed cases by 1.8% from the mean case incidence in a county. A one μ g/m 3 increase in PM 2.5 increases the same-day death rate by just over 4% from the mean. These effects tend to increase in magnitude over longer time horizons and are robust to a host of sensitivity tests. When analyzing potential mechanisms, we also demonstrate that an additional unit of PM 2.5 increases COVID-19-related hospitalizations by 0.8% and use of intensive care units by 0.5% on the same day. Using individual case records, we also show that higher PM 2.5 exposure at the time of case confirmation increases risk of later mechanical ventilation and mortality. These results suggest that air pollution plays an important role in mediating the severity of respiratory syndromes such as COVID-19.

Clinical predictors of Covid-19 mortality in a tertiary hospital in Lagos, Nigeria: A retrospective cohort study

Background

The predictors of mortality among patients presenting with severe to critical disease in Nigeria are presently unknown.

Aim

The aim of this study was to identify the predictors of mortality among patients with COVID-19 presenting for admission in a tertiary referral hospital in Lagos, Nigeria.

Patients and Methods

The study was a retrospective study. Patients' sociodemographics, clinical characteristics, comorbidities, complications, treatment outcomes, and hospital duration were documented. Pearson's Chi-square, Fischer's Exact test, or Student's t-test were used to assess the relationship between the variables and mortality. To compare the survival experience across medical comorbidities, Kaplan Meir plots and life tables were used. Univariable and multivariable Cox-proportional hazard analyses were conducted.

Results

A total of 734 patients were recruited. Participants' age ranged from five months to 92 years, with a mean ± SD of 47.4 ± 17.2 years, and a male preponderance (58.5% vs. 41.5%). The mortality rate was 9.07 per thousand person-days. About 73.9% (n = 51/69) of the deceased had one or more co-morbidities, compared to 41.6% (252/606) of those discharged. Patients who were older than 50 years, with diabetes mellitus, hypertension, chronic renal illness, and cancer had a statistically significant relationship with mortality.

Conclusion

These findings call for a more comprehensive approach to the control of non-communicable diseases, the allocation of sufficient resources for ICU care during outbreaks, an improvement in the quality of health care available to Nigerians, and further research into the relationship between obesity and COVID-19 in Nigerians.

Real-World Experience of the Comparative Effectiveness and Safety of Molnupiravir and Nirmatrelvir/Ritonavir in High-Risk Patients with COVID-19 in a Community Setting

Molnupiravir (MOV) and nirmatrelvir/ritonavir (NMV/r) are efficacious oral antiviral agents for patients with the 2019 coronavirus (COVID-19). However, little is known about their effectiveness in older adults and those at high risk of disease progression. This retrospective single-center observational study assessed and compared the outcomes of COVID-19 treated with MOV and NMV/r in a real-world community setting. We included patients with confirmed COVID-19 combined with one or more risk factors for disease progression from June to October 2022. Of 283 patients, 79.9% received MOV and 20.1% NMV/r. The mean patient age was 71.7 years, 56.5% were men, and 71.7% had received ≥3 doses of vaccine. COVID-19-related hospitalization (2.8% and 3.5%, respectively; p = 0.978) or death (0.4% and 3.5%, respectively; p = 0.104) did not differ significantly between the MOV and NMV/r groups. The incidence of adverse events was 2.7% and 5.3%, and the incidence of treatment discontinuation was 2.7% and 5.3% in the MOV and NMV/r groups, respectively. The real-world effectiveness of MOV and NMV/r was similar among older adults and those at high risk of disease progression. The incidence of hospitalization or death was low.

Machine learning prediction for COVID-19 disease severity at hospital admission

IMPORTANCE

Early prognostication of patients hospitalized with COVID-19 who may require mechanical ventilation and have worse outcomes within 30 days of admission is useful for delivering appropriate clinical care and optimizing resource allocation.

OBJECTIVE

To develop machine learning models to predict COVID-19 severity at the time of the hospital admission based on a single institution data.

DESIGN, SETTING, AND PARTICIPANTS

We established a retrospective cohort of patients with COVID-19 from University of Texas Southwestern Medical Center from May 2020 to March 2022. Easily accessible objective markers including basic laboratory variables and initial respiratory status were assessed using Random Forest's feature importance score to create a predictive risk score. Twenty-five significant variables were identified to be used in classification models. The best predictive models were selected with repeated tenfold cross-validation methods.

MAIN OUTCOMES AND MEASURES

Among patients with COVID-19 admitted to the hospital, severity was defined by 30-day mortality (30DM) rates and need for mechanical ventilation.

RESULTS

This was a large, single institution COVID-19 cohort including total of 1795 patients. The average age was 59.7 years old with diverse heterogeneity. 236 (13%) required mechanical ventilation and 156 patients (8.6%) died within 30 days of hospitalization. Predictive accuracy of each predictive model was validated with the 10-CV method. Random Forest classifier for 30DM model had 192 sub-trees, and obtained 0.72 sensitivity and 0.78 specificity, and 0.82 AUC. The model used to predict MV has 64 sub-trees and returned obtained 0.75 sensitivity and 0.75 specificity, and 0.81 AUC. Our scoring tool can be accessed at https://faculty.tamuc.edu/mmete/covid-risk.html .

CONCLUSIONS AND RELEVANCE

In this study, we developed a risk score based on objective variables of COVID-19 patients within six hours of admission to the hospital, therefore helping predict a patient's risk of developing critical illness secondary to COVID-19.

CD4+ T-Cell Depression is Linked to the Severity of COVID-19 and Predicts Mortality

Objective

Most patients with coronavirus disease (COVID-19) have abnormalities of lymphocyte subsets. This study aimed to determine the distribution of lymphocytes in patients with various severity levels of COVID-19 and to describe the relationship between the CD4+ T helper and prognosis.

Materials and Methods

Adult (>18 years old) patients with COVID-19 who followed up in a tertiary hospital were included in the study prospectively. Demographic and clinical characteristics of the patients were obtained from the hospital records. Peripheral flow cytometry was studied in patients with different severity of COVID-19 and different prognoses. Next, we analyzed the characteristics and predictive values of lymphocyte subsets in COVID-19 patients.

Results

Totally 86 patients were included in the study, of which 21 (24.4%) had asymptomatic, 23 (26.7%) had mild/moderate, and 42 (48.8%) had severe/critical COVID-19. Severe/critical patients had lower lymphocyte levels and older age than asymptomatic patients (p<0.001 and p<0.001, respectively). We determined that decreased CD4+ T cell ratio (p<0.001) and CD4+ /CD8+ ratio (p<0.001) were indicative of the severity of the disease. CD4+ T cell ratio on admission (odds ratio [OR]=0.858; p=0.033), day seven CD4+ T cell ratio (OR=0.840; p=0.029), and C-reactive protein (CRP) levels (OR=1.014; p=0.043) were prognostic factors for mortality. According to receiver operating characteristics (ROC) curve analysis, the area under the curve was greater than 0.9 for decreased CD4 + T cell ratio on admission and the seventh day.

Conclusion

A low CD4+ T helper ratio predicts a poor prognosis. In combination with CRP, it can be used in clinical follow-up.

COVID-19 long-term sequelae: Omicron versus Alpha and Delta variants

BACKGROUND

The study aimed to assess the association between three predominant SARS-CoV-2 variants (Alpha, Delta, and Omicron) and the risk of developing long COVID (persistence of physical, medical, and cognitive symptoms more than 4 weeks after infection), post-COVID-19 syndrome (symptoms extending beyond 12 weeks), and viral persistence (testing positive beyond 4 weeks despite clinical resolution).

METHODS

Retrospective study of 325 patients hospitalized for COVID-19 with genomic sequencing information. For each SARS-CoV-2 variant, sample characteristics, frequency of symptoms, and long-term sequelae were compared using Chi-squared test, Fisher's exact test, Kruskal-Wallis test, and Dunn's test as appropriate. Odds ratios (OR) were calculated using logistic regression models to assess the association of risk factors and sequelae.

RESULTS

The adjusted model showed that the Omicron (vs Alpha) variant (OR, 0.30; 95% CI0.16-0.56), admission to ICU (OR, 1.14; 95% CI 1.05-1.23), and being treated with antiviral or immunomodulatory drugs (OR, 2.01; 95% CI 1.23-3.27) predicted long COVID and post-COVID-19 syndrome. Viral persistence showed no difference between variants.

CONCLUSIONS

The Omicron variant was associated with significantly lower odds of developing long-term sequelae from COVID-19 compared with previous variants, while severity of illness indicators increased the risk. Vaccination status, age, sex, and comorbidities were not found to predict sequelae development. This information has implications for both health managers and clinicians when deciding on the appropriate clinical management and subsequent outpatient follow-up of these patients. More studies with non-hospitalized patients are still necessary.

Proof-of-Concept Analysis of B Cell Receptor Repertoire in COVID-19 Patients Undergoing ECMO by Single-Cell V(D)J and Gene Expression Sequencing

SARS-CoV-2, which causes COVID-19, has altered human activities all over the world and has become a global hazard to public health. Despite considerable advancements in pandemic containment techniques, in which vaccination played a key role, COVID-19 remains a global threat, particularly for frail patients and unvaccinated individuals, who may be more susceptible to developing ARDS. Several studies reported that patients with COVID-19-related ARDS who were treated with ECMO had a similar survival rate to those with COVID-19-unrelated ARDS. In order to shed light on the potential mechanisms underlying the COVID-19 infection, we conducted this proof-of-concept study using single-cell V(D)J and gene expression sequencing of B cells to examine the dynamic changes in the transcriptomic BCR repertoire present in patients with COVID-19 at various stages. We compared a recovered and a deceased COVID-19 patient supported by ECMO with one COVID-19-recovered patient who did not receive ECMO treatment and one healthy subject who had never been infected previously. Our analysis revealed a downregulation of FXYD, HLA-DRB1, and RPS20 in memory B cells; MTATP8 and HLA-DQA1 in naïve cells; RPS4Y1 in activated B cells; and IGHV3-73 in plasma cells in COVID-19 patients. We further described an increased ratio of IgA + IgG to IgD + IgM, suggestive of an intensive memory antibody response, in the COVID ECMO D patient. Finally, we assessed a V(D)J rearrangement of heavy chain IgHV3, IGHJ4, and IGHD3/IGHD2 families in COVID-19 patients regardless of the severity of the disease.

Developing a mortality risk prediction model using data of 3663 hospitalized COVID-19 patients: a retrospective cohort study in an Egyptian University Hospital

PURPOSE

Since the declaration of COVID-19 as a pandemic, a wide between-country variation was observed regarding in-hospital mortality and its predictors. Given the scarcity of local research and the need to prioritize the provision of care, this study was conducted aiming to measure the incidence of in-hospital COVID-19 mortality and to develop a simple and clinically applicable model for its prediction.

METHODS

COVID-19-confirmed patients admitted to the designated isolation areas of Ain-Shams University Hospitals (April 2020-February 2021) were included in this retrospective cohort study (n = 3663). Data were retrieved from patients' records. Kaplan-Meier survival and Cox proportional hazard regression were used. Binary logistic regression was used for creating mortality prediction models.

RESULTS

Patients were 53.6% males, 4.6% current smokers, and their median age was 58 (IQR 41-68) years. Admission to intensive care units was 41.1% and mortality was 26.5% (972/3663, 95% CI 25.1-28.0%). Independent mortality predictors-with rapid mortality onset-were age ≥ 75 years, patients' admission in critical condition, and being symptomatic. Current smoking and presence of comorbidities particularly, obesity, malignancy, and chronic haematological disorders predicted mortality too. Some biomarkers were also recognized. Two prediction models exhibited the best performance: a basic model including age, presence/absence of comorbidities, and the severity level of the condition on admission (Area Under Receiver Operating Characteristic Curve (AUC) = 0.832, 95% CI 0.816-0.847) and another model with added International Normalized Ratio (INR) value (AUC = 0.842, 95% CI 0.812-0.873).

CONCLUSION

Patients with the identified mortality risk factors are to be prioritized for preventive and rapid treatment measures. With the provided prediction models, clinicians can calculate mortality probability for their patients. Presenting multiple and very generic models can enable clinicians to choose the one containing the parameters available in their specific clinical setting, and also to test the applicability of such models in a non-COVID-19 respiratory infection.

Correlation between UV Index, Temperature and Humidity with Respect to Incidence and Severity of COVID 19 in Spain

BACKGROUND

Various studies support the inverse correlation between solar exposure and Coronavirus SARS-CoV-2 infection. In Spain, from the Canary Islands to the northern part of the country, the global incidence of COVID-19 is different depending on latitude, which could be related to different meteorological conditions such as temperature, humidity, and ultraviolet index (UVI). The objective of the present work was to analyze the association between UVI, other relevant environmental factors such as temperature and humidity, and the incidence, severity, and mortality of COVID-19 at different latitudes in Spain.

METHODS

An observational prospective study was conducted, recording the numbers of new cases, hospitalizations, patients in critical units, mortality rates, and annual variations related to UVI, temperature, and humidity in five different provinces of Spain from January 2020 to February 2021.

RESULTS

Statistically significant inverse correlations (Spearman coefficients) were observed between UVI, temperature, annual changes, and the incidence of COVID-19 cases at almost all latitudes.

CONCLUSION

Higher ultraviolet radiation levels and mean temperatures could contribute to reducing COVID-19 incidence, hospitalizations, and mortality.

Biological sex and age-related differences shape the antiviral response to SARS-CoV-2 infection

For the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, clinical manifestations are broad and highly heterogeneous for both sexes. We aimed to determine how biological sex and age impact immune gene expression, particularly influencing the humoral neutralizing antibody (NAb) response and the cytokine production in coronavirus disease 2019 (COVID-19) subjects. The immune gene expression, according to biological sex and age, was assessed using the genome wide expression profile of blood proteins from healthy individuals using the Genotype Tissue Expression (GTEx) database. Moreover, anti-SARS-CoV-2 neutralizing antibody titers and cytokine levels were determined in blood samples from 141 COVID-19 individuals from Medellín, Colombia. Among subjects with COVID-19, males had statistically significantly higher median NAb titers and serum concentrations of interleukin-6 and CC chemokine ligand 3 than females. Overall, our findings point out a more robust innate immune response in women that could help recognize and restrain the virus faster than in men.

The possible therapeutic role of curcumin and quercetin in the early-stage of COVID-19-Results from a pragmatic randomized clinical trial

Background

Curcumin (CUR) and quercetin (QUE), two natural polyphenols, possess diverse biological activities including broad-spectrum antiviral, antioxidant, and immunomodulatory effects. Both CUR and QUE have shown inhibition of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in in vitro assays.

Objective

In the present study we aimed to assess the possible treatment benefits of a combined curcumin and quercetin (CUR-QUE) oral supplement, alongside standard of care (SOC), in the early-stage COVID-19 infection.

Methods

This was an exploratory, pragmatic, open-label, randomized controlled clinical trial, conducted at the Department of Pathology, Liaquat University of Medical and Health Sciences, Jamshoro, PK. The study compared the treatment effect of an oral CUR-QUE supplement plus SOC vs. SOC alone, in the early-stage/mild to moderately symptomatic COVID-19 outpatients. Patients were randomized in a 1:1 ratio to CUR-QUE (n = 25) and control (n = 25) treatment groups. The CUR-QUE supplementation consisted of a daily intake of 168 mg curcumin and 260 mg quercetin, as two soft capsules, to be taken twice a day at home for 14 days.

Results

After one-week of treatment, most of the patients in the CUR-QUE group showed an expedited clearance of the viral infection i.e., 18 (72.0%) vs. 6 (24.0%) patients in the control group tested negative for SARS-CoV-2 in the nasal-oropharyngeal swab reverse transcription-polymerase chain reaction (RT-PCR) analysis (p = 0.0002). In addition, COVID-19-associated acute symptoms were also speedily resolved in the CUR-QUE treated patients, i.e., 10 (40.0%) vs. 4 (16.0%) patients in the control group (p = 0.061). The CUR-QUE supplementation therapy was well-tolerated by all 25 patients and no treatment-emergent effects or serious adverse events were reported.

Conclusion

The results revealed in this exploratory study suggest a possible therapeutic role of curcumin and quercetin in the early-stage of COVID-19. It is proposed that the two agents possibly acting in synergy, interfere the SARS-CoV-2 replication, and thus help a speedy recovery in the early-stage of COVID-19. Further research is highly encouraged.

Clinical trial registration

Clinicaltrials.gov, Identifier NCT04603690.

Inventory study of an early pandemic COVID-19 cohort in South-Eastern Sweden, focusing on neurological manifestations

BACKGROUND

Neurological manifestations in patients with COVID-19 have been reported previously as outcomes of the infection. The purpose of current study was to investigate the occurrence of neurological signs and symptoms in COVID-19 patients, in the county of Östergötland in southeastern Sweden.

METHODS

This is a retrospective, observational cohort study. Data were collected between March 2020 and June 2020. Information was extracted from medical records by a trained research assistant and physician and all data were validated by a senior neurologist.

RESULTS

Seventy-four percent of patients developed at least one neurological symptom during the acute phase of the infection. Headache (43%) was the most common neurological symptom, followed by anosmia and/or ageusia (33%), confusion (28%), hallucinations (17%), dizziness (16%), sleep disorders in terms of insomnia and OSAS (Obstructive Sleep Apnea) (9%), myopathy and neuropathy (8%) and numbness and tingling (5%). Patients treated in the ICU had a higher male presentation (73%). Several risk factors in terms of co-morbidities, were identified. Hypertension (54.5%), depression and anxiety (51%), sleep disorders in terms of insomnia and OSAS (30%), cardiovascular morbidity (28%), autoimmune diseases (25%), chronic lung diseases (24%) and diabetes mellitus type 2 (23%) founded as possible risk factors.

CONCLUSION

Neurological symptoms were found in the vast majority (74%) of the patients. Accordingly, attention to neurological, mental and sleep disturbances is warranted with involvement of neurological expertise, in order to avoid further complications and long-term neurological effect of COVID-19. Furthermore, risk factors for more severe COVID-19, in terms of possible co-morbidities that identified in this study should get appropriate attention to optimizing treatment strategies in COVID-19 patients.

THE ROLE OF THROMBOSIS RISK SCALES LIKE PROGRESSION PREDICTORS OF COVID-19-ASSOCIATED PNEUMONIA

OBJECTIVE

The aim: To determine the risk factors for progression by establishing the diagnostic and prognostic role of PPS and ISTH DIC score in patients with COVID-19 required hospitalization.

PATIENTS AND METHODS

Materials and methods: Main group was 130 patients with COVID-19, divided depending on the severity into 3 subgroups. Patients were examined twice. On visit 1 and visit 2 (after 7-14 days after hospitalization). Were provided: physical examination, lung ultrasound (LUS), laboratory tests (D-dimer, coagulogram). Were counted PPS and ISTH DIC score. Non-parametrical statistic, ROC analysis.

RESULTS

Results: The level of D-dimer was significantly elevated in the examined patients and correlated with the severity of the disease. The number of points on the scales ISTH DIC and Padua had a significant difference between the subgroups. The maximum number of points was obtained by patients of subgroup 3, which indicates the maximum risk of thrombotic complications, as well as DIC. The ROC analysis showed that among coagulation parameters the most sensitive and specific factors associated with the progression of the clinical course is the D-dimer at admission.

CONCLUSION

Conclusions: Thus, the determination of D-dimer, fibrinogen, as well as usage of the DIC and Padua scales is a useful tool not only to estimate the severity of COVID-19, but also to predict the prognosis. Thus, the level of D-dimer above 260 ng/ml, as well as the presence of three or more points on the DIC scale and/or five or more points on the Padua scale in patients with COVID-19 during hospitalization significantly increases the risk of progression clinical process.

SARS-CoV-2 in brief: from virus to prevention

The recent outbreak of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), ahighly transmissible virus with a likely animal origin, has posed major and unprecedentedchallenges to millions of lives across the affected nations of the world. This outbreak firstoccurred in China, and despite massive regional and global attempts shortly thereafter, itspread to other countries and caused millions of deaths worldwide. This review presents keyinformation about the characteristics of SARS-CoV-2 and its associated disease (namely,coronavirus disease 2019) and briefly discusses the origin of the virus. Herein, we also brieflysummarize the strategies used against viral spread and transmission.

Impact of a pulmonary rehabilitation program on social disadvantage and physical activity data of postCOVID19 patients: A North-African pilot study

Background In addition to the cardiorespiratory, muscular, and neurological manifestations, coronavirus disease 2019 (COVID-19) alters patients' health-related quality of life (HRQoL), induces a large variety of psychiatric manifestations, and reduces mobility and motor activity. Several studies have raised the impact of a pulmonary rehabilitation program (PRP) on social disadvantage ( e.g., HRQoL, anxiety, depression) and physical activity of COVID-19 patients, but very few have been performed in low-income countries. This study aimed to investigate the impact of a PRP on post-COVID-19 HRQoL, hospital anxiety and depression (HAD), and physical activity in Tunisian post-COVID19-patients. Methods This was a cross-sectional study in an outpatient care setting. Patients with post-COVID-19 were included. They completed an interview (including three questionnaires) before and after a PRP (three sessions/week for four weeks, each session was 70 minutes in duration, PRP items: aerobic cycle endurance, strength training, and education). The VQ11 questionnaire assessed functional dimension, psychological dimension, relational dimension, and total score; HAD appraised depression and anxiety; and Voorrips physical activity assessed daily activity, physical activity, leisure activity, and total scores. Data were expressed as mean±standard deviation in PRP change (PRP change=after-PRP values - before-PRP values). Results In total, 14 moderate to severe post-COVID-19 patients (61±4 years) were included. The PRP significantly improved the i) functional, psychological, and relational dimensions, and the VQ11 total score by 1.79±1.58 (p=0.0033), 2.00±2.15 (p=0.0108), 1.57±1.50 (p=0.0077), and 5.36±3.97 (p=0.0015), respectively; ii) HAD anxiety and depression scores by 2.07±2.40 (p=0.0076), and 2.57±3.08 (p=0.0058); and iii) physical activity and total scores by 1.75±2.44 (p=0.0251), and 1.78±2.65 (p=0.0341), respectively. Conclusion The PRP improved HRQoL, HAD, and physical activity of Tunisian post-COVID-19 patients.

Clinical features and effectiveness of Chinese medicine in patients with COVID-19 from overseas: A retrospective study in Xiamen, China

COVID-19, referred to as new coronary pneumonia, is an acute infectious disease caused by a new type of coronavirus SARS-CoV-2. To evaluate the effect of integrated Chinese medicine and Western medicine in patients with COVID-19 from overseas. Data were collected from 178 COVID-19 patients overseas at First Affiliated Hospital of Xiamen University from April 1, 2021 to July 31, 2021. These patients received therapy of integrated Chinese medicine and western medicine. Demographic data and clinical characteristics were extracted and analyzed. In addition, the prescription which induced less length of PCR positive days and hospitalization days than the median value was obtained. The top 4 frequently used Chinese medicine and virus-related genes were analyzed by network pharmacology and bioinformatics analysis. According to the chest computed tomography (CT) measurement, abnormal lung findings were observed in 145 subjects. The median length of positive PCR/hospitalization days was 7/7 days for asymptomatic subjects, 14/24 days for mild subjects, 10/15 days for moderate subjects, and 14/20 days for severe subjects. The most frequently used Chinese medicine were Scutellaria baicalensis (Huangqin), Glycyrrhiza uralensis (Gancao), Bupleurum chinense (Chaihu), and Pinellia ternata (Banxia). The putative active ingredients were baicalin, stigmasterol, sigmoidin-B, cubebin, and troxerutin. ACE, SARS-CoV-2 3CL, SARS-CoV-2 Spike, SARS-CoV-2 ORF7a, and caspase-6 showed good binding properties to active ingredients. In conclusion, the clinical results showed that integrated Chinese medicine and Western medicine are effective in treating COVID-19 patients from overseas. Based on the clinical outcomes, the putative ingredients from Chinese medicine and the potential targets of SARS-CoV-2 were provided, which could provide a reference for the clinical application of Chinese medicine in treating COVID-19 worldwide.

Skin-Attachable Sensors for Biomedical Applications

With the growing concern about human health issues, especially during the outbreak of the COVID-19 pandemic, the demand for personalized healthcare regarding disease prevention and recovery is increasing. However, tremendous challenges lie in both limited public medical resources and costly medical diagnosis approaches. Recently, skin-attachable sensors have emerged as promising health monitoring platforms to overcome such difficulties. Owing to the advantages of good comfort and high signal-to-noise ratio, skin-attachable sensors enable household, real-time, and long-term detection of weak physiological signals to efficiently and accurately monitor human motion, heart rate, blood oxygen saturation, respiratory rate, lung and heart sound, glucose, and biomarkers in biomedical applications. To further improve the integration level of biomedical skin-attachable sensors, efforts have been made in combining multiple sensing techniques with elaborate structural designs. This review summarizes the recent advances in different functional skin-attachable sensors, which monitor physical and chemical indicators of the human body. The advantages, shortcomings, and integration strategies of different mechanisms are presented. Specially, we highlight sensors monitoring pulmonary function such as respiratory rate and blood oxygen saturation for their potential usage in the COVID-19 pandemic. Finally, the future development of skin-attachable sensors is envisioned.

Modelling the first wave of COVID-19 in India

Estimating the burden of COVID-19 in India is difficult because the extent to which cases and deaths have been undercounted is hard to assess. Here, we use a 9-component, age-stratified, contact-structured epidemiological compartmental model, which we call the INDSCI-SIM model, to analyse the first wave of COVID-19 spread in India. We use INDSCI-SIM, together with Bayesian methods, to obtain optimal fits to daily reported cases and deaths across the span of the first wave of the Indian pandemic, over the period Jan 30, 2020 to Feb 15, 2021. We account for lock-downs and other non-pharmaceutical interventions (NPIs), an overall increase in testing as a function of time, the under-counting of cases and deaths, and a range of age-specific infection-fatality ratios. We first use our model to describe data from all individual districts of the state of Karnataka, benchmarking our calculations using data from serological surveys. We then extend this approach to aggregated data for Karnataka state. We model the progress of the pandemic across the cities of Delhi, Mumbai, Pune, Bengaluru and Chennai, and then for India as a whole. We estimate that deaths were undercounted by a factor between 2 and 5 across the span of the first wave, converging on 2.2 as a representative multiplier that accounts for the urban-rural gradient. We also estimate an overall under-counting of cases by a factor of between 20 and 25 towards the end of the first wave. Our estimates of the infection fatality ratio (IFR) are in the range 0.05—0.15, broadly consistent with previous estimates but substantially lower than values that have been estimated for other LMIC countries. We find that approximately 35% of India had been infected overall by the end of the first wave, results broadly consistent with those from serosurveys. These results contribute to the understanding of the long-term trajectory of COVID-19 in India.

Making sense of publicly available epidemiological data for the COVID-19 pandemic in India presents multiple challenges, largely to do with the quality of the data. Here, we describe ways of addressing these questions by studying the data using a well-parameterised, detailed compartmental model together with Bayesian methods, alongside information derived from pan-India serological surveys. We focus on the first wave of the Indian pandemic, across the interval Jan 30, 2020 to Feb 15, 2021. We estimate that deaths were under-counted by a factor between 2 and 5 across the span of the first wave and that cases were under-counted by a factor of between 20 and 25 towards its end. We estimate an infection fatality ratio (IFR) in the range 0.05—0.15. We find that approximately 35% of India had been infected overall by the end of the first wave, a number that helps us better understand the context in which the second and later waves unfolded.

Clinical clustering with prognostic implications in Japanese COVID-19 patients: report from Japan COVID-19 Task Force, a nation-wide consortium to investigate COVID-19 host genetics

Background

The clinical course of coronavirus disease (COVID-19) is diverse, and the usefulness of phenotyping in predicting the severity or prognosis of the disease has been demonstrated overseas. This study aimed to investigate clinically meaningful phenotypes in Japanese COVID-19 patients using cluster analysis.

Methods

From April 2020 to May 2021, data from inpatients aged ≥ 18 years diagnosed with COVID-19 and who agreed to participate in the study were collected. A total of 1322 Japanese patients were included. Hierarchical cluster analysis was performed using variables reported to be associated with COVID-19 severity or prognosis, namely, age, sex, obesity, smoking history, hypertension, diabetes mellitus, malignancy, chronic obstructive pulmonary disease, hyperuricemia, cardiovascular disease, chronic liver disease, and chronic kidney disease.

Results

Participants were divided into four clusters: Cluster 1, young healthy (n = 266, 20.1%); Cluster 2, middle-aged (n = 245, 18.5%); Cluster 3, middle-aged obese (n = 435, 32.9%); and Cluster 4, elderly (n = 376, 28.4%). In Clusters 3 and 4, sore throat, dysosmia, and dysgeusia tended to be less frequent, while shortness of breath was more frequent. Serum lactate dehydrogenase, ferritin, KL-6, d-dimer, and C-reactive protein levels tended to be higher in Clusters 3 and 4. Although Cluster 3 had a similar age as Cluster 2, it tended to have poorer outcomes. Both Clusters 3 and 4 tended to exhibit higher rates of oxygen supplementation, intensive care unit admission, and mechanical ventilation, but the mortality rate tended to be lower in Cluster 3.

Conclusions

We have successfully performed the first phenotyping of COVID-19 patients in Japan, which is clinically useful in predicting important outcomes, despite the simplicity of the cluster analysis method that does not use complex variables.

Integrating in silico and in vivo approach for investigating the role of polyherbal oil in prevention and treatment of COVID-19 infection

Currently, there are no FDA approved antiviral drugs available to treat COVID-19 patients. Also, due to emergence of new SARS-CoV-2 variants, the protective efficacy of vaccines could be reduced, hence it is urgent to have alternative treatments for combating the SARS-CoV-2 infection. Since, there is a long-standing history of herbal medicine in the treatment of respiratory diseases. In the present study, we investigated two polyherbal oil blend viz. Sudarshan AV and Elixir AV (SAV and EAV) in inhibiting SARS-COV-2. From GC-MS analysis of polyherbal oils (SAV and EAV) a total of 11 active compounds were selected, on the basis of their abundance and activity. Further, from the molecular docking studies, we found an inhibitory effect of these compounds on viral envelope and membrane, spike proteins whilst an agonistic effect with human host receptor angiotensin-converting enzyme 2 (ACE2) implicating the crucial role of the individual compound in resistance of SARS-CoV-2. Since, the in-silico results suggest that polyherbal oil (SAV and EAV) contributes in preventing the entry of SARS-CoV-2 into the human body, we further investigated the efficacy of polyherbal formulated essential oil (FEO; SAV & EAV) in prevention and treatment of COVID-19 in hamster model. The male golden Syrian hamsters (n = 23) were divided into 5 groups i.e., Group 1: Control (n = 3); Group 2: Infected (n = 5); Group 3: Infected + Remdesivir (n = 5); Group 4: Infected + FEO (n = 5) and Group 5: Prophylactic FEO + Infected (n = 5). In both treatment and prophylactic groups, the FEO's significantly reduced the lung injury investigated histo-pathologically and viral load expression measured by real time PCR in comparison to infected hamsters. Furthermore, cytokines expression analysis clearly highlighted the efficacy of FEO's due to its anti-inflammatory activity and overall protection in treatment groups. In conclusion, the FEO (SAV & EAV) seem to be potent in both prevention and treatment of COVID-19 and related lung injury.

A severe presentation of breakthrough infection caused by the Omicron variant with radiological findings of COVID-19 pneumonia in an elderly woman

Omicron variant of COVID-19 is characterized by exceptional transmissibility and by immune evasion with the ability infect people with naturally acquired or vaccine-induced immunity. However, lung involvement is poorly reported in patients who resulted positive by this new COVID-19 variant. COVID-19 breakthrough infections are defined as COVID-19 infection in fully vaccinated patients. Herein, we present a case of breakthrough infection in an elderly woman who came in emergency with dyspnea and with findings of COVID-19 pneumonia on chest computed tomography. The patient was vaccinated with a booster dose of an mRNA vaccine some months earlier and the Omicron variant was detected on real-time reverse-transcription polymerase chain reaction. However, the patient's condition remained stable. For our knowledge we report the first case with lung involvement due to Omicron variant in an elderly after the booster dose of mRNA vaccine. This case highlights as COVID-19 breakthrough infections may represent some concerns in the elderly patients in presence of virus variants.

Biochemical Parameters as Prognostic Markers in Severely Ill COVID-19 Patients

Background

Prognostication plays a pivotal role in critical care medicine. Its importance is indisputable in the management of coronavirus disease 2019 (COVID-19), as the presentation of this disease may vary from docile, self-limiting symptoms to lethal conditions. Amid the COVID-19 pandemic, much emphasis was initially placed on molecular and serological testing. However, it was realized later that routine laboratory tests also provide key information in terms of the severity of the disease and thus could be used to predict the outcome of these patients.

Methodology

The aim of our study was to evaluate the biochemical parameters as prognostic markers in severely ill COVID-19 patients. We carried out a retrospective, case-control study. The study population was comprised of all severely ill COVID-19 patients admitted between October 2020 and January 2021 at our level 3 COVID hospital. Cases were defined as the patients who expired despite treatment and all resuscitative measures as per the standard operating procedures (SOPs) of our COVID intensive care unit (ICU) while controls were defined as the patients that were transferred out of the COVID ICU for further recovery. The detailed history, findings of physical examination, vitals recorded by point of care testing (POCT) devices at our ICU, clinical diagnosis, and the results of the biochemical analysis were recorded in a specially designed pro forma. The biochemical parameters recorded at the time of admission were compared between the groups of controls and cases in order to evaluate their role as predictors of mortality using appropriate statistical methods. P-values less than 0.05 were considered statistically significant. For all the parameters that showed a statistically significant difference, receiver operating characteristics (ROC) analysis was done to assess the utility of biochemical parameters as predictors of mortality or survival. Areas under the curve (AUCs) of 0.6 to 0.7, 0.7 to 0.8, 0.8 to 0.9, and >0.9 were considered acceptable, fair, good, and excellent for discrimination, respectively.

Results

Of the 178 severely ill COVID-19 patients enrolled in the study, 86 were controls and 92 were cases (52% mortality). Serum urea (p<0.0001), creatinine (p=0.0019), aspartate transaminase (AST) (p=0.0104), lactate dehydrogenase (LDH) (p=0.0001), procalcitonin (PCT) (p=0.0344), and interleukin 6 (IL-6) (p=0.0311) levels were significantly higher (p<0.05), while total protein (p=0.0086), albumin (p<0.0001), and indirect bilirubin (p=0.0147) levels were significantly lower (p<0.05) in cases as compared to controls. The difference was statistically insignificant (p>0.05) for serum sodium, potassium, total and direct bilirubin, globulin, alanine transaminase (ALT), alkaline phosphatase (ALP), D-dimer, and ferritin. On ROC analysis, urea was fair (AUC=0.721), creatinine (AUC=0.698) and IL-6 (AUC=0.698) were acceptable predictors of mortality, while albumin (AUC=0.698) was an acceptable predictor of survival in severely ill COVID-19 patients during their intensive care stay.

Conclusion

Understanding the pathophysiological changes associated with the severity of COVID-19 in terms of an alteration of biochemical parameters is a pressing priority. Our study highlights the importance of routine laboratory tests in predicting outcomes in severely ill COVID-19 patients.

Coagulopathy of Dengue and COVID-19: Clinical Considerations

Thrombocytopenia and platelet dysfunction commonly occur in both dengue and COVID-19 and are related to clinical outcomes. Coagulation and fibrinolytic pathways are activated during an acute dengue infection, and endothelial dysfunction is observed in severe dengue. On the other hand, COVID-19 is characterised by a high prevalence of thrombotic complications, where bleeding is rare and occurs only in advanced stages of critical illness; here thrombin is the central mediator that activates endothelial cells, and elicits a pro-inflammatory reaction followed by platelet aggregation. Serological cross-reactivity may occur between COVID-19 and dengue infection. An important management aspect of COVID-19-induced immunothrombosis associated with thrombocytopenia is anticoagulation with or without aspirin. In contrast, the use of aspirin, nonsteroidal anti-inflammatory drugs and anticoagulants is contraindicated in dengue. Mild to moderate dengue infections are treated with supportive therapy and paracetamol for fever. Severe infection such as dengue haemorrhagic fever and dengue shock syndrome often require escalation to higher levels of support in a critical care facility. The role of therapeutic platelet transfusion is equivocal and should not be routinely used in patients with dengue with thrombocytopaenia and mild bleeding. The use of prophylactic platelet transfusion in dengue fever has strained financial and healthcare systems in endemic areas, together with risks of transfusion-transmitted infections in low- and middle-income countries. There is a clear research gap in the management of dengue with significant bleeding.

The association of APOE genotype with COVID-19 disease severity

COVID-19 has caused the recent pandemic of respiratory infection, which threatened global health. The severity of the symptoms varies among affected individuals, from asymptotic or mild signs to severe or critical illness. Genetic predisposition explains the variation in disease severity among patients who suffer from severe symptoms without any known background risk factors. The present study was performed to show the association between APOE genotype and the severity of COVID-19 disease. The APOE genotype of 201 COVID-19 patients (101 patients with asymptomatic to mild form of the disease as the control group and 100 patients with severe to critical illness without any known background risk factors as the case group) were detected via multiplex tetra-primer ARMS-PCR method. Results showed that the e4 allele increased the risk of the COVID-19 infection severity more than five times and the e4/e4 genotype showed a 17-fold increase in the risk of severe disease. In conclusion, since our study design was based on the exclusion of patients with underlying diseases predisposing to severe form of COVID-19 and diseases related to the APOE gene in the study population, our results showed that the e4 genotype is independently associated with the severity of COVID-19 disease. However, further studies are needed to confirm these findings in other nations and to demonstrate the mechanisms behind the role of these alleles in disease severity.

The Relation between Immunological Features and the Positive SARS-CoV-2 Nucleic Acid in Patients with Nonsevere COVID⁃19

Objective

The novel coronavirus nucleic acid results are the core indicators of illness monitoring. This study aimed to evaluate the relationship between immunological features and positive SARS-CoV-2 nucleic acid by analyzing the clinical and immunological features in nonsevere COVID-19 cases.

Methods

Data from nonsevere COVID-19 patients admitted to Haihe Hospital from May 2020 to June 2021 were retrospectively reviewed and analyzed.

Results

(1) A total of 122 cases were reviewed in the present study, including 38 mild and 84 moderate cases. The average age of mild cases was significantly different from moderate cases (P < 0.001). Eight patients complained of hyposmia and it was more frequent in mild cases (P < 0.001). The nucleic acid positive duration (NPD) of nonsevere novel coronavirus was 20.49 (confidence interval (CI) 17.50-3.49) days. (2) The levels of specific IgM and IgG for COVID-19 were higher in mild cases than in moderate cases (P=0.023 and P=0.047, respectively). (3) The correlation analysis with antibodies and T-cell subtypes showed that the lymphocyte (LYM) count, T cells, CD4⁺T cells, and CD8⁺T cells had a linear correlation with NPD. (4) Among the 93 patients monitored, 62 COVID-19 cases presented a progressive rise of specific IgM and IgG. The daily increase rates of IgM and IgG were 38.42% (CI 28.22-48.61%) and 24.90% (CI 0.23-29.58%), respectively.

Conclusion

The levels and daily increase rates of specific IgM and IgG against the virus can vary between cases. The NPD presented a linear correlation with the LYM, T cells, CD4⁺T cells, and CD8+T cells. Hence, more attention should be paid to these indicators in clinical practice.

COVID-19 Associated Guillain–Barré Syndrome: A Report of Nine New Cases and a Review of the Literature

Background: Guillain–Barré syndrome (GBS)—a rare condition characterized by acute-onset immune-mediated polyneuropathy—has been registered as a neurological manifestation of COVID-19, suggesting a possible link between these two conditions. Methods: We report a case series of patients with COVID-19-related GBS hospitalized in the Neurology Department of Colentina Clinical Hospital, Bucharest, Romania, between March 2020 and March 2021. Several variables were analyzed, such as the mean interval between the onset of COVID-19 symptoms and neurological ones, clinical features, treatment course, and outcome. Further on, we conducted a thorough literature review based on the PubMed and ScienceDirect scientific databases. Results: A total of 9 COVID-19 patients developed symptoms of GBS, out of which in 7, it manifested as an acute inflammatory demyelinating polyneuropathy (AIDP). Five patients presented respiratory failure, 2 requiring mechanical ventilation. All patients received a course of intravenous immunoglobulins, 2 additionally requiring plasma exchange. Upon discharge, all but 1 patient (who had not regained the ability to walk) had a positive outcome, and 1 died during admission. In the literature review, we analyzed the published sources at the time of writing. Conclusions: A link between COVID-19 and GBS might be possible; therefore, increased vigilance is required in the early identification of these cases for prompt diagnosis and treatment. Some notable differences such as an earlier onset of GBS symptoms, higher respiratory dysfunction, and higher mortality rates in COVID-19 patients have been observed between the presentation of GBS in the context of COVID-19 and GBS of other causes.

Metabolic Reprogramming in SARS-CoV-2 Infection Impacts the Outcome of COVID-19 Patients

Severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2) infection triggers inflammatory clinical stages that affect the outcome of patients with coronavirus disease 2019 (COVID-19). Disease severity may be associated with a metabolic imbalance related to amino acids, lipids, and energy-generating pathways. The aim of this study was to characterize the profile of amino acids and acylcarnitines in COVID-19 patients. A multicenter, cross-sectional study was carried out. A total of 453 individuals were classified by disease severity. Levels of 11 amino acids, 31 acylcarnitines, and succinylacetone in serum samples were analyzed by electrospray ionization-triple quadrupole tandem mass spectrometry. Different clusters were observed in partial least squares discriminant analysis, with phenylalanine, alanine, citrulline, proline, and succinylacetone providing the major contribution to the variability in each cluster (variable importance in the projection >1.5). In logistic models adjusted by age, sex, type 2 diabetes mellitus, hypertension, and nutritional status, phenylalanine was associated with critical outcomes (odds ratio=5.3 (95% CI 3.16-9.2) in the severe vs. critical model, with an area under the curve of 0.84 (95% CI 0.77-0.90). In conclusion the metabolic imbalance in COVID-19 patients might affect disease progression. This work shows an association of phenylalanine with critical outcomes in COVID-19 patients, highlighting phenylalanine as a potential metabolic biomarker of disease severity.