Acute ischemic stroke (AIS) patients with active COVID-19 infection often have more severe symptoms and worse recovery. COVID-19 infection can cause gut microbiota dysbiosis, which is also a risk factor for poor outcomes in AIS patients. However, the association between gut microbiota and functional outcomes among AIS patients with COVID-19 infection has not been fully clarified yet. In this study, we performed 16S rRNA gene sequencing to characterize the gut microbial community among AIS patients with acute COVID-19 infection, AIS patients with post-acute COVID-19 infection, and AIS patients without COVID-19 infection. We found that AIS patients with acute COVID-19 experienced poorer recovery and significant gut dysbiosis, characterized by higher levels of Enterobacteriaceae and lower levels of Ruminococcaceae and Lachnospiraceae. Furthermore, a shorter time window (less than 28 days) between COVID-19 infection and stroke was identified as a risk factor for poor functional outcomes in AIS patients with COVID-19, and the enrichment of Enterobacteriaceae was indicated as a mediator in the relationship between infection time window and poor stroke outcomes. Our findings highlight the importance of early intervention after COVID-19 infection, especially by regulating the gut microbiota, which plays a role in the prognosis of AIS patients with COVID-19 infection.IMPORTANCEThe gut microbiota plays an important role in the association between respiratory system and cerebrovascular system through the gut-lung axis and gut-brain axis. However, the specific connection between gut bacteria and the functional outcomes of acute ischemic stroke (AIS) patients with COVID-19 is not fully understood yet. In our study, we observed a significant decrease in bacterial diversity and shifts in the abundance of key bacterial families in AIS patients with acute COVID-19 infection. Furthermore, we identified that the time window was a critical influence factor for stroke outcomes, and the enrichment of Enterobacteriaceae acted as a mediator in the relationship between the infection time window and poor stroke outcomes. Our research provides a new perspective on the complex interplay among AIS, COVID-19 infection, and gut microbiota dysbiosis. Moreover, recognizing Enterobacteriaceae as a potential mediator of poor stroke prognosis offers a novel avenue for future exploration and therapeutic interventions.

The ongoing coronavirus disease 2019 (COVID-19) pandemic, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has imposed a heavy burden on medical systems. In addition to the respiratory system, the virus also causes injuries to other organs and systems such as the gastroenteric system, kidneys, and reproductive system. Female reproductive health requires more attention in this context.

We have performed a thorough review of the relevant literature that addresses the impacts of SARS-CoV-2 infection and COVID-19 vaccination on the female reproductive system.

Most evidence shows that SARS-CoV-2 does not infect the female reproductive system. However, the virus may indirectly influence sex hormone concentrations through inflammation associated with cytokine storms and nervous system damage. Menstrual disorders in women infected with SARS-CoV-2 may be caused by down-regulation of angiotensin-converting enzyme 2, abnormal hormone levels, medications, and stress. There is no significant difference in ovarian follicle quality and in vitro fertilization parameters between the pre- and post-COVID-19 vaccination groups. In addition, most symptoms due to side effects of vaccination could recover within a short period of time.

SARS-CoV-2 infection affects female reproductive system function through multiple mechanisms. It is recommended that women of childbearing age be vaccinated with COVID-19 vaccine.

COVID-19 can be presented with various gastrointestinal symptoms. Shortly after the pandemic outbreak, several machine learning algorithms were implemented to assess new diagnostic and therapeutic methods for this disease. The aim of this study is to assess gastrointestinal and liver-related predictive factors for SARS-CoV-2 associated risk of hospitalization.

Data collection was based on a questionnaire from the COVID-19 outpatient test center and from the emergency department at the University Hospital in combination with the data from internal hospital information system and from a mobile application used for telemedicine follow-up of patients. For statistical analysis SARS-CoV-2 negative patients were considered as controls in three different SARS-CoV-2 positive patient groups (divided based on severity of the disease). The data were visualized and analyzed in R version 4.0.5. The Chi-squared or Fisher test was applied to test the null hypothesis of independence between the factors followed, where appropriate, by the multiple comparisons with the Benjamini Hochberg adjustment. The null hypothesis of the equality of the population medians of a continuous variable was tested by the Kruskal Wallis test, followed by the Dunn multiple comparisons test. In order to assess predictive power of the gastrointestinal parameters and other measured variables for predicting an outcome of the patient group the Random Forest machine learning algorithm was trained on the data. The predictive ability was quantified by the ROC curve, constructed from the Out-of-Bag data. Matthews correlation coefficient was used as a one-number summary of the quality of binary classification. The importance of the predictors was measured using the Variable Importance. A 2D representation of the data was obtained by means of Principal Component Analysis for mixed type of data. Findings with the p-value below 0.05 were considered statistically significant.

A total of 710 patients were enrolled in the study. The presence of diarrhea and nausea was significantly higher in the emergency department group than in the COVID-19 outpatient test center. Among liver enzymes only aspartate transaminase (AST) has been significantly elevated in the hospitalized group compared to patients discharged home. Based on the Random Forest algorithm, AST has been identified as the most important predictor followed by age or diabetes mellitus. Diarrhea and bloating have also predictive importance, although much lower than AST.

SARS-CoV-2 positivity is connected with isolated AST elevation and the level is linked with the severity of the disease. Furthermore, using the machine learning Random Forest algorithm, we have identified the elevated AST as the most important predictor for COVID-19 related hospitalizations.

COVID-19 is an infectious disease characterized by multiple respiratory and extrapulmonary manifestations, including gastrointestinal symptoms. Although recent studies have linked gut microbiota to infectious diseases such as influenza, little is known about the role of the gut microbiota in COVID-19 pathophysiology.

To better understand the host-gut microbiota interactions in COVID-19, we characterized the gut microbial community and gut barrier function using metagenomic and metaproteomic approaches in 63 COVID-19 patients and 8 non-infected controls. Both immunohematological parameters and transcriptional profiles were measured to reflect the immune response in COVID-19 patients.

Altered gut microbial composition was observed in COVID-19 patients, which was characterized by decreased commensal species and increased opportunistic pathogenic species. Severe illness was associated with higher abundance of four microbial species (i.e., Burkholderia contaminans, Bacteroides nordii, Bifidobacterium longum, and Blautia sp. CAG 257), six microbial pathways (e.g., glycolysis and fermentation), and 10 virulence genes. These severity-related microbial features were further associated with host immune response. For example, the abundance of Bu. contaminans was associated with higher levels of inflammation biomarkers and lower levels of immune cells. Furthermore, human-origin proteins identified from both blood and fecal samples suggested gut barrier dysfunction in COVID-19 patients. The circulating levels of lipopolysaccharide-binding protein increased in patients with severe illness and were associated with circulating inflammation biomarkers and immune cells. Besides, proteins of disease-related bacteria (e.g., B. longum) were detectable in blood samples from patients.

Our results suggest that the dysbiosis of the gut microbiome and the dysfunction of the gut barrier might play a role in the pathophysiology of COVID-19 by affecting host immune homeostasis.

Since COVID-19 occurrence in late 2019, intense research efforts on an unprecedented scale have focused on the study of named severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) entry mechanisms and clinical presentations. As for other coronaviruses, SARS-CoV-2 presents with extrarespiratory clinical manifestations such as diarrhea, nausea, vomiting, and abdominal pain which highlight that the gastrointestinal (GI) system as another viral target along with the typical presentations of COVID-19 which is characterized primarily by respiratory symptoms. The digestive system is involved in many systemic functions through the gut-brain axis and systemic immunity modulation. Therefore, the GI system plays an important role in the presentation of the disease, pathogenesis, and possibly treatment outcomes. This minireview summarizes recent work to study SARS-CoV-2 infection as it relates to comorbidities, GI symptoms. This will help to strategize the priorities in understanding the impact of the virus on outcomes in various aspects.

Diabetes mellitus (DM) has a high incidence of comorbidities among patients with severe coronavirus disease 2019 (COVID-19). The elevated prevalence of DM in the world population makes it a significant risk factor because diabetic individuals appear to be prone to clinical complications and have increased mortality rates. Here, we review the possible underlying mechanisms involved in DM that led to worse outcomes in COVID-19. The impacts of hyperglycemia side effects, secondary comorbidities, weakened innate and adaptive immunity, chronic inflammation, and poor nutritional status, commonly present in DM, are discussed. The role of the SARS-CoV-2 receptor and its polymorphic variations on higher binding affinity to facilitate viral uptake in people with DM were also considered. Clinical differences between individuals with type 1 DM and type 2 DM affected by COVID-19 and the potential diabetogenic effect of SARS-CoV-2 infection were addressed.

The coronavirus disease 2019 (COVID-19) disproportionately affected African Americans (AA) and Hispanics (HSP).

To analyze the significant effectors of outcome in African American patient population and make special emphasis on gastrointestinal (GI) symptoms, laboratory values and comorbidities.

We retrospectively evaluated the medical records of 386 COVID-19 positive patients admitted at Howard University Hospital between March and May 2020. We assessed the symptoms, including the GI manifestations, comorbidities, and mortality, using logistic regression analysis.

Of these 386 COVID-19 positive patients, 257 (63.7%) were AAs, 102 (25.3%) HSP, and 26 (6.45%) Whites. There were 257 (63.7%) AA, 102 (25.3%) HSP, 26 (6.45%) Whites. The mean age was 55.6 years (SD = 18.5). However, the mean age of HSP was the lowest (43.7 years vs 61.2 for Whites vs 60 for AAs). The mortality rate was highest among the AAs (20.6%) and lowest among HSP (6.9%). Patients with shortness of breath (SOB) (OR2 = 3.64, CI = 1.73-7.65) and elevated AST (OR2 = 8.01, CI = 3.79-16.9) elevated Procalcitonin (OR2 = 8.27, CI = 3.95-17.3), AST (OR2 = 8.01, CI = 3.79-16.9), ferritin (OR2 = 2.69, CI = 1.24-5.82), and Lymphopenia (OR2 = 2.77, CI = 1.41-5.45) had a high mortality rate. Cough and fever were common but unrelated to the outcome. Hypertension and diabetes mellitus were the most common comorbidities. Glucocorticoid treatment was associated with higher mortality (OR2 = 5.40, CI = 2.72-10.7). Diarrhea was prevalent (18.8%), and GI symptoms did not affect the outcome.

African Americans in our study had the highest mortality as they consisted of an older population and comorbidities. Age is the most important factor along with SOB in determining the mortality rate. Overall, elevated liver enzymes, ferritin, procalcitonin and C-reactive protein were associated with poor prognosis. GI symptoms did not affect the outcome. Glucocorticoids should be used judiciously, considering the poor outcomes associated with it. Attention should also be paid to monitor liver function during COVID-19, especially in AA and HSP patients with higher disease severity.

Italy was the first country in Europe to report a SARS-CoV-2 case. Since then, the country has suffered a large number of COVID-19 infections both in adults and children. This disease has been shown to lead to different outcomes in these two groups, which often present varying symptoms and comorbidities.

Therefore, we aimed to evaluate the symptoms, comorbidities and laboratory values in adults and children.

We present the characteristics of 1,324 adults and 563 pediatric COVID-19 Italian patients. The data was retrieved from studies published in Italy and found via PubMed and Google Scholar.

The virus appeared to affect adults more than children and men more than women, and to result in more severe outcomes in patients with abnormal laboratory values and a higher number of comorbidities. Adults are at higher risk for complications and death, and they usually present with fever, respiratory symptoms, cough, fatigue, diarrhea, myalgia, and/or loss of taste, smell, or appetite. Children usually have a milder disease progression and usually present with fever, cough, rhinorrhea, pharyngitis, sore throat, pneumonia, GI symptoms (diarrhea, vomiting, abdominal pain), fatigue, and dyspnea.

Our findings support early reports that showed that SARS-CoV-2 is associated with more common asymptomatic cases and milder clinical outcome in children than in adults. Acute respiratory distress syndrome and Multisystem inflammatory syndrome in children (systemic vasculitis) are the most severe disease progressions for adults and children, respectively.

COVID-19 is an infectious disease caused by the newly discovered SARS-CoV-2 virus. This virus causes a respiratory tract infection, symptoms include dry cough, fever, tiredness and in more severe cases, breathing difficulty. SARS-CoV-2 is an extremely contagious virus that is spreading rapidly all over the world and the scientific community is working tirelessly to find an effective treatment. This paper aims to determine the origin of this virus by comparing its nucleic acid sequence with all members of the coronaviridae family. This study uses a new approach based on the combination of three powerful techniques which are: Ngrams (For text categorization), Principal Component Analysis (For dimensionality reduction) and Random Forest algorithm (For supervised classification). The experimental results have shown that a large set of SARS-CoV-2 genomes, collected from different locations around the world, present significant similarities to those found in pangolins. This finding confirms some previous results obtained by other methods, which also suggest that pangolins should be considered as possible hosts in the emergence of the new coronavirus.