Abnormalities in liver biochemistry are common in COVID-19 patients. Hepatic vein Doppler waveform, typically triphasic, may become biphasic or monophasic in cirrhosis, correlating with liver dysfunction, fibrosis, inflammation, and portal hypertension. This study investigates liver ultrasound (US) features in COVID-19 patients, correlating hepatic vein Doppler waveform and portal vein velocity (PVV) with inflammatory indexes and clinical outcomes.

Fifty-seven patients with SARS-CoV-2 infection participated in a crosssectional study. Bedside upper abdomen US evaluations, including B-mode and Doppler, were conducted using a convex probe. Hepatic vein Doppler waveforms were classified as triphasic, biphasic, or monophasic, and the hepatic vein waveform index (HVWI) was calculated. PVV was measured over three cardiac cycles. Tracings were blindly analyzed by three operators to ensure consistency.

Low HVWI and high PVV correlated with elevated LDH, ALT, D-dimer, and ferritin (p < 0.05). HVWI showed significant negative correlations with ferritin, D-dimer, and ALT (p < 0.05). D-Dimer and ferritin were higher in patients with biphasic/monophasic waveforms (p < 0.05). High PVV and larger spleen diameters predicted worse respiratory outcomes, including CPAP and tracheal intubation (p < 0.05). Optimal cut-off values for PVV (21.7 cm/s) and spleen diameter (9.84 cm) maximized sensitivity and specificity for predicting these outcomes. FIB-4 scores did not correlate with respiratory outcomes or hepatic hemodynamics (p > 0.05). Hemodynamic alterations were not significantly influenced by the presence of SLD (Steatotic Liver Disease).

COVID-19 patients exhibit altered intrahepatic hemodynamics, with hepatic vein waveform abnormalities potentially reflecting liver inflammation and fibrosis. PVV and spleen diameter may serve as non-invasive predictors of respiratory outcomes.

A major challenge with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of coronavirus disease 2019 (COVID-19), has been assessing the intensity, dynamics, and determinants of the antibody responses after infection and/or vaccination. Therefore, we aimed to characterize the longitudinal dynamics of the antibody responses among naturally infected individuals and individuals who achieved hybrid immunity in a large Canadian cohort. We demonstrate that anti-Spike IgGs and neutralizing antibody dynamics vary greatly among individuals with COVID-19, in peak antibody levels, rate of waning, and longevity of the antibody response. Additionally, we found an association between robust antibody responses and individuals with severe COVID-19 clinical symptoms during the first-month post-symptom onset. For individuals who achieved hybrid immunity, a robust increase in anti-S1 IgGs and neutralizing antibodies followed the first vaccination dose; however, there was a minimal increase in the anti-S1 IgGs and neutralizing antibody titers after administration of the second dose of the vaccine. Furthermore, neutralizing antibodies elicited by the wild-type virus alone were largely ineffective against emerging variants of concern in our natural infection-only cohort, in contrast to a much broader and more robust neutralization profile observed in individuals who achieved hybrid immunity. Our findings emphasize the need for global SARS-CoV-2 vaccination efforts to further sustain protective immune responses required to minimize viral spread and disease severity in the population. As SARS-CoV-2 variants continue to emerge, understanding the interplay between previous infections, vaccine durability, and virus evolution will be critical for guiding ongoing vaccination strategies.

A major challenge with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of coronavirus disease 2019 (COVID-19), has been assessing the intensity, dynamics, and determinants of the antibody response after infection and/or vaccination. Our paper addresses this in a large Canadian cohort with antibody responses that were generated by natural infection as well as vaccine in some persons studied.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic has highlighted the potential exacerbation of gastrointestinal symptoms in patients with disorders of gut-brain interaction (DGBIs). However, the distinct symptom trajectories and psychological burden in patients with post-COVID-19 DGBIs compared with patients with pre-existing irritable bowel syndrome (IBS)/functional dyspepsia (FD) and non-DGBI controls remain poorly understood.

To examine the long-term gastrointestinal symptom progression and psychological comorbidities in patients with post-COVID-19 DGBI, patients with pre-existing IBS/FD and non-DGBI controls.

This post hoc analysis of a prospective multicenter cohort study reviewed patient charts for demographic data and medical history. Participants completed the Gastrointestinal Symptom Rating Scale at four time points: baseline, 1, 6, and 12 months, and the Hospital Anxiety and Depression Scale at 6 and 12 months. The cohort was divided into three groups: (1) post-COVID-19 DGBIs (2) non-DGBI, and (3) pre-existing IBS/FD, with the post-COVID-19 DGBIs group compared to the latter two control groups.

Among 599 eligible patients, 27 (4.5%) were identified as post-COVID-19 DGBI. This group experienced worsening abdominal pain, hunger pain, heartburn, and acid regurgitation, unlike symptom improvement or stability in non-DGBI controls (p < 0.001 for all symptoms, except hunger pain, p = 0.001). While patients with pre-existing IBS/FD improved in most gastrointestinal symptoms but worsened in constipation and incomplete evacuation, patients with post-COVID-19 DGBI exhibited consistent symptom deterioration across multiple gastrointestinal domains. Anxiety and depression remained unchanged in patients with post-COVID-19 DGBI, contrasting with significant reductions in controls (non-DGBI: p = 0.003 and p = 0.057; pre-existing IBS/FD: p = 0.019 and p = 0.007, respectively).

COVID-19 infection is associated with the development of newly diagnosed DGBIs and distinct symptom trajectories when compared with patients with pre-existing IBS/FD. Patients with post-COVID-19 DGBI experience progressive gastrointestinal symptom deterioration and persistent psychological distress, underscoring the need for tailored management strategies for this unique subgroup.

Comorbidities, including obesity and type 2 diabetes mellitus (T2DM), are associated with increased disease severity and mortality following SARS-CoV-2 infection. Here, we investigated virus-host interactions under the effects of these comorbidities in diet-induced obesity (DIO) and leptin receptor-deficient (T2DM) mice following infection with SARS-CoV-2. DIO mice, as well as their lean counterparts, showed limited susceptibility to SARS-CoV-2 infection. In contrast, T2DM mice showed exacerbated pulmonary SARS-CoV-2 replication and delayed viral clearance associated with down-regulation of innate and adaptative immune gene signatures, ineffective type I interferon response, and delayed SARS-CoV-2-specific cell-mediated immune responses. While T2DM mice showed higher and prolonged SARS-CoV-2-specific immunoglobulin isotype responses compared to their lean counterparts, neutralizing antibody levels were equivalent. By silencing the leptin receptor in vitro using a human alveolar epithelial cell line, we observed an increase in SARS-CoV-2 replication and type I interferons. Altogether, our data provides for the first time evidence that disruption of leptin receptor signaling leading to obesity and T2DM induces altered type I interferon and cell-mediated responses against SARS-CoV-2, mediating increased viral replication and delayed clearance. These data shed light on the alteration of the innate immune pathway in the lung using in-depth transcriptomic analysis and on adaptive immune responses to SARS-CoV-2 under T2DM conditions. Finally, this study provides further insight into this risk factor aggravating SARS-CoV-2 infection and understanding the underlying cellular mechanisms that could help identify potential intervention points for this at-risk population.

The COVID-19 pandemic highlighted the importance of considering social determinants of health in health outcomes. Within this spectrum of determinants, social networks garnered attention as the pandemic highlighted the negative effects of social isolation in the context of social distancing measures. Postpandemic, examining the role social networks play in COVID-19 recovery can help guide patient care and shape future health policies. This study aimed to investigate the relationship between social networks and self-rated health change, as well as physical function, in patients recovering from COVID-19 pneumonia.

This was a retrospective cohort study utilizing clinical data from 2 New York City hospitals and a 9-month follow-up survey of COVID-19 pneumonia survivors. We evaluated a composite Social Network Score from the 6-item Lubben Social Network Scale and its association with 2 outcomes: 1) self-rated health change and 2) physical function.

A total of 208 patients were included in this study. A 1-point increase in the Social Network Score was associated with greater odds of both same or improved self-rated health change (odds ratio [OR] 1.07, 95% CI 1.02-1.12, P = .01), as well as unimpaired physical function (OR 1.08, 95% CI 1.03-1.14, P < .01).

This study emphasized the importance of social networks as a social determinant of health among patients recovering from COVID-19 hospitalization. Targeted interventions to enhance social networks may benefit not only COVID-19 patients but also individuals recovering from other acute illnesses.

The existing literature has described the common symptoms and long-term effects of coronavirus disease (COVID-19). However, there is a lack of detailed information on how different degrees of disease severity affect survivors differently. This study aims to fill that gap by evaluating the symptoms, physical activity, and functionality of COVID-19 survivors across a spectrum of severity levels, comparing them with those of healthy individuals.

An observational study was carried out following the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) criteria and checklist. Participants were divided into 5 groups based on COVID-19 severity according to the World Health Organization classification: healthy (COVID-19-negative), mild (symptomatic without pneumonia or dyspnoea), moderate (pneumonia and dyspnoea without hospitalisation), severe (severe pneumonia requiring hospitalisation), and critical (severe pneumonia with admission to the intensive care unit). Descriptive variables, symptoms (Fatigue Borg Scale, Fatigue Impact Scale, Fatigue Severity Scale, Dyspnoea Borg Scale, Visual Analogue Scale, Hospital Anxiety and Depression Scale, and European Quality of Life-5 Dimensions), physical activity (the International Physical Activity Questionnaire) and functionality (Patient-Specific Functional Scale, Short Physical Performance Battery, Arm Curl test, and 2 min step test) were measured.

A total of 304 participants were included: healthy (n = 42), mild (n = 143), moderate (n = 49), severe (n = 52), and critical (n = 18) COVID-19 patients. The impact of COVID-19 on surviving patients varies significantly with the severity of the disease. The results show that the hospitalisation time, age, and comorbidities of the patients are greater in those with a greater severity of the disease. Patients with more severe COVID-19 also experience greater frailty, dysphagia, fatigue, dyspnoea, and pain. Additionally, those with severe cases have poorer overall health, reduced physical activity, and diminished functionality. No evidence of post-COVID-19 anxiety or depression is found in the sample, even considering the timeframe between the negative test and the assessment.

Patients with higher COVID-19 severity (severe or critical) experience more symptoms than those with lower COVID-19 severity (mild or moderate). Additionally, those with severe cases have poorer overall health, reduced physical activity and diminished functionality. Register: Clinicaltrials.gov: NCT05731817.

During the SARS-CoV-2 pandemic, a significant number of critical patients required ventilatory assistance in health institutions. In this context, Ventilator-Associated Pneumonia (VAP) was the most prevalent nosocomial infection among critically ill patients. We aimed to analyze the occurrence of VAP in critically ill patients with SARS-CoV-2 and the risk factors associated with the outcome.

This is a multicenter, retrospective cohort study which included patients ≥18 years old, diagnosed with COVID-19, admitted to intensive care units (ICU) and who received invasive mechanical ventilation (MV) for >2 consecutive days. The associations between the variables were initially tested, and those that showed potential associations (p<0.05) were included in the multivariate logistic regression model.

One third of patients had an episode of VAP, with an incidence density of 34.97 cases per 1000 MV days. In addition, 42.37% (50) of the microorganisms causing VAP were multidrug-resistant, predominantly gram-negative bacteria (61.32%). More than 50% of participants developed healthcare-associated infections and 243 (73.64%) died. The factors associated with greater chances of VAP were: prone position (OR= 3.77), BMI 25-29.9 kg/m2 (OR= 4.76), pressure injury (OR= 4.41), length of stay in the ICU (OR= 1.06), positive tracheal aspirate before VAP (OR= 5.41) and dyspnea (OR= 3.80).

Patients with COVID-19 are at high risk of VAP, which leads to an increased risk of death (OR = 2.18). Multiple factors increase the chances of VAP in this population, namely: work overload in health institutions, prone position, prolonged ICU time, infusion of multiple drugs, invasive devices, and in particular, immobility in bed.

Early identification of patients at risk for acute respiratory failure (ARF) could help clinicians devise preventive strategies. Analyzing biosignals with artificial intelligence (AI) can uncover hidden information and variability within time series. We aimed to develop and validate AI models to predict ARF within 72 h after emergency department admission, primarily using high-resolution biosignals collected within 4 h of arrival.

Our AI model, built on convolutional recurrent neural networks, combines biosignal feature extraction and sequence modeling. The model was developed and internally validated with data from 5284 admissions [1085 (20.5%) positive for ARF], and externally validated using data from 144 admissions [7 (4.9%) positive for ARF] from another institution. We defined ARF as the application of advanced respiratory support devices.

Our AI model performed well in predicting ARF, achieving area under the receiver operating characteristic curve (AUROC) of 0.840 and 0.743 in internal and external validations, respectively. It outperformed the Modified Early Warning Score (MEWS) and XGBoost models built only with clinical variables. High predictive ability for mortality was observed, with AUROC up to 0.809. A 10% increase in AI prediction scores was associated with 1.44-fold and 1.42-fold increases in ARF risk and mortality risk, respectively, even after adjusting for MEWS and demographic variables.

Our AI model demonstrates high predictive accuracy and significant associations with clinical outcomes. Our AI model has the potential to promptly aid in triage decisions. Our study shows that using AI to analyze biosignals advances disease detection and prediction.

DNMT3A and TET2 are epigenetic regulator genes commonly mutated in age-related clonal hematopoiesis (CH). Despite having opposed epigenetic functions, these mutations are associated with increased all-cause mortality and a low risk for progression to hematologic neoplasms. Although individual impacts on the epigenome have been described using different model systems, the phenotypic complexity in humans remains to be elucidated. Here, we make use of a natural inflammatory response occurring during coronavirus disease 2019 (COVID-19), to understand the association of these mutations with inflammatory morbidity (acute respiratory distress syndrome [ARDS]) and mortality. We demonstrate the age-independent, negative impact of DNMT3A mutant (DNMT3Amt) CH on COVID-19-related ARDS and mortality. Using single-cell proteogenomics we show that DNMT3A mutations involve myeloid and lymphoid lineage cells. Using single-cell multiomics sequencing, we identify cell-specific gene expression changes associated with DNMT3A mutations, along with significant epigenomic deregulation affecting enhancer accessibility, resulting in overexpression of interleukin-32 (IL-32), a proinflammatory cytokine that can result in inflammasome activation in monocytes and macrophages. Finally, we show with single-cell resolution that the loss of function of DNMT3A is directly associated with increased chromatin accessibility in mutant cells. Hence, we demonstrate the negative prognostic impact of DNMT3Amt CH on COVID-19-related ARDS and mortality. DNMT3Amt CH in the context of COVID-19, was associated with inflammatory transcriptional priming, resulting in overexpression of IL32. This overexpression was secondary to increased chromatic accessibility, specific to DNMT3Amt CH cells. DNMT3Amt CH can thus serve as a potential biomarker for adverse outcomes in COVID-19.

Solid organ transplant (SOT) recipients are at risk of severe COVID-19. Vaccination is an important preventive measure but may have side effects, including decreased leukocyte counts. We aimed to describe the prevalence and relative incidence of decreased leukocyte counts and changes in leukocyte counts before and after SARS-CoV-2 mRNA vaccination and SARS-CoV-2 infection in SOT recipients.

Changes in leukocyte counts from before to after each vaccine dose were investigated using linear mixed models. We determined the prevalence of decreased leukocyte counts before and after each vaccine dose and before and after SARS-CoV-2 infection. Self-controlled case series analysis was used to investigate whether the period after either vaccination or infection was associated with risk of decreased leukocyte count.

We included 228 adult kidney, lung, and liver transplant recipients. Prior to the first vaccine dose, the mean leukocyte count was 7.3 × 109 cells/L (95% CI 6.9-7.6). Both the leukocyte counts, and the prevalence of decreased leukocyte counts remained unchanged from before to after vaccination regardless of the number of vaccine doses provided. There was no association between vaccination and decreased leukocyte counts (incidence rate ratio (IRR): 0.6; 95% CI: 0.2-2.1; p = 0.461). In contrast, SARS-CoV-2 infection was associated with increased risk of a decreased leukocyte count (IRR: 7.1; 95% CI: 2.8-18.1; p < 0.001).

SARS-CoV-2 mRNA vaccination was not associated with risk of decreased leukocyte count and did not affect the prevalence of decreased leukocyte counts in SOT recipients. In contrast, SARS-CoV-2 infection was associated with a higher risk of a decreased leukocyte count.

Neutrophils, particularly low-density neutrophils (LDNs), are believed to contribute to acute COVID-19 severity. Here, we showed that neutrophilia can be detected acutely and even months after SARS-CoV-2 infection in patients and mice, while neutrophil depletion reduced disease severity in mice. A key factor in neutrophilia and severe disease in infected mice was traced to the chemokine CXCL12 secreted by bone marrow cells and unexpectedly, endothelial cells. CXCL12 levels were negatively correlated with LDN numbers in longitudinal analyses of patient blood samples. CXCL12 blockade in SARS-CoV-2-infected mice increased blood/lung neutrophil numbers, thereby accelerating disease progression without changing lung virus titers. The exaggerated mortality caused by CXCL12 blockade could be reversed by neutrophil depletion. In addition, blocking interactions between SARS-CoV-2 and angiotensin-converting enzyme 2 (ACE2) reduced CXCL12 levels, suggesting a signal transduction from virus-mediated ACE2 ligation to increased CXCL12 secretion. Collectively, these results demonstrate a previously unappreciated role of CXCL12 in diminishing neutrophilia, including low-density neutrophilia, and its deleterious effects in SARS-CoV-2 infections. The results also support the involvement of SARS-CoV-2-endothelial cell interactions in viral pathogenesis.

Several nutrients are crucial in enhancing the immune system and preserving the structural integrity of bodily tissue barriers. Vitamin D (VD) and zinc (Zn) have received considerable interest due to their immunomodulatory properties and ability to enhance the body's immune defenses. Due to their antiviral, anti-inflammatory, antioxidative, and immunomodulatory properties, the two nutritional powerhouses VD and Zn are crucial for innate and adaptive immunity. As observed with COVID-19, deficiencies in these micronutrients impair immune responses, increasing susceptibility to viral infections and severe disease. Ensuring an adequate intake of VD and Zn emerges as a promising strategy for fortifying the immune system. Ongoing clinical trials are actively investigating their potential therapeutic advantages. Beyond the immediate context of the pandemic, these micronutrients offer valuable tools for enhancing immunity and overall well-being, especially in the face of future viral threats. This analysis emphasizes the enduring significance of VD and Zn as both treatment and preventive measures against potential viral challenges beyond the current health crisis. The overview delves into the immunomodulatory potential of VD and Zn in combating viral infections, with particular attention to their effects on animals. It provides a comprehensive summary of current research findings regarding their individual and synergistic impacts on immune function, underlining their potential in treating and preventing viral infections. Overall, this overview underscores the need for further research to understand how VD and Zn can modulate the immune response in combatting viral diseases in animals.

The complex link between COVID-19 and immunometabolic diseases demonstrates the important interaction between metabolic dysfunction and immunological response during viral infections. Severe COVID-19, defined by a hyperinflammatory state, is greatly impacted by underlying chronic illnesses aggravating the cytokine storm caused by increased levels of Pro-inflammatory cytokines. Metabolic reprogramming, including increased glycolysis and altered mitochondrial function, promotes viral replication and stimulates inflammatory cytokine production, contributing to illness severity. Mitochondrial metabolism abnormalities, strongly linked to various systemic illnesses, worsen metabolic dysfunction during and after the pandemic, increasing cardiovascular consequences. Long COVID-19, defined by chronic inflammation and immune dysregulation, poses continuous problems, highlighting the need for comprehensive therapy solutions that address both immunological and metabolic aspects. Understanding these relationships shows promise for effectively managing COVID-19 and its long-term repercussions, which is the focus of this review paper.

Background: Understanding the interactions between age and comorbidities is crucial for assessing COVID-19 mortality, particularly in patients with cardiac and pulmonary conditions. This study investigates the relationship between comorbidities and mortality outcomes in a cohort of hospitalized COVID-19 patients, emphasizing the interplay of age, cardiac, and pulmonary conditions. Methods: We analyzed a cohort of 3005 patients hospitalized with COVID-19 between 2020 and 2022. Key variables included age, comorbidities (diabetes, cardiac, pulmonary, and neoplasms), and clinical outcomes. Chi-square tests and logistic regression models were used to assess the association between comorbidities and mortality. Stratified analyses by age, diabetes, and pulmonary conditions were conducted to explore interaction effects. Additionally, interaction terms were included in multivariable logistic regression models to evaluate the combined impact of age, comorbidities, and mortality. Results: Cardiac conditions such as hypertension, ischemic cardiopathy, and myocardial infarction showed significant protective effects against mortality in younger patients and in those without pulmonary conditions (p < 0.001). However, these protective effects were diminished in older patients and those with pulmonary comorbidities. Age was found to be a significant modifier of the relationship between cardiac conditions and mortality, with a stronger protective effect observed in patients under the median age (p < 0.001). Pulmonary comorbidities significantly increased the risk of mortality, particularly when co-occurring with cardiac conditions (p < 0.001). Diabetes did not significantly modify the relationship between cardiac conditions and mortality. Conclusions: The findings highlight the complex interactions between age, cardiac conditions, and pulmonary conditions in predicting COVID-19 mortality. Younger patients with cardiac comorbidities show a protective effect against mortality, while pulmonary conditions increase mortality risk, especially in older patients. These insights suggest that individualized risk assessments incorporating age and comorbidities are essential for managing COVID-19 outcomes.

Background The development of vaccines against SARS-CoV-2 has proved to be a highly successful strategy. In this work, the aim is to study the effects of the SARS-CoV-2 vaccine on the production of inflammatory markers and how this affect morbidity and mortality. Electronic medical record (EMR) data from 210 patients diagnosed with COVID-19 from November 2020 to June 2021 were collected. The admitted patients were divided into three groups, the one-dose vaccinated, two-dose vaccinated, and the non-vaccinated. All patients were moderate or severe in disease level as defined by the WHO classification. The results show that CRP was 101 ± 5.3, 97 ± 10.8, and 145 ± 17.3 (p < 0.05), fibrinogen 529 ± 16.3, 397 ± 33.8, and 610 ± 15 (p < 0.05), D-dimer 1244 ± 89, 1279 ± 297, and 1615 ± 224 (p < 0.05), ferritin was 1170 ± 122, 999 ± 202, and 1663 ± 409 (p < 0.05), IL-6 was 196 ± 12, 96 ± 5, and 580 ± 402 (NS), for the non-vaccinated, one-dose vaccinated, and two-dose vaccinated groups, respectively. The high level of CRP up to 150-200 mg/dL was more common among the surviving vaccinated patients. Oxygen supplementation, mechanical ventilation, and mortality were higher in the non-vaccinated group. Blood urea nitrogen (BUN) level was higher in the vaccinated patients, 25 ± 0.14 vs. 33 ± 6.15, respectively (p < 0.05). Inflammation markers were significantly higher in the vaccinated groups compared to non-vaccinated groups. On the other hand, extremely high levels of CRP (>200 mg/dL) were correlated with high mortality incidence.

Pregnant women with COVID-19 are at elevated risk for severe outcomes, but clinical data on management of these patients are limited. Monoclonal antibodies, such as casirivimab plus imdevimab (CAS+IMD), have proven effective in treating non-pregnant adults with COVID-19, prompting further evaluation in pregnant women.

A phase 3 portion of an adaptive, multicentre, randomised, double-blind, placebo-controlled trial evaluated the safety, clinical outcomes, pharmacokinetics and immunogenicity of CAS+IMD (1200 mg or 2400 mg) in the treatment of pregnant outpatients with COVID-19 (NCT04425629). Participants were enrolled between December 2020 and November 2021, prior to the emergence of Omicron-lineage variants against which CAS+IMD is not active. Safety was evaluated in randomised participants who received study drug (n=80); clinical outcomes were evaluated in all randomised participants (n=82). Only two pregnant participants received placebo, limiting conclusions regarding treatment effect. Infants born to pregnant participants were followed for developmental outcomes ≤1 year of age.

In pregnant participants, CAS+IMD was well tolerated, with no grade ≥2 hypersensitivity or infusion-related reactions reported. There were no participant deaths, and only one COVID-19-related medically attended visit. Although two pregnancies (3%) reported issues in the fetus/neonate, they were confounded by maternal history or considered to be due to an alternate aetiology. No adverse developmental outcomes in infants ≤1 year of age were considered related to in utero exposure to the study drug. CAS+IMD 1200 mg and 2400 mg rapidly and similarly reduced viral loads, with a dose-proportional increase in concentrations of CAS+IMD in serum. Pharmacokinetics were consistent with that reported in the general population. Immunogenicity incidence was low.

CAS+IMD treatment of pregnant outpatients with COVID-19 showed similar safety, clinical outcomes and pharmacokinetic profiles to that observed in non-pregnant adults. There was no evidence of an impact on developmental outcomes in infants ≤1 year of age.

NCT04425629.

The risk of cardiovascular complications due to SARS-CoV-2 are significantly increased within the first 6 months of the infection. Patients with COVID-19 have an increased risk of death, and there is evidence that many may experience a wide range of post-acute cardiovascular complications. Our work aims to provide an update on current clinical aspects of diagnosis and treatment of cardiovascular manifestations during acute and long-term COVID-19.

SARS-CoV-2 has been shown to be associated with increased incidence of cardiovascular complications such as myocardial injury, heart failure, and dysrhythmias, as well as coagulation abnormalities not only during the acute phase but also beyond the first 30 days of the infection, associated with high mortality and poor outcomes. Cardiovascular complications during long-COVID-19 were found regardless of comorbidities such as age, hypertension, and diabetes; nevertheless, these populations remain at high risk for the worst outcomes during post-acute COVID-19. Emphasis should be given to the management of these patients. Treatment with low-dose oral propranolol, a beta blocker, for heart rate management may be considered, since it was found to significantly attenuate tachycardia and improve symptoms in postural tachycardia syndrome, while for patients on ACE inhibitors or angiotensin-receptor blockers (ARBs), under no circumstances should these medications be withdrawn. In addition, in patients at high risk after hospitalization due to COVID-19, thromboprophylaxis with rivaroxaban 10 mg/day for 35 days improved clinical outcomes compared with no extended thromboprophylaxis. In this work we provide a comprehensive review on acute and post-acute COVID-19 cardiovascular complications, symptomatology, and pathophysiology mechanisms. We also discuss therapeutic strategies for these patients during acute and long-term care and highlight populations at risk. Our findings suggest that older patients with risk factors such as hypertension, diabetes, and medical history of vascular disease have worse outcomes during acute SARS-CoV-2 infection and are more likely to develop cardiovascular complications during long-COVID-19.

Alpha-1 receptor antagonists may interfere with IL-6 signaling and could therefore be a potential treatment for COVID-19. However, the effectiveness of these drugs in mitigating the risk of clinical deterioration among non-hospitalized patients with COVID-19 is unknown.

The aim of this study is to examine the association between alpha-1 antagonist exposure and the 30-day risk of a hospital encounter or death in nonhospitalized patients with COVID-19.

We conducted a population-based cohort study of Ontario residents aged 35 years and older who were eligible for public drug coverage and who had a positive test for SARS-CoV-2 between January 1, 2020, and March 1, 2021. We matched each individual receiving an alpha-1 antagonist at the time of their positive test with two non-exposed individuals using propensity scores. Our outcome was a composite of a hospital admission, emergency department visit, or death, 1 to 30 days following the positive test.

We matched 3289 alpha-1 antagonist exposed patients to 6189 unexposed patients. Overall, there was no difference in the 30-day risk of the primary outcome among patients exposed to alpha-1 antagonists at the time of their diagnosis relative to unexposed individuals (28.8% vs. 28.0%; OR 1.00, 95% CI 0.91 to 1.11). In a secondary analysis, individuals exposed to alpha-1 antagonists had a lower risk of death in the 30 days following a COVID diagnosis (OR 0.79; 95% CI 0.66 to 0.93).

Alpha-1 antagonists did not mitigate the 30-day risk of clinical deterioration in non-hospitalized patients with COVID-19. Our findings do not support the general repurposing of alpha-1 antagonists as a treatment for such patients, although there may be subgroups of patients in whom further research is warranted.

TMEM16 proteins, which function as Ca2+‑activated Cl‑ channels are involved in regulating a wide variety of cellular pathways and functions. The modulators of Cl‑ channels can be used for the molecule‑based treatment of respiratory diseases, cystic fibrosis, tumors, cancer, osteoporosis and coronavirus disease 2019. The TMEM16 proteins link Ca2+ signaling, cellular electrical activity and lipid transport. Thus, deciphering these complex regulatory mechanisms may enable a more comprehensive understanding of the physiological functions of the TMEM16 proteins and assist in ascertaining the applicability of these proteins as potential pharmacological targets for the treatment of a range of diseases. The present review examined the structures, functions and characteristics of the different types of TMEM16 proteins, their association with the pathogenesis of various diseases and the applicability of TMEM16 modulator‑based treatment methods.

To describe the predictors of mortality in hospitalized patients with severe acute respiratory syndrome (SARS) due to COVID-19 presenting with silent hypoxemia.

Retrospective cohort study of hospitalized patients with SARS due to COVID-19 and silent hypoxemia at admission, in Brazil, from January to June 2021. The primary outcome of interest was in-hospital death. Multivariable logistic regression analysis was performed.

Of 46,102 patients, the mean age was 59 ± 16 years, and 41.6% were female. During hospitalization, 13,149 patients died. Compared to survivors, non-survivors were older (mean age, 66 vs. 56 years; P < 0.001), less frequently female (43.6% vs. 40.9%; P < 0.001), and more likely to have comorbidities (74.3% vs. 56.8%; P < 0.001). Non-survivors had higher needs for invasive mechanical ventilation (42.4% vs. 6.6%; P < 0.001) and intensive care unit admission (56.9% vs. 20%; P < 0.001) compared to survivors. In the multivariable regression analysis, advanced age (OR 1.04; 95%CI 1.037-1.04), presence of comorbidities (OR 1.54; 95%CI 1.47-1.62), cough (OR 0.74; 95%CI 0.71-0.79), respiratory distress (OR 1.32; 95%CI 1.26-1.38), and need for non-invasive respiratory support (OR 0.37; 95%CI 0.35-0.40) remained independently associated with death.

Advanced age, presence of comorbidities, and respiratory distress were independent risk factors for mortality, while cough and requirement for non-invasive respiratory support were independent protective factors against mortality in hospitalized patients due to SARS due to COVID-19 with silent hypoxemia at presentation.

Co-infection with diverse bacteria is commonly seen in patients infected with the novel coronavirus, SARS-CoV-2. This type of co-infection significantly impacts the occurrence and development of novel coronavirus infection. Bacterial co-pathogens are typically identified in the respiratory system and blood culture, which complicates the diagnosis, treatment, and prognosis of COVID-19, and even exacerbates the severity of disease symptoms and increases mortality rates. However, the status and impact of bacterial co-infections during the COVID-19 pandemic have not been properly studied. Recently, the amount of literature on the co-infection of SARS-CoV-2 and bacteria has gradually increased, enabling a comprehensive discussion on this type of co-infection. In this study, we focus on bacterial infections in the respiratory system and blood of patients with COVID-19 because these infection types significantly affect the severity and mortality of COVID-19. Furthermore, the progression of COVID-19 has markedly elevated the antimicrobial resistance among specific bacteria, such as Klebsiella pneumoniae, in clinical settings including intensive care units (ICUs). Grasping these resistance patterns is pivotal for the optimal utilization and stewardship of antibiotics, including fluoroquinolones. Our study offers insights into these aspects and serves as a fundamental basis for devising effective therapeutic strategies. We primarily sourced our articles from PubMed, ScienceDirect, Scopus, and Google Scholar. We queried these databases using specific search terms related to COVID-19 and its co-infections with bacteria or fungi, and selectively chose relevant articles for inclusion in our review.

SGLT-2i are increasingly recognized for their benefits in patients with cardiometabolic risk factors. Additionally, emerging evidence suggests potential applications in acute illnesses, including COVID-19. This systematic review aims to evaluate the effects of SGLT-2i in patients facing acute illness, particularly focusing on SARS-CoV-2 infection.

Following PRISMA guidelines, a systematic search of PubMed, Scopus, medRxiv, Research Square, and Google Scholar identified 22 studies meeting inclusion criteria, including randomized controlled trials and observational studies. Data extraction and quality assessment were conducted independently.

Out of the 22 studies included in the review, six reported reduced mortality in DM-2 patients taking SGLT-2i, while two found a decreased risk of hospitalization. Moreover, one study demonstrated a lower in-hospital mortality rate in DM-2 patients under combined therapy of metformin plus SGLT-2i. However, three studies showed a neutral effect on the risk of hospitalization. No increased risk of developing COVID-19 was associated with SGLT-2i use in DM-2 patients. Prior use of SGLT-2i was not associated with ICU admission and need for MV. The risk of acute kidney injury showed variability, with inconsistent evidence regarding diabetic ketoacidosis.

Our systematic review reveals mixed findings on the efficacy of SGLT-2i use in COVID-19 patients with cardiometabolic risk factors. While some studies suggest potential benefits in reducing mortality and hospitalizations, others report inconclusive results. Further research is needed to clarify optimal usage and mitigate associated risks, emphasizing caution in clinical interpretation.

Introduction Chronic hepatitis C (CHC) remains a significant public health concern due to both hepatic and extrahepatic manifestations associated with substantial morbidity and mortality. The emergence of SARS-CoV-2 has raised concerns about the outcomes of COVID-19 in CHC patients. Method We conducted a retrospective analysis of patients with CHC and SARS-CoV-2 infection admitted to a tertiary care hospital between 2020 and 2023. We performed a global analysis of the entire batch of patients and, later, we evaluated the patients according to the severity of the SARS-CoV-2 infection Results The cohort included 89 patients (63 females, 26 males) with a median age of 65 years. Most patients were hospitalized in 2021. Common clinical manifestations included fever, cough, digestive symptoms, and headache. The most frequent comorbidities were renal disease, thyroid disorders, and cancer. Univariate logistic regression analysis identified older age, hospitalization in 2021, and respiratory failure as risk factors for severe COVID-19. Elevated lactate dehydrogenase levels were also associated with an increased risk of severe COVID-19. Regarding CHC, detectable hepatitis C virus viremia was associated with more severe liver disease (p<0.01). Conclusion Patients with CHC and SARS-CoV-2 infection have a substantial risk of severe outcomes. Early identification and management of these patients are crucial to improve their prognosis.

Numerous studies have stated that comorbidities are risk factors for coronavirus disease 2019 (COVID-19) mortality, but few have considered the severity or stage of these comorbidities. The aim of this study was to determine the association between the severity of comorbidity, age, and number of COVID-19 vaccinations with COVID-19 mortality. This case-control study was conducted from July 2021 until December 2022 at the Dr. Soetomo General Academic Hospital, Surabaya, Indonesia. The patients were divided into non-survived patients (case group) and survived patients (control group). The inclusion criteria for cases were adult patients hospitalized with confirmed COVID-19, based on reverse transcriptase-polymerase chain reaction (RT-PCR) testing of nasopharyngeal swabs. Using total sampling, 1,046 confirmed COVID-19 patients, which consisted of 450 (43%) non-survived patients and 596 (57%) survived patients, were included. The most common comorbidity was diabetes mellitus (DM) (82.7%), chronic kidney disease (CKD) (43%), hypertension (25.7%), and obesity (23.6%). Our multivariate analysis indicated that older age (aOR: 1.03; 95%CI: 1.02-1.04, p<0.001), male sex (aOR: 1.29; 95%CI: 1.11- 2.00, p=0.007), severe COVID-19 at first admission (aOR: 3.13; 95%CI: 2.08-4.73, p<0.001), having pneumonia (aOR: 1.99; 95%CI: 1.21-3.33, p=0.005), poorly controlled DM with HbA1c≥9% (aOR: 2.90; 95%CI: 1.72-4.89, p<0.001), severe obesity with body mass index (BMI)≥30 (OR: 2.90; 95%CI: 1.72-4.89, p<0.001), hypertension stage 2 (aOR: 1.99; 95%CI: 1.12-3.53, p=0.019) or stage 3 (aOR: 6.59; 95%CI: 2.39-18.17, p<0.001), CKD stage 3 (aOR: 2.50; 95%CI: 1.36-4.59, p=0.003), stage 4 (aOR: 5.47; 95%CI: 2.18-13.69, p<0.001) or stage 5 (aOR: 1.71; 95%CI: 1.04-2.81, p=0.036), and having chronic lung disease (aOR: 3.08; 95%CI: 1.22-7.77, p=0.017) significantly increased the risk of COVID-19 mortality. In contrast, COVID-19 vaccination reduced the risk of COVID-19-associated death. This study highlights that more severe comorbidities, advanced age, and incomplete vaccination were associated with COVID-19 mortality.

The coronavirus disease (COVID-19) pandemic has occurred in Massachusetts in multiple waves led by a series of emerging variants. While the evidence has linked obesity with severe symptoms of COVID-19, the effect of obesity on susceptibility to SARS-CoV-2 infection remains unclear. Identification of intrinsic factors, which increase the likelihood of exposed individuals succumbing to productive SARS-CoV-2 infection could help plan mitigation efforts to curb the illness. We aim to investigate whether obese individuals have a higher susceptibility to developing productive SARS-CoV-2 infection given comparable exposure to nonobese individuals. This case-control study leveraged data from the Mass General Brigham's (MGB) electronic medical records (EMR), containing 687,813 patients, to determine whether obesity at any age increases the proportion of infections. We used PCR results of 72,613 subjects who tested positive to SARS-CoV-2 or declared exposure to the virus independently of the result of the test. For this study, we defined susceptibility as the likelihood of testing positive upon suspected exposure. We demonstrate evidence that SARS-CoV-2 exposed obese individuals were more prone to become COVID positive than nonobese individuals [adjusted odds ratio = 1.34 (95% CI: 1.29-1.39)]. Temporal analysis showed significantly increased susceptibility in obese individuals across the duration of the pandemic in Massachusetts. Obese exposed individuals are at a higher risk of getting infected with SARS-CoV-2. This indicates that obesity is not only a risk factor for worsened outcomes but also increases the risk for infection upon exposure. Identifying such populations early will be crucial for curbing the spread of this infectious disease.

Recent studies have demonstrated that individuals hospitalized due to COVID-19 can be affected by "long-COVID" symptoms for as long as one year after discharge.

Our study objective is to identify data-driven clusters of patients using a novel, unsupervised machine learning technique.

The study uses data from 437 patients hospitalized in New York City between March 3rd and May 15th of 2020. The data used was abstracted from medical records and collected from a follow-up survey for up to one-year post-hospitalization. Hospitalization data included demographics, comorbidities, and in-hospital complications. The survey collected long-COVID symptoms, and information on general health, social isolation, and loneliness. To perform the analysis, we created a graph by projecting the data onto eight principal components (PCs) and running the K-nearest neighbors algorithm. We then used Louvain's algorithm to partition this graph into non-overlapping clusters.

The cluster analysis produced four clusters with distinct health and social connectivity patterns. The first cluster (n = 141) consisted of patients with both long-COVID neurological symptoms (74%) and social isolation/loneliness. The second cluster (n = 137) consisted of healthy patients who were also more socially connected and not lonely. The third cluster (n = 96) contained patients with neurological symptoms who were socially connected but lonely, and the fourth cluster (n = 63) consisted entirely of patients who had traumatic COVID hospitalization, were intubated, suffered symptoms, but were socially connected and experienced recovery.

The cluster analysis identified social isolation and loneliness as important features associated with long-COVID symptoms and recovery after hospitalization. It also confirms that social isolation and loneliness, though connected, are not necessarily the same. Physicians need to be aware of how social characteristics relate to long-COVID and patient's ability to cope with the resulting symptoms.

The COVID-19 pandemic has had a significant impact on mental health, and individuals with certain preexisting morbidities-such as obesity-may have disproportionately experienced pandemic-related stress. We aimed to examine whether being obese or overweight was associated with worse mood and trauma among those infected with COVID-19.

Data were collected as part of a larger longitudinal survey study (n = 591) examining the psychological impact of COVID-19. Complete baseline data for those who reported testing positive from April 2020 through June 2021 were examined.

Body mass index was correlated with depression (r = 0.13, P < .01) and generalized anxiety disorder (r = 0.10, P = .02), but not with posttraumatic stress disorder (r = 0.06, P = .16). Multivariable analyses revealed that body mass index was no longer a unique predictor, except for those with a body mass index >40 kg/m2, suggesting that other sociodemographic factors, not obesity, were driving mood symptoms for those infected with COVID-19.

Chronic conditions such as obesity are associated with adverse outcomes in coronavirus disease 2019 (COVID-19) acute respiratory distress syndrome (ARDS) patients. The aim of our study was to evaluate the relationship between BMI and outcomes in critically ill patients with COVID-19 ARDS.

A retrospective study including all patients with COVID-19 and ARDS on mechanical ventilation admitted to the intensive care unit (ICU) over 2 years. Patients with obesity (BMI ≥30 kg/m2) were compared with those without obesity (BMI >18.5 up to 29.9 kg/m2). Outcomes compared were primary (mortality, duration of mechanical ventilation, and length of ICU stay) and secondary complications during the ICU course (inotrope requirement, acute kidney injury [AKI] requiring renal replacement therapy [RRT], and bloodstream and urinary tract infections).

One hundred and eight patients were included in the study. The mean age of patients was 52 years, and 94 (87%) patients were males. As compared to COVID-19 ARDS patients without obesity, COVID-19 patients with obesity were more prone to develop complications like AKI, necessitating continuous RRT (P = 0.005). There was no significant difference in other complications between the two groups (all P > 0.05). There was no increased mortality in these obese patients (P = 0.056). In these patients with obesity, those who also had ischemic heart disease had an increased likelihood of mortality (P = 0.036).

Our study concludes that patients with COVID-19 ARDS who are obese are not at higher risk of mortality and more likely to develop renal complications. When these patients develop cardiac complications or bloodstream infections, they have a significantly higher risk of mortality.

Currently, SARS-CoV-2 is still spreading rapidly and globally. A large proportion of patients with COVID-19 developed liver injuries. The human-induced pluripotent stem cell (iPSC)-derived hepatocytes recapitulate primary human hepatocytes and have been widely used in studies of liver diseases.

To explore the susceptibility of hepatocytes to SARS-CoV-2, we differentiated iPSCs to functional hepatocytes and tried infecting them with different MOI (1, 0.1, 0.01) of SARS-CoV-2.

The iPSC-derived hepatocytes are highly susceptible to virus infection, even at 0.01 MOI. Other than the ancestral strain, iHeps also support the replication of SARS-CoV-2 variants including alpha, beta, theta, and delta. More interestingly, the ACE2 expression significantly upregulated after infection, suggesting a vicious cycle between virus infection and liver injury.

The iPSC-derived hepatocytes can support the replication of SARS-CoV-2, and this platform could be used to investigate the SARS-CoV-2 hepatotropism and hepatic pathogenic mechanisms.

Given the high prevalence of hypertension among Chinese adults, this population is at a significantly increased risk of severe COVID-19 complications. The purpose of this study is to assess the willingness of Chinese hypertensive adults to receive the COVID-19 vaccine and to identify the diverse factors that shape their vaccination decisions.

Sampling was conducted utilizing multistage stratified random sampling, and ultimately, a total of 886 adult hypertensive patients from Luzhou City in Southwest China were included in this study. The questionnaire design was based on the Theory of Planned Behaviour and was used to investigate their willingness to be vaccinated with COVID-19. Structural equation modeling was employed for data analysis.

The results showed that 75.6% of hypertensive individuals were willing to receive COVID-19 vaccination. The structural equation modeling revealed that Subjective Norms (path coefficient = 0.361, CR = 8.049, P < 0.001) and Attitudes (path coefficient = 0.253, CR = 4.447, P < 0.001) had positive effects on vaccination willingness, while Perceived Behavioral Control (path coefficient=-0.004, CR=-0.127, P = 0.899) had no significant impact on Behavioral Attitudes. Mediation analysis indicated that Knowledge (indirect path coefficient = 0.032, LLCI = 0.014, ULCI = 0.058), Risk Perception (indirect path coefficient = 0.077, LLCI = 0.038, ULCI = 0.124), and Subjective Norms (indirect path coefficient = 0.044, LLCI = 0.019, ULCI = 0.087) significantly influenced vaccination willingness through Attitudes as a mediating factor.

The willingness of hypertensive individuals to receive the COVID-19 vaccination is not satisfactory. The Theory of Planned Behavior provides valuable insights into understanding their vaccination intentions. Efforts should be concentrated on enhancing the subjective norms, attitudes, and knowledge about vaccination of hypertensive patients.

The need for the identification of risk factors associated to COVID-19 disease severity remains urgent. Patients' care and resource allocation can be potentially different and are defined based on the current classification of disease severity. This classification is based on the analysis of clinical parameters and routine blood tests, which are not standardized across the globe. Some laboratory test alterations have been associated to COVID-19 severity, although these data are conflicting partly due to the different methodologies used across different studies. This study aimed to construct and validate a disease severity prediction model using machine learning (ML). Seventy-two patients admitted to a Brazilian hospital and diagnosed with COVID-19 through RT-PCR and/or ELISA, and with varying degrees of disease severity, were included in the study. Their electronic medical records and the results from daily blood tests were used to develop a ML model to predict disease severity. Using the above data set, a combination of five laboratorial biomarkers was identified as accurate predictors of COVID-19 severe disease with a ROC-AUC of 0.80 ​±​ 0.13. Those biomarkers included prothrombin activity, ferritin, serum iron, ATTP and monocytes. The application of the devised ML model may help rationalize clinical decision and care.