Search Results (2,755)

The COVID-19 pandemic initially focused clinical efforts on hospitalized patients. However, as the pandemic progressed, attention shifted to outpatients who often experience milder symptoms yet still contribute to viral transmission. This scoping review aimed to document and evaluate the clinical outcomes assessed in randomized controlled trials (RCTs) involving outpatients with COVID-19, identifying gaps and areas for improvement in trial design. This review followed the PRISMA-ScR guidelines. A comprehensive search of four electronic databases (PubMed, Scopus, Cochrane CENTRAL, and Web of Science) was conducted for RCTs published between December 2019 and December 2023. Studies were included if they involved outpatients with confirmed COVID-19 and reported clinical outcomes. Data were extracted from eligible studies, and outcomes were categorized using the COMET taxonomy. A total of 91 studies were included, representing a wide geographical distribution, with the USA, Iran, and Brazil contributing the most studies. The most frequently investigated treatments included hydroxychloroquine, fluvoxamine, convalescent plasma, and ivermectin. Key outcomes focused on hospitalization rates, symptom resolution, and disease progression. Mortality, although less common in outpatients, was reported in 65 studies, underscoring the importance of outpatient interventions. This review highlights the need for standardized outcome measures in outpatient COVID-19 trials. Full article

The recent global spread of the SARS-CoV-2 pathogen, which causes COVID-19, and its rapid mutation, requires the fast development of effective preventive and treatment measures. According to WHO reports, over 778 million confirmed cases of COVID-19 have been reported, including approximately 7 million deaths. The androgen-regulated cell-surface serine protease TMPRSS2 interacts with the SARS-CoV-2 spike protein. Therefore, directly inhibiting TMPRSS2 will negatively impact the activation of coronaviruses and, consequently, disease progression. That is why TMPRSS2 is a very important target in current drug discovery. On the other hand, it is known that C₆₀ fullerene (a nearly spherical molecule consisting of 60 carbon atoms) exhibits activity against various protein targets. Here, for the first time, the potential binding of C₆₀ fullerene with TMPRSS2 was investigated using different computer simulation methods, including p2Rank, PCA, gmx_MMPBSA analysis, molecular docking, and molecular dynamics simulations. As a result, four potential binding pockets on the TMPRSS2 surface that could interact with C₆₀ fullerene were identified. Among all “C₆₀ fullerene-TMPRSS2” complexes, one was selected as the most promising binding site based on the results of computational modeling evaluations. This opens up the prospect of creating new anticoronavirus drugs based on these carbon nanoparticles. Full article

Background: Immunological monitoring in multiple sclerosis (MS) patients treated with disease-modifying drugs may help predict infectious complications and guide treatment. The main objective of this study was to evaluate whether anti-CD20 treatments in MS patients induce immunodeficiency and whether certain immunological parameters can predict the risk of infection and response to treatment. Methods: This retrospective, observational, single-centre study included MS patients who started treatment with ocrelizumab or rituximab and received follow-up in the Neuroimmunology Unit of our centre between January 2017 and January 2023. The study was conducted in collaboration with the Immunology Department of this hospital. Results: Fifty-five patients were included, with a mean age of 47 years and a follow-up period of 24 months. Analyses of lymphocyte subpopulations (T, B, NK) and immunoglobulin levels (IgG, IgA, IgM) were performed before treatment and at 6-, 12- and 24-month follow-ups. In addition, we carried out an exhaustive study of B cells in the baseline analysis. Sixty-four percent of patients presented infections, mostly due to COVID-19. Three patients developed cryptogenic organising pneumonia. IgG hypogammaglobulinemia was the main risk factor for developing infections. Patients with infections had fewer mature memory B cells and a lower percentage of NK cells. Furthermore, a lower proportion of naïve and mature memory B cells was associated with inflammatory activity and disease progression, respectively. The absence of CD20 depletion during follow-up was associated with clinical worsening. Conclusions: Baseline immunophenotype and immunological monitoring can help predict the risk of infections and the efficacy of anti-CD20 therapy in MS patients. Full article

Background/Objectives: The COVID-19 pandemic accelerated the inappropriate use of antibiotics, amplifying the global threat of antimicrobial resistance (AMR), particularly in resource-limited healthcare settings. This study investigated AMR patterns in a tertiary care hospital, focusing on the impact of the COVID-19 pandemic on invasive bacterial pathogens. Methods: This retrospective observational study was conducted at the University Clinical Centre of the Republic of Srpska, analyzing AMR data from invasive bacterial isolates collected between 2015 and 2024, and assessing correlations between antibiotic utilization and resistance patterns during the study periods. Results: Among 4718 invasive bacterial isolates, Acinetobacter spp. (26.7%) and K. pneumoniae (20.8%) were the most prevalent. A significant increase in invasive isolates was observed during the COVID-19 period, particularly for K. pneumoniae (p = 0.003), P. aeruginosa (p = 0.017), Acinetobacter spp. (p = 0.013), and E. faecium (p = 0.028). The highest multidrug-resistant (MDR) rates were observed in Acinetobacter spp. (97% during COVID-19) and K. pneumoniae (>80% post-COVID-19). Resistance increased significantly in K. pneumoniae to cephalosporins, fluoroquinolones, and carbapenems, and in P. aeruginosa and Acinetobacter spp. to carbapenems, while P. aeruginosa resistance to aminoglycosides declined. Strong correlations were found between carbapenems use and Acinetobacter spp. resistance (r = 0.861, p = 0.001), and vancomycin use and E. faecalis resistance (r = 0.798, p = 0.006). Moderate correlations were also observed between carbapenems use and resistance of K. pneumoniae and P. aeruginosa. Conclusions: These findings highlight the profound impact of the COVID-19 pandemic on AMR dynamics, particularly among Gram-negative pathogens, and underscore the urgent need for strengthened antimicrobial stewardship and targeted surveillance to curb the spread of MDR pathogens, especially in resource-limited hospitals. Full article

Over 100 million pregnant people worldwide remain at risk of COVID-19. We compared the prevalence of severe COVID-19 in pregnancy and in people of reproductive age, and the risk of adverse pregnancy/neonatal outcomes in those with/without COVID-19 during gestation. In the Canadian Mother–Child Cohort, two sub-cohorts were identified using medical services, prescription medication fillings, hospitalizations, and COVID-19 surveillance testing programs data (28 February 2020–2021). The first included all pregnant people with at least one completed trimester of pregnancy during the study period, stratified on COVID-19 status. The second included all non-pregnant people (aged 15–45) with a positive COVID-19 test during the same period. COVID-19 severity was categorized based on hospital admissions before the end of pregnancy. Associations between COVID-19 during pregnancy and adverse perinatal outcomes were quantified using log-binomial regressions. A total of 150,345 pregnant people (3464 (2.3%) had COVID-19), and 112,073 non-pregnant people with COVID-19 were included. Maternal age at the time of COVID-19 diagnosis/positive test was statistically significantly lower among pregnant individuals compared to those who were not pregnant (96% had less than 40 years vs. 80%, p < 0.001). In pregnancy, COVID-19 was associated with the risk of spontaneous abortions (adjRR 1.76, 95%CI 1.37, 2.25), gestational diabetes (adjRR 1.52, 95%CI 1.18, 1.97), prematurity (adjRR 1.30, 95%CI 1.01, 1.67), and NICU (adjRR 1.32, 95%CI 1.10, 1.59); COVID-19 treatment with medications reduced risks. Severe COVID-19 was more prevalent in pregnancy and was associated with higher risks of adverse maternal/neonatal outcomes. As some countries are pulling back preventive strategies for COVID-19, this study highlights the importance of continued surveillance during pregnancy to prevent adverse pregnancy outcomes. Full article

Background and Clinical Significance: Atrophic rhinitis (AR) is a rare, chronic inflammatory condition characterized by progressive atrophy of the nasal mucosa and underlying bone. The present report describes a case of severe secondary AR as a sequela of COVID-19-associated necrotizing rhinitis, highlighting the diagnostic and management challenges posed by multi-drug resistant pathogens and extensive anatomical destruction. Case Presentation: A 75-year-old female developed progressive necrotizing rhinosinusitis with osteomyelitis following a COVID-19 infection. Computed tomography (CT) confirmed an osteolytic process and subsequent profound anatomical destruction, while histopathology ruled out invasive fungal disease. The resulting cavity was colonized by multi-drug resistant Pseudomonas aeruginosa and Staphylococcus aureus. Management and Outcome: Management focused on preventing crust formation through a structured “nasal rest” protocol, supplemented by cleansing nasal douching with a surfactant (baby soap) and mechanical crust removal. This treatment led to significant clinical improvement, with reduced crusting and complete resolution of ozena symptoms. Conclusions: This case illustrates the potential for SARS-CoV-2 infection to precipitate severe necrotizing sinonasal complications leading to secondary AR. It demonstrates the efficacy of a management strategy focused on mechanical cleansing and nasal rest, particularly when conventional antibiotic therapy is limited by extensive drug resistance. Full article

Long-COVID and Myalgic Encephalomyelitis/Chronic Fatigue Syndrome are disabling diseases characterised by ongoing fatigue, post-exertional malaise, cognitive impairment, and autonomic dysfunction. Myalgic Encephalomyelitis/Chronic Fatigue Syndrome typically follows viral infections, whereas Long-COVID exclusively follows SARS-CoV-2 infection, with overlapping but distinct features. This review uses comprehensive searches of online databases to compare their clinical presentations, pathophysiologies, and treatments. Both Long-COVID and ME/CFS appear to involve multifactorial mechanisms, including viral persistence, immune dysregulation, endothelial dysfunction, and autoimmunity, though their relative contributions remain uncertain. Symptom management strategies are consistent, however. Cognitive behaviour therapy has been successful, and there are minimal drug treatments. Graded exercise therapy occupies a contested place, recommending individualised pacing and multidisciplinary rehabilitation. Common and exclusive mechanisms must be identified to formulate valuable therapies. A more significant body of research focusing on immune dysfunction as a pathogenic mechanism for advancing the disease and enabling more effective therapies and diagnostics is needed. Full article

Background/Objectives: Molnupiravir (MOV) and nirmatrelvir (NMV) are antiviral drugs that were FDA-approved under the emergency use authorization (EUA) for coronavirus disease-2019 (COVID-19) treatment. MOV and NMV target the viral RNA-dependent RNA polymerase and main protease, respectively. Paxlovid is a combination of NMV and ritonavir (RTV), an inhibitor of the human cytochrome P450-3A4 (hCYP3A4). In this study, the structural consequences in the hCYP3A4 caused by MOV-induced mutations (MIM) were evaluated using in silico tools. Methods: MOV-induced mutations (MIM) were inserted into all the possible hotspots in the active site region of the hCYP3A4 gene, and mutant protein models were built. Structural changes in the heme-porphyrin ring of hCYP3A4 were analyzed in the presence and absence of substrates/inhibitors, including RTV. Molecular dynamics (MD) simulations were performed to analyze the effect of MIM-induced structural changes in hCYP3A4 on drug binding. Results: MD simulations confirm that MIMs, R375G and R440G in hCYP3A4 severely affect the heme-porphyrin ring stability by causing a tilt that in turn affects RTV binding, suggesting a possible inefficiency in the function of hCYP3A4. Similar results were seen for amlodipine, atorvastatin, sildenafil and warfarin, which are substrates of hCYP3A4. Conclusions: The current in silico studies indicate that hCYP3A4 containing MIMs can create complications in the treatment of COVID-19 patients, particularly with co-morbidities due to its functional inefficiency. Hence, clinicians must be vigilant when using MOV in combination with other drugs. Further in vitro studies focused on hCYP3A4 containing MIMs are currently in progress to support our current in silico findings. Full article

Background/Objectives: Research on the association of adverse social determinants of health (SDOH) with severe pediatric coronavirus disease (COVID-19) is limited. We examined associations between SDOH patterns and COVID-19 severity in children. Methods: We conducted a prospective, observational study of children (<18 years) with symptomatic SARS-CoV-2 infection evaluated in an urban pediatric emergency department (March 2021–April 2022) in Detroit, Michigan. Caregivers completed a 34-item survey based on the Healthy People 2030 framework. Severe disease was defined as the occurrence of respiratory/cardiac failure or death within four weeks of diagnosis. Continuous and categorical variables were described using medians and percentages, respectively. Associations between disease severity and risk factors were determined using chi-square tests. Association rule mining was used for feature selection, followed by multivariate logistic regression. Results: We analyzed data from 354 children [6–12 years: 31.1%, Female: 51.1%, Black: 59%, not Hispanic: 84.7%, public insurance: 77.1%, chronic condition: 27.4%]. Of the total, 113 children had severe disease. Most caregivers were 30–44 years old (53.1%), had less than a college degree (70.4%), and income < USD 50,000 (75.2%). Adverse SDOH reported included food/housing insecurity (24.6%), no support (64.7%), unmet childcare needs (35.9%), and lack of transportation (12.7%). After controlling for age, sex, medical history, income, and obesity, severe disease was associated with caregiver use of drugs/alcohol (OR:5.92, p < 0.001) and social discrimination/lack of support (OR: 1.74, p = 0.030). Conclusions: Two SDOH patterns (caregiver use of drugs/alcohol and social discrimination/lack of support) were associated with severe COVID-19. Further studies are needed to confirm findings and develop interventions. Full article

Background: Iodinated contrast agents are widely used in computed tomography (CT) imaging; however, they can cause adverse drug reactions (ADRs) ranging from mild hypersensitivity to severe anaphylaxis. While several clinical risk factors have been identified, large–scale studies incorporating environmental variables remain limited. This study aimed to assess the prevalence and predictors of contrast agent-related ADRs over a 10-year period. Methods: We retrospectively analyzed 221,962 adult outpatients who underwent contrast-enhanced CT between January 2014 and December 2023 at a single tertiary center: Patient characteristics, clinical conditions (e.g., hypertension, allergy history), contrast agent types, premedication status, seasonal trends, temperature, and humidity were examined. ADRs were categorized as mild, moderate, or severe based on American College of Radiology (ACR) guidelines. Logistic regression was used to identify independent predictors. Results: The overall prevalence of ADRs was 0.64% (1423 cases). ADRs were more frequent in females, younger patients, and those receiving premedication. Seasonal and environmental patterns were evident: higher ADR rates occurred in summer and autumn, with positive correlations to ambient temperature and humidity. Among contrast agents, Ioversol (1.4%) and Iomeprol (1.2%) showed the highest ADR rates. The prevalence of mild ADRs increased in the post–COVID-19 period, while that of moderate reactions declined. Conclusions: This real–world study identified multiple clinical and environmental factors associated with ADRs to iodinated contrast agents in CT imaging. The findings suggest the importance of individualized risk assessment and the consideration of environmental factors when planning contrast administration. Full article

The COVID-19 pandemic resulted in high morbidity and mortality, as well as severe social and economic disruption globally. Since the pandemic began in 2019, the severe acute respiratory syndrome, coronavirus 2, has undergone numerous changes, resulting in the emergence of new variants and subvariants. The emergence of new variants of the virus poses a challenge to scientists. There is currently no SARS-CoV-2 variant meeting the criteria of variants of concern, whereas the only variant of interest is JN.1, and there are six variants under monitoring: LP8.1, NP1.8.1, XEC, KP.3, KP.3.1.1 and the latest, XFG (Stratus). Although the latter appears to be more transmissible than the others, genomic evidence indicates that it is less aggressive than some recent variants. Nevertheless, continuous genomic surveillance of COVID-19 is still important to detect any new variants that could threaten public health. Numerous therapeutic strategies, such as drugs, vaccines, and nutritional supplements, are being used to treat COVID-19. This narrative review is an overview of COVID-19 and its various facets, from the number of cases to the therapies used, the current variants, and the ongoing clinical trials, specifically focusing on the most recent studies. Full article

Background: The COVID-19 pandemic had major global repercussions for hospitalized patients, affecting multiple aspects of hospital care. Understanding these effects is important for improving healthcare management and infection control practices. This study aimed to analyze and compare the pandemic’s impact on antimicrobial use in hospitalized patients, with emphasis on therapeutic, microbiological, and pharmacoeconomic aspects. Methods: A retrospective observational study was conducted at a Brazilian tertiary hospital (2018–2022). Adult patients receiving antimicrobials were included. Variables analyzed were antimicrobial consumption, incidence of healthcare-associated infections, resistance profiles, hospital costs, adverse drug reactions, and pharmacy activities. Data were obtained from anonymized institutional records and analyzed using descriptive statistics, time series, and linear regression. Results: Analysis of 268,713 hospitalizations showed that the median monthly number of patients receiving antimicrobials did not increase significantly during the pandemic. Higher consumption of carbapenems, glycopeptides, polymyxins, and echinocandins was linked to more healthcare-associated infections by multidrug-resistant organisms. Clostridioides difficile infections declined. Mortality rose significantly, especially among COVID-19 patients. Costs increased by 39%, with antimicrobial-related expenses up 45.7%. Conclusions: The pandemic intensified antimicrobial use, resistance, and costs. While limited by its single-center design and the use of all inpatients as the denominator, these findings highlight the important need for reinforced antimicrobial stewardship to build healthcare system resilience. Full article

Candidemia is a major global health challenge, with Candida albicans being the most common causative agent. Since antifungal drugs may promote resistance, regular epidemiological studies are required. Nonetheless, microbiological and clinical data on C. albicans in Türkiye are limited. Therefore, we assessed data from C. albicans cases in a tertiary care hospital in Türkiye. Among 171 enrolled patients, the overall mortality rate was 66.7%. Univariate analysis showed that age, intensive care unit (ICU) admission, central venous catheterization, mechanical ventilation, hemodialysis, diabetes mellitus, Coronavirus disease 2019 (COVID-19) infection, steroid use, and hyperalimentation were associated with mortality. Multivariate logistic regression showed that age, ICU admission, steroid use and hyperalimentation were independently associated with mortality. In Cox regression, age, ICU admission, prior antifungal use, and absence of antifungal treatment after candidemia were independently associated with decreased survival. Fluconazole (FLC) was the most frequently used antifungal, and patients treated with FLC + amphotericin B or FLC + echinocandin had the best survival rates. All 171 isolates were susceptible to all tested antifungals. Our findings show high mortality rates and reveal mortality-associated factors. Candida albicans remains susceptible to all antifungals; therefore, timely diagnosis and appropriate antifungal treatment can enhance survival and clinical outcomes. Full article

Pattern recognition and machine learning algorithms have become integral to modern drug discovery, offering powerful tools to uncover complex patterns in biomedical data. This article provides a comprehensive review of state-of-the-art pattern recognition techniques—including traditional machine learning (e.g., support vector machines), deep learning approaches, genome-wide association studies (GWAS), and biomarker discovery methods—as applied in pharmacogenomics and computational drug repurposing. We discuss how these methods facilitate the identification of genetic factors that influence drug response, as well as the in silico screening of existing drugs for new therapeutic uses. Two antiviral agents, ribavirin and lopinavir, are examined as extended case studies in the context of COVID-19, illustrating practical applications of pattern recognition algorithms in analyzing pharmacogenomic data and guiding drug repurposing efforts during a pandemic. We highlight successful approaches such as the machine learning-driven prediction of responders and the AI-assisted identification of repurposed drugs (exemplified by the case of baricitinib for COVID-19), alongside current limitations, including data scarcity, model interpretability, and translational gaps. Finally, we outline future directions for integrating multi-omics data, improving algorithmic interpretability, and enhancing the synergy between computational predictions and experimental validation. The insights presented highlight the promising role of pattern recognition algorithms in advancing precision medicine and accelerating drug discovery, while recognizing the challenges that must be addressed to fully realize their potential. Full article

The COVID-19 pandemic has had a diverse impact worldwide, affecting all strata of society. This article examines the relationship between health system adaptation and socioeconomic inequality in countries and the WHO Eastern Mediterranean Region (WHO-EMR), and we suggest that the dynamics among government response, health system preparedness, and epidemic spread are calibrated by the present socioeconomic inequality. With the use of a panel dataset spanning February 2020 to March 2021 and both linear (PARDL) and nonlinear (PNARDL) estimation techniques, we find that more socioeconomically vulnerable regions were disproportionately hit by the efforts of the pandemic, even in the presence of containment measures. From our findings, we find that health system capacity measures, such as hospital bed density and primary healthcare expenditure, are positively related to long-term economic resilience, while antimicrobial drug resistance is strongly negatively related to it. The study emphasizes the need for selective policy interventions to protect the most disadvantaged groups, a finding of relevance for other high-inequality low- and middle-income countries. Full article