Clinical Characteristics of Paediatric Hyperinflammatory Syndrome in the Era of Corona Virus Disease 2019 (COVID-19)

Pediatric endocarditis - a stone left after the pandemic cascade

Infective endocarditis is a rare disease in children. The etiology is mainly bacterial. However, viral infective endocarditis, possibly related to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has also been reported. The pathophysiological principle of the connection between the two entities seems to be attributed to the transient immune deficiency of the body during the infection. Additionally, SARS-CoV-2 is reported in the literature as a direct cardiopathic virus. Therefore, the new coronavirus seems to have the ability to affect both the intact cardiac tissue and the previously damaged one both during the acute episode and at a distance from it. Consequently, we propose to review the main pathophysiological aspects of pediatric cardiac damage caused by SARS-CoV-2. The ultimate goal is to deepen existing knowledge, broaden the horizon of understanding and analysis regarding the systemic damage induced by viral infections, and strengthen an information base from which to start a meta-analysis. Next, we performed a non-systematized screening of the specialized literature with reference to cases of endocarditis in the pediatric population, reported in the period 2020-2023. From the total of articles found, we chose to include in the review a number of 6 case reports, including a number of 7 patients (5 children and 2 adolescents). Analysis of reports suggests that SARS-CoV-2 infection could play a role in the development of endocarditis, either directly through active infection or indirectly through a post-infectious immune response. Also, pre-existing conditions and complex medical history predispose to an increased risk of developing a severe, complicated form of endocarditis. Also, the lack of data on the vaccination history and the failure to categorize the infection depending on the type of antibodies (IgM or IgG) in some studies represent a major bias in the reports. The latter make it difficult to evaluate the influence of vaccination and the impact of acute versus chronic infection on the course of cases.

Drug-disease interaction: Clinical consequences of inflammation on drugs action and disposition

Inflammation is a culprit in many conditions affecting millions of people worldwide. A plethora of studies has revealed that inflammation and inflammatory mediators such as cytokines and chemokines are associated with altered expression and activity of various proteins such as those involved in drug metabolism, specifically cytochrome P450 enzymes (CYPs). Emphasis of most available reports is on the inflammation-induced downregulation of CYPs, subsequently an increase in their substrate concentrations, and the link between the condition and the inflammatory mediators such as interleukin-6 and tumor necrosis factor alpha. However, reports also suggest that inflammation influences expression and/or activity of other proteins such as those involved in the drug-receptor interaction. These multifaced involvements render the clinical consequence of the inflammation unexpected. Such changes are shown in many inflammatory conditions including rheumatoid arthritis, Crohn's disease, acute respiratory illnesses as well as natural processes such as aging, among others. For example, some commonly used cardiovascular drugs lose their efficacy when patients get afflicted with inflammatory conditions such as rheumatoid arthritis and Crohn's disease. Interestingly, this is despite increased concentration subsequent to reduced clearance. The observation is attributed to a simultaneous reduction in the expression of target receptor proteins such as the calcium and potassium channel and β-adrenergic receptor as well as the metabolic enzymes. This narrative review summarizes the current understanding and clinical implications of the inflammatory effects on both CYPs and drug-receptor target proteins.

NeuroCORD: A Language Model to Facilitate COVID-19-Associated Neurological Disorder Studies

COVID-19 can lead to multiple severe outcomes including neurological and psychological impacts. However, it is challenging to manually scan hundreds of thousands of COVID-19 articles on a regular basis. To update our knowledge, provide sound science to the public, and communicate effectively, it is critical to have an efficient means of following the most current published data. In this study, we developed a language model to search abstracts using the most advanced artificial intelligence (AI) to accurately retrieve articles on COVID-19-associated neurological disorders. We applied this NeuroCORD model to the largest benchmark dataset of COVID-19, CORD-19. We found that the model developed on the training set yielded 94% prediction accuracy on the test set. This result was subsequently verified by two experts in the field. In addition, when applied to 96,000 non-labeled articles that were published after 2020, the NeuroCORD model accurately identified approximately 3% of them to be relevant for the study of COVID-19-associated neurological disorders, while only 0.5% were retrieved using conventional keyword searching. In conclusion, NeuroCORD provides an opportunity to profile neurological disorders resulting from COVID-19 in a rapid and efficient fashion, and its general framework could be used to study other COVID-19-related emerging health issues.