Longitudinal changes in global structural brain connectivity and cognitive performance in former hospitalized COVID-19 survivors: an exploratory study.

BACKGROUND: Long-term sequelae of COVID-19 can result in reduced functionality of the central nervous system and substandard quality of life. Gaining insight into the recovery trajectory of admitted COVID-19 patients on their cognitive performance and global structural brain connectivity may allow a better understanding of the diseases' relevance. OBJECTIVES: To assess whole-brain structural connectivity in former non-intensive-care unit (ICU)- and ICU-admitted COVID-19 survivors over 2 months following hospital discharge and correlate structural connectivity measures to cognitive performance. METHODS: Participants underwent Magnetic Resonance Imaging brain scans and a cognitive test battery after hospital discharge to evaluate structural connectivity and cognitive performance. Multilevel models were constructed for each graph measure and cognitive test, assessing the groups' influence, time since discharge, and interactions. Linear regression models estimated whether the graph measurements affected cognitive measures and whether they differed between ICU and non-ICU patients. RESULTS: Six former ICU and six non-ICU patients completed the study. Across the various graph measures, the characteristic path length decreased over time (ß = 0.97, p = 0.006). We detected no group-level effects (ß = 1.07, p = 0.442) nor interaction effects (ß = 1.02, p = 0.220). Cognitive performance improved for both non-ICU and ICU COVID-19 survivors on four out of seven cognitive tests 2 months later (p < 0.05). CONCLUSION: Adverse effects of COVID-19 on brain functioning and structure abate over time. These results should be supported by future research including larger sample sizes, matched control groups of healthy non-infected individuals, and more extended follow-up periods.

Antibiotic prescriptions in the context of suspected bacterial respiratory tract superinfections in the COVID-19 era: a retrospective quantitative analysis of antibiotic consumption and identification of antibiotic prescription drivers.

This study aims to quantify antibiotic consumption for suspected respiratory tract superinfections in COVID-19 patients, while investigating the associated drivers of antibiotic prescribing in light of the current signs of antibiotic overuse. Adult patients with a positive COVID-19 diagnosis admitted to a Belgian 721-bed university hospital were analyzed retrospectively (March 11th-May 4th, 2020), excluding short-term admissions (< 24 h). Antibiotic prescriptions were analyzed and quantified, using Defined Daily Doses (DDD) per admission and per 100 bed days. Possible drivers of antibiotic prescribing were identified by means of mixed effects logistic modelling analysis with backwards selection. Of all included admissions (n = 429), 39% (n = 171) were prescribed antibiotics for (presumed) respiratory tract superinfection (3.6 DDD/admission; 31.5 DDD/100 bed days). Consumption of beta-lactamase inhibitor-penicillin combinations was the highest (2.55 DDD/admission; 23.3 DDD/100 bed days). Four drivers were identified: fever on admission (OR 2.97; 95% CI 1.42-6.22), lower SpO2/FiO2 ratio on admission (OR 0.96; 95% CI 0.92-0.99), underlying pulmonary disease (OR 3.04; 95% CI 1.12-8.27) and longer hospital stay (OR 1.09; 95% CI 1.03-1.16). We present detailed quantitative antibiotic data for presumed respiratory tract superinfections in hospitalized COVID-19 patients. In addition to knowledge on antibiotic consumption, we hope antimicrobial stewardship programs will be able to use the drivers identified in this study to optimize their interventions in COVID-19 wards.

Sequence evolution and escape from specific immune pressure of an HIV-1 Rev epitope with extensive sequence similarity to human nucleolar protein 6.

Antigen-specific immunity is crucially important for containing viral replication in human immunodeficiency virus (HIV)-1-infected hosts. Several epitopes have been predicted for the early expressed HIV-1 proteins Tat and Rev, but few have been studied in detail. We characterized the human leukocyte antigen (HLA)-B44-restricted Rev epitope EELLKTVRL (EL9) in an HIV-1-infected subject treated with antiretroviral therapy. Interestingly, a high sequence similarity was found between the EL9 epitope and the human nucleolar protein 6 (NOL6). However, this similarity does not seem to impede immunogenicity as CD8(+) T-cells, previously stimulated with EL9-pulsed dendritic cells, were able to specifically recognize the HIV-1 Rev epitope without cross-recognizing the human self-antigen NOL6. After the subject interrupted antiretroviral therapy and virus rebounded, mutations within the EL9 epitope were identified. Although the emerging mutations resulted in decreased or abolished T-cell recognition, they did not impair Rev protein function. Mutations leading to escape from T-cell recognition persisted for up to 124 weeks following treatment interruption. This study shows that the HLA-B44-restricted Rev CD8(+) T-cell epitope EL9 is immunogenic notwithstanding its close resemblance to a human peptide. The epitope mutates as a consequence of dynamic interaction between T-cells and HIV-1. Clinical status, CD4(+) T-cell count and viral load remained stable despite escape from T-cell recognition.