Presence of SARS-CoV-2 RNA in COVID-19 survivors with post-COVID symptoms 2 years after hospitalization: The VIPER study.

The SARS-CoV-2 VIrus PERsistence (VIPER) study investigated the presence of long-lasting SARS-CoV-2 RNA in plasma, stool, urine, and nasopharyngeal samples in COVID-19 survivors. The presence of SARS-CoV-2 RNA reverse transcription polymerase chain reactions (RT-PCR) were analyzed within plasma, stool, urine, and nasopharyngeal swab samples in COVID-19 survivors with post-COVID symptoms and a comparison group of COVID-19 survivors without post-COVID symptoms matched by age, sex, body mass index and vaccination status. Participants self-reported the presence of any post-COVID symptom (defined as a symptom that started no later than 3 months after the initial infection). Fifty-seven (57.9% women, age: 51.1, standard deviation [SD]: 10.4 years) previously hospitalized COVID-19 survivors with post-COVID symptoms and 55 (56.4% women, age: 50.0, SD: 12.8 years) matched individuals who had a past SARS-CoV-2 infection without post-COVID symptoms were evaluated 27 (SD 7.5) and 26 (SD 8.7) months after hospital discharge, respectively. The presence of SARS-CoV-2 RNA was identified in three nasopharyngeal samples of patients with post-COVID symptoms (5.2%) but not in plasma, stool, or urine samples. Thus, SARS-CoV-2 RNA was not identified in any sample of survivors without post-COVID symptoms. The most prevalent post-COVID symptoms consisted of fatigue (93%), dyspnea, and pain (both, 87.7%). This study did not find SARS-CoV-2 RNA in plasma, stool, or urine samples, 2 years after the infection. A prevalence of 5.2% of SARS-CoV-2 RNA in nasopharyngeal samples, suggesting a potential active or recent reinfection, was found in patients with post-COVID symptoms. These results do not support the association between SARS-CoV-2 RNA in plasma, stool, urine, or nasopharyngeal swab samples and post-COVID symptomatology in the recruited population.

Exploring Cognitive Dysfunction in Long COVID Patients: Eye Movement Abnormalities and Frontal-Subcortical Circuits Implications via Eye-Tracking and Machine Learning.

BACKGROUND: Cognitive dysfunction is regarded as one of the most severe aftereffects following coronavirus disease 2019 (COVID-19). Eye movements, controlled by several brain areas, such as the dorsolateral prefrontal cortex and frontal-thalamic circuits, provide a potential metric for assessing cortical networks and cognitive status. We aimed to examine the utility of eye movement measurements in identifying cognitive impairments in long COVID patients. METHODS: We recruited 40 long COVID patients experiencing subjective cognitive complaints and 40 healthy controls and used a certified eye-tracking medical device to record saccades and antisaccades. Machine learning was applied to enhance the analysis of eye movement data. RESULTS: Patients did not differ from the healthy controls regarding age, sex, and years of education. However, the patients' Montreal Cognitive Assessment total score was significantly lower than healthy controls. Most eye movement parameters were significantly worse in patients. These included the latencies, gain (computed as the ratio between stimulus amplitude and gaze amplitude), velocities, and accuracy (evaluated by the presence of hypermetric or hypometria dysmetria) of both visually and memory-guided saccades; the number of correct memory saccades; the latencies and duration of reflexive saccades; and the number of errors in the antisaccade test. Machine learning permitted distinguishing between long COVID patients experiencing subjective cognitive complaints and healthy controls. CONCLUSION: Our findings suggest impairments in frontal subcortical circuits among long COVID patients who report subjective cognitive complaints. Eye-tracking, combined with machine learning, offers a novel, efficient way to assess and monitor long COVID patients' cognitive dysfunctions, suggesting its utility in clinical settings for early detection and personalized treatment strategies. Further research is needed to determine the long-term implications of these findings and the reversibility of cognitive dysfunctions.

In-hospital incidence of and risk factors for influenza-associated respiratory failure.

BACKGROUND: Respiratory failure (RF) is the most important complication of influenza virus infection. Its definition and incidence are heterogeneous in the literature. METHODS: This systematic review and meta-analysis aim to determine the incidence of and risk factors for RF in patients hospitalized with influenza. Electronic databases were searched for articles on RF in patients hospitalized for influenza infection up to December 2021 regardless of their geographical location. Observational and experimental studies were considered for inclusion, excluding case series. The Newcastle-Ottawa and Johanna Briggs scales were used for quality assessment. A random-effects meta-analysis was performed, followed by subgroup analyses according to, among others, presence/absence of pneumonia, RF definition, serotype and time period. PRISMA guidelines were followed for this review. RESULTS: Thirty-six studies were finally included in the meta-analysis. Overall, RF incidence was 24% (range 5%-85%, 95% confidence interval [95CI] 19%-31%). Significantly higher incidences of RF were found in patients with pneumonia (42%, 95CI 28%-57%, p = .006), when RF was defined as hypoxemia (58%, 95CI 31%-81%, p < .001), and during the 2009 pandemic (25%, 95CI 16%-36%) and postpandemic period (23%, 95CI 15%-34%, p = .01). No differences were found between human influenza serotypes. Assessment of risk factors associated with the development of RF was not possible due to their inconsistent and heterogeneous reporting. CONCLUSION: Respiratory failure is frequent in hospitalized influenza patients, especially in patients with pneumonia and since the 2009 pandemic, although its definition and reporting widely vary in the literature. This complicates its characterization and comparison between cohorts and with other respiratory viruses.

A Short Corticosteroid Course Reduces Symptoms and Immunological Alterations Underlying Long-COVID.

Despite the growing number of patients with persistent symptoms after acute SARS-CoV-2 infection, the pathophysiology underlying long-COVID is not yet well characterized, and there is no established therapy. We performed a deep immune profiling in nine patients with persistent symptoms (PSP), before and after a 4-day prednisone course, and five post-COVID-19 patients without persistent symptoms (NSP). PSP showed a perturbed distribution of circulating mononuclear cell populations. Symptoms in PSP were accompanied by a pro-inflammatory phenotype characterized by increased conventional dendritic cells and augmented expression of antigen presentation, co-stimulation, migration, and activation markers in monocytes. The adaptive immunity compartment in PSP showed a Th1-predominance, decreased naïve and regulatory T cells, and augmentation of the PD-1 exhaustion marker. These immune alterations reverted after the corticosteroid treatment and were maintained during the 4-month follow-up, and their normalization correlated with clinical amelioration. The current work highlights an immunopathogenic basis together with a possible role for steroids in the treatment for long-COVID.