Search

Objective: To characterize the cognitive profile of long COVID-19 subjects and its possible association with clinical symptoms, emotional disturbance, biomarkers, and disease severity. Methods: We performed a single-center cross-sectional cohort study. Subjects between 20 and 60 years old with confirmed COVID-19 infection were included. The assessment was performed 6 months following hospital or ambulatory discharge. Excluded were those with prior neurocognitive impairment and severe neurological/neuropsychiatric disorders. Demographic and laboratory data were extracted from medical records. Results: Altogether, 108 participants were included, 64 were male (59.25%), and the mean age was 49.10 years. The patients were classified into four groups: non-hospitalized (NH, n = 10), hospitalized without Intensive Care Unit (ICU) or oxygen therapy (HOSPI, n = 21), hospitalized without ICU but with oxygen therapy (OXY, n = 56), and ICU (ICU, n = 21) patients. In total, 38 (35.18%) reported Subjective Cognitive Complaints (SCC). No differences were found considering illness severity between groups. Females had more persistent clinical symptoms and SCC than males. Persistent dyspnea and headache were associated with higher scores in anxiety and depression. Persistent fatigue, anxiety, and depression were associated with worse overall cognition. Conclusions: No cognitive impairment was found regarding the severity of post-COVID-19 infection. SCC was not associated with a worse cognitive performance, but with higher anxiety and depression. Persistent clinical symptoms were frequent independent of illness severity. Fatigue, anxiety, and depression were linked to poorer cognitive function. Tests for attention, processing speed, and executive function were the most sensitive in detecting cognitive changes in these patients. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic has brought attention to the long-term consequences of the virus, particularly the persistent symptoms that characterize long COVID. This syndrome, which can last for months after the initial infection, includes a range of neurological and neuropsychiatric manifestations that have significant implications for brain health and dementia research. This review explores the current understanding of long COVID's cognitive, neurological, and psychiatric symptoms and their potential impact on brain stimulation and neuroimaging studies. It argues that researchers must adapt their study designs and screening processes to account for the confounding effects of long COVID and ensure the accuracy and reliability of their findings. To advance the understanding of this condition and its long-term effects on brain health, the review proposes a series of strategies, including the development of standardized screening tools, the investigation of underlying mechanisms, and the identification of risk factors and protective factors. It also emphasizes the importance of collaborative research efforts and international data sharing platforms in accelerating the pace of discovery and developing targeted interventions for individuals with long COVID. As the prevalence of this condition continues to grow, it is imperative that the neuroscience community comes together to address this challenge and support those affected by long COVID. [ABSTRACT FROM AUTHOR]

Cutting-edge brain imaging techniques, particularly positron emission tomography with Fluorodeoxyglucose (PET/FDG), are being used in conjunction with Artificial Intelligence (AI) to shed light on the neurological symptoms associated with Long COVID. AI, particularly deep learning algorithms such as convolutional neural networks (CNN) and generative adversarial networks (GAN), plays a transformative role in analyzing PET scans, identifying subtle metabolic changes, and offering a more comprehensive understanding of Long COVID's impact on the brain. It aids in early detection of abnormal brain metabolism patterns, enabling personalized treatment plans. Moreover, AI assists in predicting the progression of neurological symptoms, refining patient care, and accelerating Long COVID research. It can uncover new insights, identify biomarkers, and streamline drug discovery. Additionally, the application of AI extends to non-invasive brain stimulation techniques, such as transcranial direct current stimulation (tDCS), which have shown promise in alleviating Long COVID symptoms. AI can optimize treatment protocols by analyzing neuroimaging data, predicting individual responses, and automating adjustments in real time. While the potential benefits are vast, ethical considerations and data privacy must be rigorously addressed. The synergy of AI and PET scans in Long COVID research offers hope in understanding and mitigating the complexities of this condition. [ABSTRACT FROM AUTHOR]

Post-COVID-19 syndrome (PCS) fatigue is typically most severe <6 months post-infection. Combining magnetic resonance imaging (MRI) and positron emission tomography (PET) imaging with the glucose analog [18F]-Fluorodeoxyglucose (FDG) provides a comprehensive overview of the effects of PCS on regional brain volumes and metabolism, respectively. The primary purpose of this exploratory study was to investigate differences in MRI/PET outcomes between people < 6 months (N = 18, 11 female) and > 6 months (N = 15, 6 female) after COVID-19. The secondary purpose was to assess if any differences in MRI/PET outcomes were associated with fatigue symptoms. Subjects > 6 months showed smaller volumes in the putamen, pallidum, and thalamus compared to subjects < 6 months. In subjects > 6 months, fatigued subjects had smaller volumes in frontal areas compared to non-fatigued subjects. Moreover, worse fatigue was associated with smaller volumes in several frontal areas in subjects > 6 months. The results revealed no brain metabolism differences between subjects > 6 and < 6 months. However, both groups exhibited both regional hypo- and hypermetabolism compared to a normative database. These results suggest that PCS may alter regional brain volumes but not metabolism in people > 6 months, particularly those experiencing fatigue symptoms. [ABSTRACT FROM AUTHOR]

Background: Common long-term sequelae after COVID-19 include fatigue and cognitive impairment. Although symptoms interfere with daily living, the underlying pathology is largely unknown. Previous studies report relative hypometabolism in frontal, limbic and cerebellar regions suggesting focal brain involvement. We aimed to determine whether absolute hypometabolism was present and correlated to same day standardized neurocognitive testing. Methods: Fourteen patients included from a long COVID clinic had cognitive testing and quantitative dynamic [18F]FDG PET of the brain on the same day to correlate cognitive function to metabolic glucose rate. Results: We found no hypometabolism in frontal, limbic and cerebellar regions in cognitively impaired relative to cognitive intact patients. In contrast, the cognitive impaired patients showed higher cerebellar metabolism (p = 0.03), which correlated with more severe deficits in working memory and executive function (p = 0.03). Conclusions: Hypermetabolism in the cerebellum may reflect inefficient brain processing and play a role in cognitive impairments after COVID-19. [ABSTRACT FROM AUTHOR]