In recent decades, the elderly population has increased at higher rates than any other population group, resulting in an increase in age-related diseases such as neurodegenerative and cognitive impairment. To address this global health problem, it is necessary to search for new dietary strategies that can prevent the main neurocognitive problems associated with the ageing process. Therefore, the aim of the present study was to analyze the effect of cocoa flavanols and red berry anthocyanins on brain-derived neurotrophic factor (BDNF) and nerve growth factor receptor (NGF-R) and to stablish the possible improvement in cognitive performance by using a battery of neurocognitive tests that included the Verbal Learning Test Spain-Complutense, the Spatial Recall Test 10/36 BRB-N, the Wechsler Adult Intelligence Scale III and IV, the STROOP Task and the Tower of London Test. A randomized, double-blind, parallel-group study was performed in 60 healthy volunteers between 50 and 75 years old who consumed a cocoa powder, a red berries mixture or a combination of both for 12 weeks. After the intervention, we observed a reduction in the time needed to start (p = 0.031) and finish (p = 0.018) the neurocognitive test known as the Tower of London in all groups, but the decrease in time to finish the task was more pronounced in the intervention with the combination of cocoa-red berries group. We failed to show any significant difference in BDNF and NGF-R sera levels. However we found a negative correlation between BDNF and the number of movements required to finish the TOL in women (p = 0.044). In conclusion, our study showed an improvement in executive function, without any change in neurotrofin levels, for all intervention arms.

Post-COVID syndrome (PCS) is a medical condition characterized by the persistence of a wide range of symptoms after acute infection by SARS-CoV-2. The work capacity consequences of this disorder have scarcely been studied. We aimed to analyze the factors associated with occupational status in patients with PCS. This cross-sectional study involved 77 patients with PCS on active work before SARS-CoV-2 infection. Patients were evaluated 20.71 ± 6.50 months after clinical onset. We conducted a survey on occupational activity and cognitive and clinical symptoms. The association between occupational activity and fatigue, depression, anxiety, sleep quality, and cognitive testing was analyzed. Thirty-eight (49.4%) patients were working, and thirty-nine (50.6%) patients were not. Of those not working at the moment of the assessment, 36 (92.3%) patients were on sick leave. In 63 patients (81.8% of the sample), sick leave was needed at some point due to PCS. The mean duration of sick leave was 12.07 ± 8.07 months. According to the patient’s perspective, the most disabling symptoms were cognitive complaints (46.8%) and fatigue (31.2%). Not working at the moment of the assessment was associated with higher levels of fatigue and lower cognitive performance in the Stroop test. No association was found between occupational status with depression and anxiety questionnaires. Our study found an influence of PCS on work capacity. Fatigue and cognitive issues were the most frequent symptoms associated with loss of work capacity.

Fatigue is one of the most disabling symptoms in several neurological disorders and has an important cognitive component. However, the relationship between self-reported cognitive fatigue and objective cognitive assessment results remains elusive. Patients with post-COVID syndrome often report fatigue and cognitive issues several months after the acute infection. We aimed to develop predictive models of fatigue using neuropsychological assessments to evaluate the relationship between cognitive fatigue and objective neuropsychological assessment results. We conducted a cross-sectional study of 113 patients with post-COVID syndrome, assessing them with the Modified Fatigue Impact Scale (MFIS) and a comprehensive neuropsychological battery including standardized and computerized cognitive tests. Several machine learning algorithms were developed to predict MFIS scores (total score and cognitive fatigue score) based on neuropsychological test scores. MFIS showed moderate correlations only with the Stroop Color–Word Interference Test. Classification models obtained modest F1-scores for classification between fatigue and non-fatigued or between 3 or 4 degrees of fatigue severity. Regression models to estimate the MFIS score did not achieve adequate R2 metrics. Our study did not find reliable neuropsychological predictors of cognitive fatigue in the post-COVID syndrome. This has important implications for the interpretation of fatigue and cognitive assessment. Specifically, MFIS cognitive domain could not properly capture actual cognitive fatigue. In addition, our findings suggest different pathophysiological mechanisms of fatigue and cognitive dysfunction in post-COVID syndrome.