INTRODUCTION: There is a growing interest in the effect of Long-COVID (LC) on cognition, and neuroimaging allows us to gain insight into the structural and functional changes underlying cognitive impairment in LC. We used multimodal neuroimaging data in combination with neuropsychological evaluations to study cognitive complaints in a cohort of LC patients with mild to moderate severity symptoms. METHODS: We conducted a 3T brain magnetic resonance imaging (MRI) study with diffusion tensor imaging (DTI) and functional MRI (fMRI) sequences on 53 LC patients 1.8 years after acute COVID-19 onset. We administered neuropsychological tests to evaluate cognitive domains and examined correlations with Tract-Based Spatial Statistics (TBSS) and resting state. RESULTS: We included 53 participants with LC (mean age, 48.23 years; 88.7% females). According to the Frascati criteria, more than half of the participants had deficits in the executive (59%) and attentional (55%) domains, while 40% had impairments in the memory domain. Only one participant (1.89%) showed problems in the visuospatial and visuoconstructive domain. We observed that increased radial diffusivity in different white matter tracts was negatively correlated with the memory domain. Our results showed that higher resting state activity in the fronto-parietal network was associated with lower memory performance. Moreover, we detected increased functional connectivity among the bilateral hippocampus, the right hippocampus and the left amygdala, and the right hippocampus and the left middle temporal gyrus. These connectivity patterns were inversely related to memory and did not survive false discovery rate (FDR) correction. DISCUSSION: People with LC exhibit cognitive impairments linked to long-lasting changes in brain structure and function, which justify the cognitive alterations detected.

INTRODUCTION: The Frail-VIG index-and the Pfeiffer test are measurements used in Primary Care for assessment frailty and the cognitive impairment screening. The Frail-VIG index is a multidimensional instrument that allows a rapid assessment of the degree of frailty in the context of clinical practice. OBJECTIVE: Our aim was to investigate the convergent and discriminative validity of the Frail-VIG index with regard to Pfeiffer test value. DESIGN: A cross-sectional study. SITE: Two urban Primary Health Care centres of the Catalan Institute of Health, Barcelona (Spain). PARTICIPANTS: All people included under a home care programme during the year 2018. No exclusion criteria were applied. MAIN MEASUREMENTS: We used the Frail-VIG index to measure frailty and the Pfeiffer test to cognitive impairment screening. Trained nurses administered both instruments during face-to-face assessments in a participant’s home during usual care. The relationships between both instruments were examined using Pearson’s correlation coefficient. RESULTS: A total of 412 participants were included. Frail-VIG score and Pfeiffer test value were moderately correlated (r=0.564; P<0.001). Non-frail people had a lower risk of developing cognitive impairment than moderate to severe frail people. The value of the Pfeiffer test increased significantly as the Frail-VIG index score also increased. CONCLUSIONS: Frail-VIG index demonstrated a convergent validity with the Pfeiffer test. Its discriminative validity was optimal, as their scores showed an excellent capacity to differentiate between people with a higher and lower risk of developing cognitive impairment. These findings provide additional pieces of evidence for construct validity of the Frail-VIG index.

Introduction Breastfeeding (BF) is the healthiest form of nutrition for babies and is recommended exclusively (EBF) for at least the first six months of life. The carbon footprint of formula feeding (FF) has been studied, but that of BF is unknown. Aim To identify the environmental impact of three types of infant feeding taking into account the accessories needed and the diet of postpartum women in the baby’s first month of life. Methods This is a multicentre, cross-sectional study conducted in the Barcelona North Metropolitan Area (Catalonia, Spain). The participating sites are primary care settings that will recruit 408 postpartum women (4-6 weeks) as per inclusion/exclusion criteria. The data will be collected through a GREEN MOTHER Survey that includes 4 dimensions: 1) socio-demographic and clinical data; 2) data on the newborn and accessories used in infant feeding; 3) general data on the mother’s diet (food consumption habits), and 4) recording of 24 h of the mother’s diet. The data analysis will be performed to check the prevalence of infant feeding types at birth and month 1, as well as a comparative analysis of three types of infant feeding on environmental impact (climate change; water consumption, and scarcity). Ethics. This project was approved by the Research Ethics Committee of the Jordi Gol i Gurina University Institute Foundation for Primary Health Care Research (IDIAP) under code 22/101-P dated 22/02/2023. Discussion A second phase of the GREEN MOTHER study is planned, which will consist of an educational intervention to promote breastfeeding, nutrition and sustainability. This intervention will be based on the results obtained in Phase I. We expect that the project results – through the publication and dissemination of scientific papers and reports among relevant stakeholders (association of community midwives, healthcare and primary care attention professionals and the public) – will increase public awareness of breastfeeding and its impact on sustainability.

Introduction Personality plays a crucial role in shaping an individual’s interactions with the world. The Big Five personality traits are widely used frameworks that help describe people’s psychological behaviours. These traits predict how individuals behave within an organizational setting.Methods In this article, we introduce a virtual reality (VR) strategy for relatively scoring an individual’s personality to evaluate the feasibility of predicting personality traits from implicit measures captured from users interacting in VR simulations of different organizational situations. Specifically, eye-tracking and decision-making patterns were used to classify individuals according to their level in each of the Big Five dimensions using statistical machine learning (ML) methods. The virtual environment was designed using an evidence-centered design approach.Results The dimensions were assessed using NEO-FFI inventory. A random forest ML model provided 83% accuracy in predicting agreeableness. A k-nearest neighbour ML model provided 75%, 75%, and 77% accuracy in predicting openness, neuroticism, and conscientiousness, respectively. A support vector machine model provided 85% accuracy for predicting extraversion. These analyses indicated that the dimensions could be differentiated by eye-gaze patterns and behaviours during immersive VR.Discussion Eye-tracking measures contributed more significantly to this differentiation than the behavioural metrics. Currently, we have obtained promising results with our group of participants, but to ensure the robustness and generalizability of our findings, it is imperative to replicate the study with a considerably larger sample. This study demonstrates the potential of VR and ML to recognize personality traits.

Background The neurological symptoms of Long COVID (LC) and the impact of neuropsychological manifestations on people’s daily lives have been extensively described. Although a large body of literature describes symptoms, validating this with objective measures is important. This study aims to identify and describe the effects of Long COVID on cognition, balance, and the retinal fundus, and determine whether the duration of symptoms influences cognitive impairment.Methods This cross-sectional study involved LC volunteers with cognitive complaint from public health centers in northern Barcelona who participated between January 2022 and March 2023. This study collected sociodemographic characteristics, information on substance use, comorbidities, and clinical data related to COVID-19. We measured five cognitive domains using a battery of neuropsychological tests. Balance was assessed through posturography and retinal vascular involvement by retinography.Results A total of 166 people with LC and cognitive complaints participated, 80.72% were women and mean age was 49.28 +/- 8.39 years. The most common self-reported symptoms were concentration and memory deficit (98.80%), brain fog (82.53%) and insomnia (71.17%). The 68.67% presented cognitive deficit in at least one domain, with executive functions being the most frequent (43.98%). The 51.52% of the participants exhibited a dysfunctional pattern in balance, and 9.2% showed some alteration in the retina. There were no statistically significant differences between cognitive impairment and symptom duration.Conclusion Our findings contribute to a more comprehensive understanding of the pathology associated with Long COVID. They highlight the diversity of self-reported symptoms, the presence of abnormal balance patterns, and some cognitive impairment. These findings underscore the necessity of addressing the clinical management of this condition in primary care through follow-up and the pursuit of multidisciplinary and comprehensive treatment.