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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.
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There is evidence of an association between hypertension and retinal arteriolar narrowing. Manual measurement of retinal vessels comes with additional variability, which can be eliminated using automated software. This scoping review aims to summarize research on automated retinal vessel analysis systems. Searches were performed on Medline, Scopus, and Cochrane to find studies examining automated systems for the diagnosis of retinal vascular alterations caused by hypertension using the following keywords: diagnosis; diagnostic screening programs; image processing, computer-assisted; artificial intelligence; electronic data processing; hypertensive retinopathy; hypertension; retinal vessels; arteriovenous ratio and retinal image analysis. The searches generated 433 articles. Of these, 25 articles published from 2010 to 2022 were included in the review. The retinographies analyzed were extracted from international databases and real scenarios. Automated systems to detect alterations in the retinal vasculature are being introduced into clinical practice for diagnosis in ophthalmology and other medical specialties due to the association of such changes with various diseases. These systems make the classification of hypertensive retinopathy and cardiovascular risk more reliable. They also make it possible for diagnosis to be performed in primary care, thus optimizing ophthalmological visits.
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The diagnosis of the post-COVID condition is usually achieved by excluding other diseases; however, cognitive changes are often found in the post-COVID disorder. Therefore, monitoring and treating the recovery from the post-COVID condition is necessary to establish biomarkers to guide the diagnosis of symptoms, including cognitive impairment. Our study employs a prospected cohort and nested case-control design with mixed methods, including statistical analyses, interviews, and focus groups. Our main aim is to identify biomarkers (functional and structural neural changes, inflammatory and immune status, vascular and vestibular signs and symptoms) easily applied in primary care to detect cognitive changes in post-COVID cases. The results will open up a new line of research to inform diagnostic and therapeutic decisions with special considerations for cognitive impairment in the post-COVID condition.
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OBJECTIVE: The aims of this study are to analyze the role of artery-vein ratio AVR assessment using VesselMap 2 software (Imedos Systems) and cardiovascular risk evaluation by means of REGICOR in the prediction of silent brain infarction (SBI) in middle-age hypertensive patients from the ISSYS study. MATERIAL AND METHODS: A cross-sectional study with 695 patients with hypertension aged 50 to 70 years who participated in the project Investigating Silent Strokes in HYpertensives: a Magnetic Resonance Imaging Study (ISSYS), was conducted in two Primary Care Centres of Barcelona. Participants agreed to a retinography and an MRI to detect silent brain infarction (SBI). The IMEDOS software was used for the semiautomatic caliber measurement of retinal arteries and veins, and the AVR was considered abnormal when <0.66. The REGICOR score was calculated for all patients. RESULTS: Multivariate logistic regression analysis was used to evaluate the impact of AVR and REGICOR scores on SBI. The OR (odds ratio) for a high REGICOR score and an abnormal AVR were 3.16 and 4.45, respectively. When analysing the interaction of both factors, the OR of an abnormal AVR and moderate REGICOR score was 3.27, whereas with a high REGICOR score it reached 13.07. CONCLUSIONS: The measurement of AVR in patients with hypertension and with a high REGICOR score can contribute to the detection of silent brain infarction.