Cognition and vascular endothelial function in hypertensive individuals with and without a history of Covid-19: A Cross-Sectional Study

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Brito, Ádrya Aryelle Ferreira, and 9 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5486274/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Patients with systemic arterial hypertension (SAH) are at higher risk of developing a more severe course of SARS-CoV-2 viral infection, in addition to potentially developing lasting cognitive sequelae. Current literature provides evidence that the mechanism underlying the worse outcome of COVID-19 and the emergence of cognitive impairments in hypertensive individuals is endothelial dysfunction. Flow-mediated dilation (FMD) is a technique that has been used for several decades to assess endothelial function. The aim of the study was to assess the effect of COVID-19 exposure on the cognitive status and endothelial function of patients with SAH. Methodology: A cross-sectional study compared cognitive status, assessed through neuropsychological tests, and endothelial function, assessed through FMD, in 52 patients diagnosed with SAH who were previously exposed or not to mild forms of COVID-19. Patients were allocated into two groups: SAH with COVID-19 exposure (SAH EXP_COVID ) and SAH without COVID-19 (SAH). Assessment was documented between six months and eighteen months post-infection. Results: No difference in FMD% was observed between the studied groups (p=0.69): for the SAH group, FMD% was 6.7 and for the SAH EXP_COVID group, FMD% was 5.4. No differences in cognitive performance were observed when comparing the groups, nor was there a relationship between cognition and endothelial function. Conclusion: There was no difference in endothelial and cognitive function between hypertensive patients infected or not by the SARS-CoV-2 virus with the mild form of the disease. SARS-CoV-2 Endothelium Cognition Memory Figures Figure 1 Figure 2 Introduction Systemic arterial hypertension (SAH) is an important risk factor for the development and progression of cardiovascular diseases. According to the World Health Organization (WHO), cardiovascular diseases affect approximately 1.28 billion adults worldwide, with a prevalence of approximately 30 million people in Brazil. (Barros et al. 2021; Malta et al. 2018 ; Mancia et al. 2023). During the COVID-19 pandemic, it was observed that SAH was the most prevalent chronic disease among those infected by SARS-CoV-2, affecting approximately 30% of the infected individuals. (Gallo et al. 2022 ) Patients with SAH also developed more severe forms of SARS-CoV-2 and death rates compared with infected patients without SAH. (Okay et al. 2020 ; Zhou et al. 2020 ) The acute infection caused by the SARS-CoV-2 virus is accompanied by an aggressive inflammatory response known as a "cytokine storm”. (Iba et al. 2020 ; Ruan et al. 2020 ), which favors the damage of arterial endothelial tissue previously observed in the literature. (Libby and Lüscher 2020 ; Loo et al. 2021 ) In addition, the impairment in the endothelial function caused by SARS-CoV-2 may lead to circulatory disorders such as thrombosis and local tissue damage. (Iba et al. 2020 ; Libby and Lüscher 2020 ; Ambrosino et al. 2022 ). Among the main symptoms of COVID-19, a decrease in cognitive performance has been well documented in the literature including the period of recovery from the virus infection. (Tabacof et al. 2022 ) Known as post-COVID-19 syndrome, the remaining symptoms may last up to two years after the initial infection. (Kamal et al. 2021 ; Nalbandian et al. 2021 ; Taquet et al. 2022 ; Zhao et al. 2023 ) A recent systematic review revealed a notable prevalence of 22% individuals who mentioned cognitive symptoms in post-COVID-19. (Ceban et al. 2022 ). The presence of cognitive symptoms in COVID-19 may be exacerbated in the presence of SAH, which is the greatest risk factor for cerebrovascular diseases. (O'Brien et al. 2003 ; Iadecola and Gottesman 2019 ) SAH gradually and progressively causes vascular endothelial dysfunction (Iadecola and Gottesman 2019 ), which is related to decreased nitric oxide bioavailability, impairing vasodilation and stimulating the premature development of diseases that affect cognition. (Konukoglu and Uzun 2017 ; Puddu et al. 2000 ) Vascular endothelial function assessed by flow-mediated dilation (FMD) is associated with impaired cognition in patients with cerebrovascular diseases. (Naiberg et al. 2016 ) The mechanisms underlying this association suggest a reduced cerebral blood flow and loss of cerebral vasoreactivity. (Martins-Filho et al. 2020 ). Although the clear coexistence of COVID-19 and SAH creates a poorer prognosis for patients infected with SARS-CoV-2 virus, the underlying mechanisms of it remain unknown. Along this line, impaired vascular endothelial function and cognitive performance seem to be promising mechanisms present in both conditions but this is still not properly tested in the literature. Therefore, this study aimed to compare and correlate the effect of COVID-19 exposure in hypertensive patients on cognitive performance and vascular endothelial function. We hypothesize that hypertensive patients after six months of diagnosis of COVID-19, should exhibit greater cognitive impairment and worse vascular endothelial function when compared to the unexposed group. Additionally, worse endothelial function may be associated with poorer cognitive performance. Methods Between March and September 2023, patients with arterial hypertension who contracted COVID-19 (SAH EXP_COVID ) or not (SAH) were evaluated at the University of Pernambuco (UPE), located in the city of Petrolina-PE (Brazil). Patient selection was conducted after the study was announced on radio stations and digital media platforms to recruit research participants. All interested individuals underwent a screening process to confirm eligibility criteria. Ethical procedures The study was approved by the Ethics Committee of UPE, under the following protocol number CAAE: 66973322.0.0000.5191. All participants signed the Informed Consent Form (ICF). Participants This study relied on a convenience sample, where researchers carefully delineated the profile of participants to be included. The sample size was calculated using GPower 3.1.9.4 software, with significance levels α set at 0.05 and β fixed at 0.80, resulting in a total of 42 patients. Additionally, an estimated dropout rate of 20% was considered during the study planning, totaling 52 patients distributed between the groups (SAH EXP_COVID ; n = 25) and (SAH; n = 27). Patients with diagnostic criteria for arterial hypertension as proposed by the Brazilian Guidelines for Arterial Hypertension were included (Barroso et al. 2021 ), patients should have been receiving optimized drug therapy without modification for at least 3 months, aged between 40 and 75 years of both sexes. Patients who were exposed to COVID-19 but exhibited mild symptoms of the disease and did not require hospitalization were included. Diagnostic confirmation of virus infection was through Reverse Transcription - Polymerase Chain Reaction (RT-PCR) or antigen testing, with evaluation performed between 6 to 18 months after infection. Participants were excluded if they presented any neurological, neurodegenerative, or dementing diseases such as Parkinson's disease, Alzheimer's disease, vascular dementia, or stroke; presenting physical or cognitive limitations that would affect the assessments; having a Mini-Mental State Examination (MMSE) score below the expected value for age and education level; and being pregnant. Assessments All data were collected in the afternoon to avoid diurnal variation. Participants were asked to abstain from tobacco, alcohol, caffeine, and stimulant foods for 12 hours before the assessment, as well as refrain from physical activities in the last 24 hours prior to the tests. This information was confirmed by self-report upon the patient's arrival at each visit. Laboratory climatic conditions were controlled during assessments. The ambient temperature was maintained at 25°C. A quiet environment was also ensured. Cognitive performance The patients were evaluated by a neurologist who administered a battery of cognitive tests to assess attention, memory, executive dysfunction, inhibitory control, and mood symptoms. The tests included: MMSE, screening for dementia syndromes, with a brief 30-point questionnaire covering various areas such as orientation, attention and calculation, language recall, registration, and execution of commands (Molloy and Standish 1997 ); Trail Making Test A and B that evaluates through the time (in seconds) required to connect numbered circles in order, the ability of motor speed and mental flexibility (Gaudino et al. 1995 ); Teste de Stroop Victoria that evaluates attention and inhibitory control, assessed by the time (in seconds) taken to correctly read a card based on words and colors (MacLeod 1991 ); Rey Auditory Verbal Learning Test (RAVLT) that evaluates memory parameters such as learning indices and recall indices after attempting to memorize a sequence of words from a list (Kaplan et al. 2001 ); Semantic Fluency Test, performed by recording the maximum number of different animal species that the individual could report within a one-minute period (Yamasaki et al. 2023 ); Hospital Anxiety and Depression Scale (HADS), used to quantify mood symptoms. (Pais-Ribeiro et al. 2007 ; Zigmond and Snaith 1983 ). Endothelial function A trained researcher assessed parameters of endothelial function following the guidelines of a standardized protocol developed by expert consensus using the FMD technique. (Thijssen et al. 2019 ) Based on this technique, through the analysis of brachial artery dilation following an increase in artery blood flow velocity, we can evaluate vascular endothelial function mediated by nitric oxide availability. The patient was accommodated in a quiet and dark environment for a period of 10 to 15 minutes before the assessment. FMD was examined in all patients' right brachial artery. Longitudinal images of the brachial artery were obtained using high-resolution B-mode ultrasound (LOGIQ R7, GE Healthcare, Chicago, USA) with a 9 MHz multifrequency linear-array transducer probe. Doppler flow signal were corrected at a constant insonation angle of 60° throughout the procedure. In the supine position, the patient maintained the right arm abducted 90° in the frontal plane, with a blood pressure cuff placed on the forearm right after the antecubital fossa. Subsequently, the diameter of the brachial artery and blood flow velocity were continuously recorded for 9 minutes using an ultrasound. At the initial minute, the baseline diameter of the artery was assessed. Afterward, the cuff was inflated for 5 minutes to a supramaximal pressure (50 mmHg above the patient's systolic blood pressure), followed by 3 minutes of cuff deflation. The artery's diameter and blood flow velocity images remained continuously recorded throughout the process for subsequent analysis. Image analyses were performed by a single blinded evaluator (PILR) using edge-detection software (Cardiovascular Suite, FMD studio, QUIPU Srl, Pisa, Italy), cleared by the Food and Drug Administration (FDA). The main variable studied was FMD%, which corresponds to the percentage increase in artery diameter after occlusion relative to baseline values: FMD (%) = [(peak diameter - baseline diameter) / baseline diameter] * 100. Statistical analysis After data extraction, descriptive and analytical statistical treatment was conducted. The SigmaPlot 11.0 software (Systat, USA, 2011) was used for statistical analysis. Categorical variables were described in absolute values (n) and relative (%) frequencies, and Fisher's Exact Test was used for comparison between groups. The Kolmogorov-Smirnov Test was used to evaluate the distribution of data. Once the assumptions of normality were violated, the median and interquartile range (IQR) were used to describe continuous quantitative variables. The Mann-Whitney Test was used to compare medians between groups, and Spearman's non-parametric correlation was used to evaluate the relationship between FMD% and cognitive performance scores. A significance level of 5% was adopted. Results A total of 78 patients were contacted, and 52 were considered eligible. All eligible patients were included in the study, and their results were analyzed (Fig. 1 ). Of the 52 included patients, 51.92% (n = 27) had a history of COVID-19 infection 6 to 18 months prior to data collection. Female predominance was observed (76.9%; n = 40), with no difference between groups (p = 0.63). The median age was 54 years (IQR 14) for the SAH group and 58 years (IQR 12) for the SAH EXP_COVID group, with no statistical difference between the studied groups (p = 0.10). The median years of education were the same across evaluated groups (12 years). Additionally, no differences were observed in the prevalence of risk factors (smoking, obesity, and diabetes) or in the practice of physical activity (Table 1 ). Table 1 Sociodemographic Characterization of Patients with Systemic Arterial Hypertension Associated or Not with COVID-19 Exposure (n = 52) Total (n) SAH (n = 25; 48.1%) SAH EXP_COVID (n = 27; 51.9%) p value Sex Female; n (%) 40 18 (72) 22 (81) 0.630 1 Male; n (%) 12 7 (28) 5 (18) Age; median (IQR) 52 54 (14) 58 (12) 0.103 2 Education level Elementary Education; n (%) 12 7 (28) 5 (19) 0.171 1 High School Education; n (%) 24 15 (60) 9 (33) Higher Education; n (%) 16 3 (12) 13 (48) Years of Study; median (IQR) 12 (3) 12 (5) 0.060 2 Smoking No; n (%) 51 24 (96) 27 (100) 0.969 1 Yes; n (%) 1 1 (4) 0 (0) Diabetes Mellitus No; n (%) 46 24 (96) 22 (81) 0.229 1 Yes; n (%) 6 1 (4) 5 (18) Physical activity No; n (%) 38 18 (72) 20 (74) 1.000 1 Yes; n (%) 14 7 (28) 7 (26) Obesity No, n (%) 19 10 (40) 9 (33) 0.618 1 Yes; n (%) 33 15 (60) 18 (67) BMI; median (IQR) 31.6 (8.2) 32.8 (6.8) 0.899 2 1 Exact Fisher test ; 2 Mann Whitney test . No difference was observed in baseline diameter and FMD% between the studied groups (p = 0.52 and p = 0.68): for the SAH group, the median baseline diameter was 4.2 (IQR 0.8) and FMD% was 6.7 (IQR 6.1), and for the SAH EXP_COVID group, the baseline diameter was 4.1 (IQR 0.9) and FMD% was 5.4 (IQR 7.6) (Fig. 2 ). Of the 27 patients who were exposed to COVID-19, 62.9% (n = 17) reported cognitive complaints. However, no difference was observed in participants' performance on the tests conducted when comparing the two groups (Table 2 ). Table 2 Comparison of cognitive test performance Variable COVID-19 p value No Yes Learning index (RAVLT) 14 (8) 16 (6) 0.50 Delayed recall index (RAVLT) 7 (4) 8 (4) 0.89 Proactive interference index (RAVLT) 0.80 (0.5) 0.75 (0.54) 0.47 Retroactive interference index (RAVLT) 0.72 (0.28) 0.75(0.21) 0.64 Trail making test A 27.6 (12) 35.9 (20) 0.20 Trail making test B 82.5 (41.5) 75.9 (46.7) 0.66 TTB-A 54.7 (40.9) 42.3 (45.7) 0.47 Stroop test 31.8 (7.9) 29.7 (10.7) 0.83 Verbal fluency 19 (8) 19 (7) 0.54 HADS-A 7 (5) 9 (6) 0.23 HADS-D 8 (6) 6 (5) 0.39 The Mann-Whitney Test was used to compare medians between groups. Data presented in median and interquartile range. RAVLT: Rey auditory verbal learning Test. TTB-A: Time to complete Test B minus time to complete Test A. HADS-A: Anxiety scale. HADS-D: Depression scale. When comparing only participants with a history of COVID-19 exposure with and without cognitive complaints, no differences were observed in the tests (Table 3 ). Table 3 Comparison of cognitive test performance and endothelial function between patients who were infected with cognitive complaints or not Variable COVID-19 with cognitive complaint p value No Yes Learning index (RAVLT) 14.5 (9.5) 16.0 (5.0) 0.180 Delayed recall index (RAVLT) 5.5 (3.75) 9.0 (4.50) 0.054 Proactive interference index (RAVLT) 0.70 (0.28) 0.75 (0.66) 0.616 Retroactive interference index (RAVLT) 0.67 (0.11) 0.81 (0.21) 0.232 Trail making test A 36.3 (14.9) 35.9 (24) 0.978 Trail making test B 88.6 (55.7) 70.9 (50.3) 0.536 TTB-A 50.3 (52.3) 38.0 (48.1) 0.592 Stroop test 28.5 (5.9) 30.1 (13.9) 0.765 Verbal fluency 19 (6.5) 19 (6.5) 1.000 HADS-A 9.5 (6.2) 8.5 (6.5) 0.977 HADS-D 6.0 (2.7) 6.5 (5.7) 0.596 FMD% 7.0 (8.3) 5.4 (6.7) 0.458 The Mann-Whitney Test was used to compare medians between groups. Data presented in median and interquartile range. RAVLT: Rey auditory verbal learning Test. TTB-A: Time to complete Test B minus time to complete Test A. HADS-A: Anxiety scale. HADS-D: Depression scale. FMD%: Flow-mediated dilation percentage. In the analysis of the relationship between cognitive performance tests and FMD%, no relationship was observed between overall FMD% or FMD% with and without COVID-19 exposure and cognitive tests. Therefore, no regression model was used (Table 4 ). Table 4 Correlation between cognitive performance tests and FMD%, stratified by group Variable FMD% (total) FMD% (COVID-19 negative) FMD% (COVID-19 positive) Learning index (RAVLT) 0.170 (0.243) 0.245 (0.238) 0.134 (0.531) Delayed recall index (RAVLT) 0.205 (0.157) 0.245 (0.239) 0.180 (0.399) Proactive interference index (RAVLT) 0.057 (0.699) -0.013 (0.951) 0.061 (0.777) Retroactive interference index (RAVLT) 0.115 (0.431) 0.123 (0.557) 0.124 (0.564) Trail making test A -0.238 (0.099) -0.205 (0.325) -0.186 (0.382) Trail making test B 0.042 (0.793) -0.108 (0.632) 0.228 (0.346) TTB-A 0.160 (0.318) -0.012 (0.960) 0.330 (0.168) Stroop test -0.194 (0.181 -0.008 (0.999) -0.268 (0.205) Verbal fluency 0.146 (0.317) -0.071 (0.736) 0.353 (0.090) HADS-A -0.067 (0.652) -0.064 (0.763) -0.110 (0.618) HADS-D -0.070 (0.637) -0.041 (0.844) -0.091 (0.681) Spearman correlation test. Presented in r-value (p-value). RAVLT: Rey auditory verbal learning Test. TTB-A: Time to complete Test B minus time to complete Test A. HADS-A: Anxiety scale. HADS-D: Depression scale. FMD%: Flow-mediated dilation percentage. Discussion This study evaluates the potential consequences of exposure to SARS-CoV-2 infection, characterized by mild symptoms and no need for hospitalization, on the cognitive and endothelial systems of patients with SAH. It also investigates whether there is any relationship between possible cognitive impairment and the presence of endothelial dysfunction in this population. Regarding the initial hypothesis, no difference was observed between the groups of hypertensive patients with and without exposure to mild COVID-19 in cognitive assessments and vascular endothelial function. Additionally, no relationship was observed between cognitive performance and changes in endothelial function measured through the FMD technique. A meta-analysis conducted in 2022 showed that impaired endothelial function may be observed in convalescent patients with COVID-19 for a longer period, especially when residual clinical manifestations persist. (Ambrosino et al. 2022 ) It is possible that the mild magnitude of the infection, with the absence of severe and chronic symptoms, may be unable to cause persistent endothelial damage. A cohort study evaluating patients with COVID-19 observed the development of endothelial dysfunction in this population. This dysfunction progressively improved over six months. However, endothelial dysfunction persisted for more than six months compared to healthy control individuals. (Oikonomou et al. 2022 ) It is possible that in the current study, this persistent alteration was not observed because both groups consisted of patients with SAH. SAH may have been such an important risk factor for the presence of endothelial dysfunction in both groups that it may have masked the effect of the injury caused by the virus. Additionally, the six-month cutoff point may be suggested as a limit for the persistence of endothelial damage in infected patients. In the present study, the evaluation was performed on average 13 months after virus exposure, further increasing the chance of possible recovery from COVID-induced vascular damage. SAH may have been such a significant risk factor for the presence of endothelial dysfunction in both groups that it may have masked the effect of the injury caused by the virus. Additionally, the six-month cutoff point may be suggested as a limit for the persistence of endothelial damage in infected patients. In the present study, the evaluation was performed on average 13 months after virus exposure, further increasing the chance of possible recovery from COVID-induced vascular damage. In the literature, among all COVID-19-infected patients, approximately 22% reported persistent cognitive complaints. (Ceban et al. 2022 ) However, this study observed a percentage of 62.9% of persistent cognitive complaints among hypertensive patients with previous exposure to COVID-19. There are no studies in the literature that explore with more precision the prevalence of cognitive symptoms in hypertensive individuals affected by COVID-19. Although a higher percentage of cognitive complaints was found in hypertensive patients exposed to the virus, this did not represent an objective difference in cognitive tests. A complaint of cognitive performance change can be quite subjective, and this perception may be related to a previous period closer to exposure to the infection or to a state of increased sensitivity to this complaint in patients with social anxiety. (Alvi et al. 2022 ; Chollet and Leger 2023 ). A meta-analysis conducted during the pandemic, which evaluated 2,049 people, including a group of post-infection patients (up to seven months after exposure) who had lower cognition compared to the control group (mean difference = -0.94), using the MoCA score. (Crivelli et al. 2022 ) However, in this study, no difference was observed between the groups in all cognitive assessments. However, patients were evaluated for a longer period from the time of infection exposure (an average of 13 months). Perhaps six to seven months after the initial exposure could be the cutoff point for the persistence of cognitive symptoms caused by the virus. Beyond this period, cognitive sequelae may have been minimized by the aspect of a self-limiting disease. It is well studied the relationship between vascular endothelial function and cognitive impairments. Most studies show a relationship indicating that worse endothelial function correlates with poorer cognitive status. (Naiberg et al. 2016 ; Shabani et al. 2023 ) This relationship is suggested due to presence of tissue hypoperfusion and chronic local inflammation. (Naiberg et al. 2016 ; Shabani et al. 2023 ) However, other studies that evaluated this correlation only managed to find a relationship after an intervention, for example, with physical exercise. (Saleem et al. 2019 ) However, few studies assess this relationship in the context of COVID-19. (Shabani et al. 2023 ) In the present study, we did not observe a relationship between these two parameters. It is possible that we did not find differences between the groups studied, because the endothelial lesions caused by mild infection may not be of sufficient magnitude to produce clinical cognitive alterations. The evaluation of patients with mild symptoms of COVID-19 was important for this study in order to understand the relationship between virus exposure and chronic cognitive and endothelial symptoms. It is known that in patients who undergo hospitalization, several other factors can interfere and cause tissue or brain damage. (Zhao et al. 2023 ; Chollet and Leger 2023 ) These factors include severe tissue hypoxia, post-traumatic stress, intubation, renal or hepatic dysfunction, metabolic disorders, or even the use of multiple high-dose medications. The main limitation of the study is related to the confirmation of previous exposure to the virus infection. The group that confirmed viral infection did so through the results of serological or molecular diagnostic techniques; however, the control group consisted of patients who did not report exposure to infection, i.e. , a group selected by self-reporting. It is known that many SARS-CoV-2 infections can be asymptomatic. Some patients in the "unexposed" group may have had asymptomatic infections, received false-negative test results, or simply did not undergo diagnostic tests appropriately. It was not possible to take into account the influence of vaccination on the presence or absence of symptoms. Evaluating only the mild form of the disease helps to reduce the influence of vaccination on interfering with the results since the main goal of vaccination is to prevent severe forms of the disease. (Zhao et al. 2023 ) It was not possible to stratify the evaluated population by the type and characteristics of the vaccine due to the difficulty in obtaining this information. Currently, the impact of vaccines on cognitive deficits remains unknown. (Zhao et al. 2023 ). In conclusion, for individuals with SAH experiencing mild forms of COVID-19, after a period of six to eighteen months, no difference was observed in cognitive performance and endothelial function compared to hypertensive individuals not exposed to the virus. Declarations Author contribution V.R.N and A.F.D.A were the project coordinators and were responsible for the implementation and design of the study. Material preparation and data collection were performed by A. A.F, A. B. C., E.C.M.C, M.S.S., A.M.L.S, G.G.L., F.M.N.A.D Data analysis was performed by P.I.L.R. and A.A.F. . The first draft of the manuscript was written by P.I.L. and L.C.B . All authors were responsible for reviewing the manuscript. All authors contributed intellectually to this manuscript and approved the content of the manuscript. Conflict of interest statement The authors declare that they have no competing interests. Patient consent statement All participants signed an informed consent before inclusion in the study. Permission to reproduce material from other sources None. Clinical trial registration None. Data availability statement If clarification is needed, readers can contact the corresponding author to share the data. Funding statement This study was funded by Coordenação de Aperfeiçoamento de Pessoal de Nível Superior – Brazil (CAPES, Post- graduate Program in Physiotherapy, grant: 001). 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Rev Bras Epidemiol 21. doi:10.1590/1980-549720180021.supl.1 Mancia Chairperson G, Kreutz Co-Chair R, Brunström M, Burnier M, Grassi G, Januszewicz A, Muiesan ML, Tsioufis K, Agabiti-Rosei E, Algharably EAE, Azizi M, Benetos A, Borghi C, Hitij JB, Cifkova R, Coca A, Cornelissen V, Cruickshank K, Cunha PG, Danser AHJ, de Pinho RM, Delles C, Dominiczak AF, Dorobantu M, Doumas M, Fernández-Alfonso MS, Halimi JM, Járai Z, Jelaković B, Jordan J, Kuznetsova T, Laurent S, Lovic D, Lurbe E, Mahfoud F, Manolis A, Miglinas M, Narkiewicz K, Niiranen T, Palatini P, Parati G, Pathak A, Persu A, Polonia J, Redon J, Sarafidis P, Schmieder R, Spronck B, Stabouli S, Stergiou G, Taddei S, Thomopoulos C, Tomaszewski M, Van de Borne P, Wanner C, Weber T, Williams B, Zhang ZY, Kjeldsen SE (2023) 2023 ESH Guidelines for the management of arterial hypertension The Task Force for the management of arterial hypertension of the European Society of Hypertension: Endorsed by the International Society of Hypertension (ISH) and the European Renal Association (ERA). J Hypertens 41(12):1874-2071. doi:10.1097/HJH.0000000000003480 Martins-Filho RK, Zotin MC, Rodrigues G, Pontes-Neto O (2020) Biomarkers Related to Endothelial Dysfunction and Vascular Cognitive Impairment: A Systematic Review. Dement Geriatr Cogn Disord 49(4):365-374. doi:10.1159/000510053 Molloy DW, Standish TI (1997) A guide to the standardized Mini-Mental State Examination. Int Psychogeriatr 9 Suppl 1:87-94 discussion 143-150. doi:10.1017/s1041610297004754 Naiberg MR, Newton DF, Goldstein BI (2016) Flow-Mediated Dilation and Neurocognition: Systematic Review and Future Directions. Psychosom Med 78(2):192-207. doi:10.1097/PSY.0000000000000266 Nalbandian A, Sehgal K, Gupta A, Madhavan MV, McGroder C, Stevens JS, Cook JR, Nordvig AS, Shalev D, Sehrawat TS, Ahluwalia N, Bikdeli B, Dietz D, Der-Nigoghossian C, Liyanage-Don N, Rosner GF, Bernstein EJ, Mohan S, Beckley AA, Seres DS, Choueiri TK, Uriel N, Ausiello JC, Accili D, Freedberg DE, Baldwin M, Schwartz A, Brodie D, Garcia CK, Elkind MSV, Connors JM, Bilezikian JP, Landry DW, Wan EY (2021) Post-acute COVID-19 syndrome. Nat Med 27(4):601-615. doi:10.1038/s41591-021-01283-z O'Brien JT, Erkinjuntti T, Reisberg B, Roman G, Sawada T, Pantoni L, Bowler JV, Ballard C, DeCarli C, Gorelick PB, Rockwood K, Burns A, Gauthier S, DeKosky ST (2003) Vascular cognitive impairment. Lancet Neurol 2(2):89-98. doi:10.1016/s1474-4422(03)00305-3 Oikonomou E, Souvaliotis N, Lampsas S, Siasos G, Poulakou G, Theofilis P, Papaioannou TG, Haidich AB, Tsaousi G, Ntousopoulos V, Sakka V, Charalambous G, Rapti V, Raftopoulou S, Syrigos K, Tsioufis C, Tousoulis D, Vavuranakis M (2022) Endothelial dysfunction in acute and long standing COVID-19: A prospective cohort study. Vascul Pharmacol 144:106975. doi:10.1016/j.vph.2022.106975. Okay G, Durdu B, Akkoyunlu Y, Bölükçü S, Kaçmaz AB, Sümbül B, Karakuş HD, Koç MM (2020) Evaluation of Clinical Features and Prognosis in COVID-19 Patients with Hypertension: A Single-center Retrospective Observational Study. Bezmialem Science 8(2):15-21. doi:10.14235/bas.galenos.2020.4978. Pais-Ribeiro J, Silva I, Ferreira T, Martins A, Meneses R, Baltar M (2007) Validation study of a Portuguese version of the Hospital Anxiety and Depression Scale. Psychol Health Med 12(2):225-235. doi:10.1080/13548500500524088. Puddu P, Puddu GM, Zaca F, Muscari A (2000) Endothelial dysfunction in hypertension. Acta Cardiol 55(4):221-232. doi:10.2143/AC.55.4.2005744 Ruan Q, Yang K, Wang W, Jiang L, Song J (2020) Clinical predictors of mortality due to COVID-19 based on an analysis of data of 150 patients from Wuhan, China. Intensive Care Med. doi:10.1007/s00134-020-05991-x Saleem M, Herrmann N, Dinoff A, Mazereeuw G, Oh PI, Goldstein BI, Kiss A, Shammi P, Lanctôt KL (2019) Association between endothelial function and cognitive performance in patients with coronary artery disease during cardiac rehabilitation. Psychosom Med 81(2):184-191. doi:10.1097/PSY.0000000000000651. Shabani Z, Liu J, Su H (2023) Vascular dysfunctions contribute to the long-term cognitive deficits following COVID-19. Biol (Basel) 12(8):1106. doi:10.3390/biology12081106. Tabacof L, Tosto-Mancuso J, Wood J, Cortes M, Kontorovich A, McCarthy D, Rizk D, Rozanski G, Breyman E, Nasr L, Kellner C, Herrera JE, Putrino D (2022) Post-acute COVID-19 Syndrome Negatively Impacts Physical Function, Cognitive Function, Health-Related Quality of Life, and Participation. Am J Phys Med Rehabil 101(1):48-52. doi:10.1097/PHM.0000000000001910 Taquet M, Sillett R, Zhu L, Mendel J, Camplisson I, Dercon Q, Harrison PJ (2022) Neurological and psychiatric risk trajectories after SARS-CoV-2 infection: an analysis of 2-year retrospective cohort studies including 1 284 437 patients. Lancet Psychiatry 9(10):815-827. doi:10.1016/S2215-0366(22)00260-7 Thijssen DHJ, Bruno RM, van Mil ACCM, Holder SM, Faita F, Greyling A, Zock PL, Taddei S, Deanfield JE, Luscher T, Green DJ, Ghiadoni L (2019) Expert consensus and evidence-based recommendations for the assessment of flow-mediated dilation in humans. Eur Heart J 40(30):2534-2547. doi:10.1093/eurheartj/ehz350. Yamasaki T, Matsuo H, Ohara K (2023) Impact of semantic fluency on cognitive performance in aging adults: A 1-minute animal naming task. J Geriatr Psychol 32(4):256-264. doi:10.1016/j.jger.2023.05.009. Zhao S, Toniolo S, Hampshire A, Husain M (2023) Effects of COVID-19 on cognition and brain health. Trends Cogn Sci 27(11):1053-1067. doi:10.1016/j.tics.2023.08.008 Zhou F, Yu T, Du R, Fan G, Liu Y, Liu Z, Xiang J, Wang Y, Song B, Gu X, Guan L, Wei Y, Li H, Wu X, Xu J, Tu S, Zhang Y, Chen H, Cao B (2020) Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, China: a retrospective cohort study. Lancet 395(10229):1054-1062. doi:10.1016/S0140-6736(20)30566-3 Zigmond AS, Snaith RP (1983) The Hospital Anxiety and Depression Scale. Acta Psychiatr Scand 67(6):361-370. doi:10.1111/j.1600-0447.1983.tb09716.x. Additional Declarations No competing interests reported. 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(UPE)","correspondingAuthor":false,"prefix":"","firstName":"Paulo","middleName":"André Freire","lastName":"Magalhães","suffix":""},{"id":458288439,"identity":"ad5c54d5-4902-47d2-baa9-89b33602c3fb","order_by":11,"name":"Victor Ribeiro Neves","email":"","orcid":"","institution":"University of Pernambuco (UPE)","correspondingAuthor":false,"prefix":"","firstName":"Victor","middleName":"Ribeiro","lastName":"Neves","suffix":""}],"badges":[],"createdAt":"2024-11-19 22:08:07","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5486274/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5486274/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":85185081,"identity":"e69cb86b-4ff3-4ae9-a079-9f76a63ece43","added_by":"auto","created_at":"2025-06-23 08:04:39","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":58885,"visible":true,"origin":"","legend":"\u003cp\u003eFlowchart of study losses\u003c/p\u003e","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-5486274/v1/7921040f03e5a0f674e73658.jpeg"},{"id":85185083,"identity":"e3bc3f33-1b49-4cc1-9a19-ee72e21e434a","added_by":"auto","created_at":"2025-06-23 08:04:39","extension":"jpeg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":98398,"visible":true,"origin":"","legend":"\u003cp\u003eComparison of baseline and FMD% between the Studied Groups\u003c/p\u003e","description":"","filename":"floatimage2.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-5486274/v1/936b1c41ab03a66b34e896ed.jpeg"},{"id":96362755,"identity":"c31c98c0-efcb-4d69-9517-e010f1bd88e3","added_by":"auto","created_at":"2025-11-20 09:47:59","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1025814,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5486274/v1/5c580869-9426-4096-87ea-491351e389ed.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Cognition and vascular endothelial function in hypertensive individuals with and without a history of Covid-19: A Cross-Sectional Study","fulltext":[{"header":"Introduction","content":"\u003cp\u003eSystemic arterial hypertension (SAH) is an important risk factor for the development and progression of cardiovascular diseases. According to the World Health Organization (WHO), cardiovascular diseases affect approximately 1.28\u0026nbsp;billion adults worldwide, with a prevalence of approximately 30\u0026nbsp;million people in Brazil. (Barros et al. 2021; Malta et al. \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Mancia et al. 2023).\u003c/p\u003e \u003cp\u003eDuring the COVID-19 pandemic, it was observed that SAH was the most prevalent chronic disease among those infected by SARS-CoV-2, affecting approximately 30% of the infected individuals. (Gallo et al. \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) Patients with SAH also developed more severe forms of SARS-CoV-2 and death rates compared with infected patients without SAH. (Okay et al. \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Zhou et al. \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) The acute infection caused by the SARS-CoV-2 virus is accompanied by an aggressive inflammatory response known as a \"cytokine storm\u0026rdquo;. (Iba et al. \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Ruan et al. \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), which favors the damage of arterial endothelial tissue previously observed in the literature. (Libby and L\u0026uuml;scher \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Loo et al. \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) In addition, the impairment in the endothelial function caused by SARS-CoV-2 may lead to circulatory disorders such as thrombosis and local tissue damage. (Iba et al. \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Libby and L\u0026uuml;scher \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Ambrosino et al. \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAmong the main symptoms of COVID-19, a decrease in cognitive performance has been well documented in the literature including the period of recovery from the virus infection. (Tabacof et al. \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) Known as post-COVID-19 syndrome, the remaining symptoms may last up to two years after the initial infection. (Kamal et al. \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Nalbandian et al. \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Taquet et al. \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Zhao et al. \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) A recent systematic review revealed a notable prevalence of 22% individuals who mentioned cognitive symptoms in post-COVID-19. (Ceban et al. \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe presence of cognitive symptoms in COVID-19 may be exacerbated in the presence of SAH, which is the greatest risk factor for cerebrovascular diseases. (O'Brien et al. \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2003\u003c/span\u003e; Iadecola and Gottesman \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) SAH gradually and progressively causes vascular endothelial dysfunction (Iadecola and Gottesman \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), which is related to decreased nitric oxide bioavailability, impairing vasodilation and stimulating the premature development of diseases that affect cognition. (Konukoglu and Uzun \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Puddu et al. \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2000\u003c/span\u003e) Vascular endothelial function assessed by flow-mediated dilation (FMD) is associated with impaired cognition in patients with cerebrovascular diseases. (Naiberg et al. \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2016\u003c/span\u003e) The mechanisms underlying this association suggest a reduced cerebral blood flow and loss of cerebral vasoreactivity. (Martins-Filho et al. \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAlthough the clear coexistence of COVID-19 and SAH creates a poorer prognosis for patients infected with SARS-CoV-2 virus, the underlying mechanisms of it remain unknown. Along this line, impaired vascular endothelial function and cognitive performance seem to be promising mechanisms present in both conditions but this is still not properly tested in the literature. Therefore, this study aimed to compare and correlate the effect of COVID-19 exposure in hypertensive patients on cognitive performance and vascular endothelial function. We hypothesize that hypertensive patients after six months of diagnosis of COVID-19, should exhibit greater cognitive impairment and worse vascular endothelial function when compared to the unexposed group. Additionally, worse endothelial function may be associated with poorer cognitive performance.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003eBetween March and September 2023, patients with arterial hypertension who contracted COVID-19 (SAH\u003csub\u003eEXP_COVID\u003c/sub\u003e) or not (SAH) were evaluated at the University of Pernambuco (UPE), located in the city of Petrolina-PE (Brazil). Patient selection was conducted after the study was announced on radio stations and digital media platforms to recruit research participants. All interested individuals underwent a screening process to confirm eligibility criteria.\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eEthical procedures\u003c/h2\u003e \u003cp\u003eThe study was approved by the Ethics Committee of UPE, under the following protocol number CAAE: 66973322.0.0000.5191. All participants signed the Informed Consent Form (ICF).\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eParticipants\u003c/h3\u003e\n\u003cp\u003eThis study relied on a convenience sample, where researchers carefully delineated the profile of participants to be included. The sample size was calculated using GPower 3.1.9.4 software, with significance levels α set at 0.05 and β fixed at 0.80, resulting in a total of 42 patients. Additionally, an estimated dropout rate of 20% was considered during the study planning, totaling 52 patients distributed between the groups (SAH\u003csub\u003eEXP_COVID\u003c/sub\u003e; n\u0026thinsp;=\u0026thinsp;25) and (SAH; n\u0026thinsp;=\u0026thinsp;27).\u003c/p\u003e \u003cp\u003e Patients with diagnostic criteria for arterial hypertension as proposed by the Brazilian Guidelines for Arterial Hypertension were included (Barroso et al. \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), patients should have been receiving optimized drug therapy without modification for at least 3 months, aged between 40 and 75 years of both sexes. Patients who were exposed to COVID-19 but exhibited mild symptoms of the disease and did not require hospitalization were included. Diagnostic confirmation of virus infection was through Reverse Transcription - Polymerase Chain Reaction (RT-PCR) or antigen testing, with evaluation performed between 6 to 18 months after infection.\u003c/p\u003e \u003cp\u003eParticipants were excluded if they presented any neurological, neurodegenerative, or dementing diseases such as Parkinson's disease, Alzheimer's disease, vascular dementia, or stroke; presenting physical or cognitive limitations that would affect the assessments; having a Mini-Mental State Examination (MMSE) score below the expected value for age and education level; and being pregnant.\u003c/p\u003e\n\u003ch3\u003eAssessments\u003c/h3\u003e\n\u003cp\u003eAll data were collected in the afternoon to avoid diurnal variation. Participants were asked to abstain from tobacco, alcohol, caffeine, and stimulant foods for 12 hours before the assessment, as well as refrain from physical activities in the last 24 hours prior to the tests. This information was confirmed by self-report upon the patient's arrival at each visit. Laboratory climatic conditions were controlled during assessments. The ambient temperature was maintained at 25\u0026deg;C. A quiet environment was also ensured.\u003c/p\u003e\n\u003ch3\u003eCognitive performance\u003c/h3\u003e\n\u003cp\u003eThe patients were evaluated by a neurologist who administered a battery of cognitive tests to assess attention, memory, executive dysfunction, inhibitory control, and mood symptoms. The tests included: MMSE, screening for dementia syndromes, with a brief 30-point questionnaire covering various areas such as orientation, attention and calculation, language recall, registration, and execution of commands (Molloy and Standish \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e1997\u003c/span\u003e); Trail Making Test A and B that evaluates through the time (in seconds) required to connect numbered circles in order, the ability of motor speed and mental flexibility (Gaudino et al. \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e1995\u003c/span\u003e); Teste de Stroop Victoria that evaluates attention and inhibitory control, assessed by the time (in seconds) taken to correctly read a card based on words and colors (MacLeod \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e1991\u003c/span\u003e); Rey Auditory Verbal Learning Test (RAVLT) that evaluates memory parameters such as learning indices and recall indices after attempting to memorize a sequence of words from a list (Kaplan et al. \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2001\u003c/span\u003e); Semantic Fluency Test, performed by recording the maximum number of different animal species that the individual could report within a one-minute period (Yamasaki et al. \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2023\u003c/span\u003e); Hospital Anxiety and Depression Scale (HADS), used to quantify mood symptoms. (Pais-Ribeiro et al. \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Zigmond and Snaith \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e1983\u003c/span\u003e).\u003c/p\u003e\n\u003ch3\u003eEndothelial function\u003c/h3\u003e\n\u003cp\u003e A trained researcher assessed parameters of endothelial function following the guidelines of a standardized protocol developed by expert consensus using the FMD technique. (Thijssen et al. \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) Based on this technique, through the analysis of brachial artery dilation following an increase in artery blood flow velocity, we can evaluate vascular endothelial function mediated by nitric oxide availability.\u003c/p\u003e \u003cp\u003eThe patient was accommodated in a quiet and dark environment for a period of 10 to 15 minutes before the assessment. FMD was examined in all patients' right brachial artery. Longitudinal images of the brachial artery were obtained using high-resolution B-mode ultrasound (LOGIQ R7, GE Healthcare, Chicago, USA) with a 9 MHz multifrequency linear-array transducer probe. Doppler flow signal were corrected at a constant insonation angle of 60\u0026deg; throughout the procedure.\u003c/p\u003e \u003cp\u003eIn the supine position, the patient maintained the right arm abducted 90\u0026deg; in the frontal plane, with a blood pressure cuff placed on the forearm right after the antecubital fossa. Subsequently, the diameter of the brachial artery and blood flow velocity were continuously recorded for 9 minutes using an ultrasound. At the initial minute, the baseline diameter of the artery was assessed. Afterward, the cuff was inflated for 5 minutes to a supramaximal pressure (50 mmHg above the patient's systolic blood pressure), followed by 3 minutes of cuff deflation. The artery's diameter and blood flow velocity images remained continuously recorded throughout the process for subsequent analysis.\u003c/p\u003e \u003cp\u003eImage analyses were performed by a single blinded evaluator (PILR) using edge-detection software (Cardiovascular Suite, FMD studio, QUIPU Srl, Pisa, Italy), cleared by the Food and Drug Administration (FDA). The main variable studied was FMD%, which corresponds to the percentage increase in artery diameter after occlusion relative to baseline values: FMD (%) = [(peak diameter - baseline diameter) / baseline diameter] * 100.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eAfter data extraction, descriptive and analytical statistical treatment was conducted. The SigmaPlot 11.0 software (Systat, USA, 2011) was used for statistical analysis. Categorical variables were described in absolute values (n) and relative (%) frequencies, and Fisher's Exact Test was used for comparison between groups. The Kolmogorov-Smirnov Test was used to evaluate the distribution of data. Once the assumptions of normality were violated, the median and interquartile range (IQR) were used to describe continuous quantitative variables. The Mann-Whitney Test was used to compare medians between groups, and Spearman's non-parametric correlation was used to evaluate the relationship between FMD% and cognitive performance scores. A significance level of 5% was adopted.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eA total of 78 patients were contacted, and 52 were considered eligible. All eligible patients were included in the study, and their results were analyzed (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eOf the 52 included patients, 51.92% (n\u0026thinsp;=\u0026thinsp;27) had a history of COVID-19 infection 6 to 18 months prior to data collection. Female predominance was observed (76.9%; n\u0026thinsp;=\u0026thinsp;40), with no difference between groups (p\u0026thinsp;=\u0026thinsp;0.63). The median age was 54 years (IQR 14) for the SAH group and 58 years (IQR 12) for the SAH\u003csub\u003eEXP_COVID\u003c/sub\u003e group, with no statistical difference between the studied groups (p\u0026thinsp;=\u0026thinsp;0.10). The median years of education were the same across evaluated groups (12 years). Additionally, no differences were observed in the prevalence of risk factors (smoking, obesity, and diabetes) or in the practice of physical activity (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSociodemographic Characterization of Patients with Systemic Arterial Hypertension Associated or Not with COVID-19 Exposure (n\u0026thinsp;=\u0026thinsp;52)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTotal (n)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSAH\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;25; 48.1%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSAH\u003csub\u003eEXP_COVID\u003c/sub\u003e (n\u0026thinsp;=\u0026thinsp;27; 51.9%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003eSex\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale; n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18 (72)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e22 (81)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.630\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale; n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7 (28)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5 (18)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge; median (IQR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e54 (14)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e58 (12)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.103\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEducation level\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eElementary Education; n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7 (28)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5 (19)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0.171\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh School Education; n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15 (60)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9 (33)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigher Education; n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3 (12)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13 (48)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYears of Study; median (IQR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12 (3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12 (5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.060\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSmoking\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo; n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e24 (96)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e27 (100)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.969\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes; n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDiabetes Mellitus\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo; n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e24 (96)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e22 (81)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.229\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes; n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5 (18)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePhysical activity\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo; n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18 (72)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e20 (74)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e1.000\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes; n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7 (28)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7 (26)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eObesity\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10 (40)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9 (33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.618\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes; n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15 (60)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e18 (67)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI; median (IQR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e31.6 (8.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e32.8 (6.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.899\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003csup\u003e1\u003c/sup\u003e \u003cem\u003eExact Fisher test\u003c/em\u003e; \u003csup\u003e2\u003c/sup\u003e \u003cem\u003eMann Whitney test\u003c/em\u003e.\u003c/p\u003e \u003cp\u003eNo difference was observed in baseline diameter and FMD% between the studied groups (p\u0026thinsp;=\u0026thinsp;0.52 and p\u0026thinsp;=\u0026thinsp;0.68): for the SAH group, the median baseline diameter was 4.2 (IQR 0.8) and FMD% was 6.7 (IQR 6.1), and for the SAH\u003csub\u003eEXP_COVID\u003c/sub\u003e group, the baseline diameter was 4.1 (IQR 0.9) and FMD% was 5.4 (IQR 7.6) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eOf the 27 patients who were exposed to COVID-19, 62.9% (n\u0026thinsp;=\u0026thinsp;17) reported cognitive complaints. However, no difference was observed in participants' performance on the tests conducted when comparing the two groups (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eComparison of cognitive test performance\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eCOVID-19\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLearning index (RAVLT)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14 (8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16 (6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.50\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDelayed recall index (RAVLT)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7 (4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8 (4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.89\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProactive interference index (RAVLT)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.80 (0.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.75 (0.54)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.47\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRetroactive interference index (RAVLT)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.72 (0.28)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.75(0.21)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.64\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTrail making test A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e27.6 (12)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e35.9 (20)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.20\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTrail making test B\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e82.5 (41.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e75.9 (46.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.66\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTTB-A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e54.7 (40.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e42.3 (45.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.47\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStroop test\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e31.8 (7.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e29.7 (10.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.83\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVerbal fluency\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e19 (8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19 (7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.54\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHADS-A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7 (5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9 (6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.23\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHADS-D\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8 (6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6 (5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.39\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe Mann-Whitney Test was used to compare medians between groups. Data presented in median and interquartile range. RAVLT: Rey auditory verbal learning Test. TTB-A: Time to complete Test B minus time to complete Test A. HADS-A: Anxiety scale. HADS-D: Depression scale.\u003c/p\u003e \u003cp\u003eWhen comparing only participants with a history of COVID-19 exposure with and without cognitive complaints, no differences were observed in the tests (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eComparison of cognitive test performance and endothelial function between patients who were infected with cognitive complaints or not\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eCOVID-19 with cognitive complaint\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLearning index (RAVLT)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e14.5 (9.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e16.0 (5.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.180\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDelayed recall index (RAVLT)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e5.5 (3.75)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9.0 (4.50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.054\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProactive interference index (RAVLT)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e0.70 (0.28)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.75 (0.66)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.616\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRetroactive interference index (RAVLT)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e0.67 (0.11)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.81 (0.21)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.232\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTrail making test A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e36.3 (14.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e35.9 (24)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.978\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTrail making test B\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e88.6 (55.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e70.9 (50.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.536\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTTB-A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e50.3 (52.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e38.0 (48.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.592\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStroop test\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e28.5 (5.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e30.1 (13.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.765\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVerbal fluency\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e19 (6.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e19 (6.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHADS-A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e9.5 (6.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8.5 (6.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.977\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHADS-D\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e6.0 (2.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.5 (5.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.596\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eFMD%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.0 (8.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.4 (6.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.458\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe Mann-Whitney Test was used to compare medians between groups. Data presented in median and interquartile range. RAVLT: Rey auditory verbal learning Test. TTB-A: Time to complete Test B minus time to complete Test A. HADS-A: Anxiety scale. HADS-D: Depression scale. FMD%: Flow-mediated dilation percentage.\u003c/p\u003e \u003cp\u003eIn the analysis of the relationship between cognitive performance tests and FMD%, no relationship was observed between overall FMD% or FMD% with and without COVID-19 exposure and cognitive tests. Therefore, no regression model was used (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCorrelation between cognitive performance tests and FMD%, stratified by group\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFMD% (total)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFMD%\u003c/p\u003e \u003cp\u003e(COVID-19 negative)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eFMD%\u003c/p\u003e \u003cp\u003e(COVID-19 positive)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLearning index (RAVLT)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.170 (0.243)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.245 (0.238)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.134 (0.531)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDelayed recall index (RAVLT)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.205 (0.157)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.245 (0.239)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.180 (0.399)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProactive interference index (RAVLT)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.057 (0.699)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.013 (0.951)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.061 (0.777)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRetroactive interference index (RAVLT)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.115 (0.431)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.123 (0.557)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.124 (0.564)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTrail making test A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.238 (0.099)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.205 (0.325)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.186 (0.382)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTrail making test B\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.042 (0.793)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.108 (0.632)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.228 (0.346)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTTB-A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.160 (0.318)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.012 (0.960)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.330 (0.168)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStroop test\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.194 (0.181\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.008 (0.999)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.268 (0.205)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVerbal fluency\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.146 (0.317)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.071 (0.736)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.353 (0.090)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHADS-A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.067 (0.652)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.064 (0.763)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.110 (0.618)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHADS-D\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.070 (0.637)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.041 (0.844)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.091 (0.681)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eSpearman correlation test. Presented in r-value (p-value). RAVLT: Rey auditory verbal learning Test. TTB-A: Time to complete Test B minus time to complete Test A. HADS-A: Anxiety scale. HADS-D: Depression scale. FMD%: Flow-mediated dilation percentage.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study evaluates the potential consequences of exposure to SARS-CoV-2 infection, characterized by mild symptoms and no need for hospitalization, on the cognitive and endothelial systems of patients with SAH. It also investigates whether there is any relationship between possible cognitive impairment and the presence of endothelial dysfunction in this population.\u003c/p\u003e \u003cp\u003eRegarding the initial hypothesis, no difference was observed between the groups of hypertensive patients with and without exposure to mild COVID-19 in cognitive assessments and vascular endothelial function. Additionally, no relationship was observed between cognitive performance and changes in endothelial function measured through the FMD technique.\u003c/p\u003e \u003cp\u003eA meta-analysis conducted in 2022 showed that impaired endothelial function may be observed in convalescent patients with COVID-19 for a longer period, especially when residual clinical manifestations persist. (Ambrosino et al. \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) It is possible that the mild magnitude of the infection, with the absence of severe and chronic symptoms, may be unable to cause persistent endothelial damage.\u003c/p\u003e \u003cp\u003eA cohort study evaluating patients with COVID-19 observed the development of endothelial dysfunction in this population. This dysfunction progressively improved over six months. However, endothelial dysfunction persisted for more than six months compared to healthy control individuals. (Oikonomou et al. \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) It is possible that in the current study, this persistent alteration was not observed because both groups consisted of patients with SAH. SAH may have been such an important risk factor for the presence of endothelial dysfunction in both groups that it may have masked the effect of the injury caused by the virus. Additionally, the six-month cutoff point may be suggested as a limit for the persistence of endothelial damage in infected patients. In the present study, the evaluation was performed on average 13 months after virus exposure, further increasing the chance of possible recovery from COVID-induced vascular damage.\u003c/p\u003e \u003cp\u003eSAH may have been such a significant risk factor for the presence of endothelial dysfunction in both groups that it may have masked the effect of the injury caused by the virus. Additionally, the six-month cutoff point may be suggested as a limit for the persistence of endothelial damage in infected patients. In the present study, the evaluation was performed on average 13 months after virus exposure, further increasing the chance of possible recovery from COVID-induced vascular damage.\u003c/p\u003e \u003cp\u003eIn the literature, among all COVID-19-infected patients, approximately 22% reported persistent cognitive complaints. (Ceban et al. \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) However, this study observed a percentage of 62.9% of persistent cognitive complaints among hypertensive patients with previous exposure to COVID-19. There are no studies in the literature that explore with more precision the prevalence of cognitive symptoms in hypertensive individuals affected by COVID-19.\u003c/p\u003e \u003cp\u003eAlthough a higher percentage of cognitive complaints was found in hypertensive patients exposed to the virus, this did not represent an objective difference in cognitive tests. A complaint of cognitive performance change can be quite subjective, and this perception may be related to a previous period closer to exposure to the infection or to a state of increased sensitivity to this complaint in patients with social anxiety. (Alvi et al. \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Chollet and Leger \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eA meta-analysis conducted during the pandemic, which evaluated 2,049 people, including a group of post-infection patients (up to seven months after exposure) who had lower cognition compared to the control group (mean difference = -0.94), using the MoCA score. (Crivelli et al. \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) However, in this study, no difference was observed between the groups in all cognitive assessments. However, patients were evaluated for a longer period from the time of infection exposure (an average of 13 months). Perhaps six to seven months after the initial exposure could be the cutoff point for the persistence of cognitive symptoms caused by the virus. Beyond this period, cognitive sequelae may have been minimized by the aspect of a self-limiting disease.\u003c/p\u003e \u003cp\u003eIt is well studied the relationship between vascular endothelial function and cognitive impairments. Most studies show a relationship indicating that worse endothelial function correlates with poorer cognitive status. (Naiberg et al. \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Shabani et al. \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) This relationship is suggested due to presence of tissue hypoperfusion and chronic local inflammation. (Naiberg et al. \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Shabani et al. \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) However, other studies that evaluated this correlation only managed to find a relationship after an intervention, for example, with physical exercise. (Saleem et al. \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) However, few studies assess this relationship in the context of COVID-19. (Shabani et al. \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) In the present study, we did not observe a relationship between these two parameters. It is possible that we did not find differences between the groups studied, because the endothelial lesions caused by mild infection may not be of sufficient magnitude to produce clinical cognitive alterations.\u003c/p\u003e \u003cp\u003eThe evaluation of patients with mild symptoms of COVID-19 was important for this study in order to understand the relationship between virus exposure and chronic cognitive and endothelial symptoms. It is known that in patients who undergo hospitalization, several other factors can interfere and cause tissue or brain damage. (Zhao et al. \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Chollet and Leger \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) These factors include severe tissue hypoxia, post-traumatic stress, intubation, renal or hepatic dysfunction, metabolic disorders, or even the use of multiple high-dose medications.\u003c/p\u003e \u003cp\u003eThe main limitation of the study is related to the confirmation of previous exposure to the virus infection. The group that confirmed viral infection did so through the results of serological or molecular diagnostic techniques; however, the control group consisted of patients who did not report exposure to infection, \u003cem\u003ei.e.\u003c/em\u003e, a group selected by self-reporting. It is known that many SARS-CoV-2 infections can be asymptomatic. Some patients in the \"unexposed\" group may have had asymptomatic infections, received false-negative test results, or simply did not undergo diagnostic tests appropriately. It was not possible to take into account the influence of vaccination on the presence or absence of symptoms. Evaluating only the mild form of the disease helps to reduce the influence of vaccination on interfering with the results since the main goal of vaccination is to prevent severe forms of the disease. (Zhao et al. \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) It was not possible to stratify the evaluated population by the type and characteristics of the vaccine due to the difficulty in obtaining this information. Currently, the impact of vaccines on cognitive deficits remains unknown. (Zhao et al. \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn conclusion, for individuals with SAH experiencing mild forms of COVID-19, after a period of six to eighteen months, no difference was observed in cognitive performance and endothelial function compared to hypertensive individuals not exposed to the virus.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthor contribution\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eV.R.N \u0026nbsp; and A.F.D.A were the project coordinators and were responsible for the implementation and design of the study.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eMaterial preparation and data collection were performed by A. A.F, A. B. C., E.C.M.C, M.S.S., \u0026nbsp;A.M.L.S, G.G.L., F.M.N.A.D\u003c/p\u003e\n\u003cp\u003eData analysis was performed by P.I.L.R. and A.A.F. .\u003c/p\u003e\n\u003cp\u003eThe first draft of the manuscript was written by P.I.L. and L.C.B .\u003c/p\u003e\n\u003cp\u003eAll authors were responsible for reviewing the manuscript. All authors contributed intellectually to this manuscript and approved the content of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of interest statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePatient consent statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll participants signed an informed consent before inclusion in the study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePermission to reproduce material from other sources\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNone.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical trial registration\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNone.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIf clarification is needed, readers can contact the corresponding author to share the data.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was funded by Coordena\u0026ccedil;\u0026atilde;o de Aperfei\u0026ccedil;oamento de Pessoal de N\u0026iacute;vel Superior \u0026ndash; Brazil (CAPES, Post- graduate Program in Physiotherapy, grant: 001).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eOrcid\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eVictor Ribeiro Neves - https://orcid.org/0000-0002-3294-2700\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAlvi T, Kumar D, Tabak BA (2022) Social anxiety and behavioral assessments of social cognition: A systematic review. J Affect Disord 311:17-30. doi:10.1016/j.jad.2022.04.130.\u003c/li\u003e\n\u003cli\u003eAmbrosino P, Parrella P, Formisano R, Perrotta G, D\u0026apos;Anna SE, Mosella M, Papa A, Maniscalco M (2022) Cardiopulmonary Exercise Performance and Endothelial Function in Convalescent COVID-19 Patients. J Clin Med 11(5):1452. doi:10.3390/jcm11051452\u003c/li\u003e\n\u003cli\u003eBarroso WKS, Rodrigues CIS, Bortolotto LA, Mota-Gomes MA, Brand\u0026atilde;o AA, Feitosa ADM, Macahado CA, Poli-de-Figueiredo CE, Amodeo C, Mion J\u0026uacute;nior D, Barbosa ECD, Nobre F, Guimar\u0026atilde;es ICB, Vilela-Martin JF, Yugar-Toledo JC, Magalh\u0026atilde;es MEC, Neves MFT, Jardim PCBV, Miranda RD, P\u0026oacute;voa RMS, Fuchs SC, Alessi A, Lucena AJG, Avezum A, Sousa ALL, Pio-Abreu A, Sposito AC, Pierim AMG, Paiva AMG, Spinelli ACS, Nogueira AR, Dinamarco N, Eibel B, Forjaz CLM, Zanini CRO, Souza CB, Souza DSM, Nilson EAF, Costa EFA, Freitas EV, Duarte ER, Muxfeldt ES, Lima Junio EL, Campanha EMG, Cesarino EJ, Marquqes F, Argenta F, Consolim-Colombo FM, Baptista FS, Ameida FA, Borelli FAO, Fuchs FD, Plavnik FL, Salles GF, Feitosa GS, Silva GV, Guerra GM, Moreno Junior H, Finimundi HC, Back IC, Oliveira Filho JB, Gelemelli JR, Mill JG, Ribeiro JM, Lotaif LLAD, Costa LS, Magalh\u0026atilde;es LBNC, Drager LF, Martin LC, Scala LCN, Ameida MQ, Gowdak MMG, Klein MRST, Malachias MVB, Kuschnir MCC, Pinheiro ME,Borba MHE, Moreira Filho O, Passarelli Junior O, Coellho OR, Vitorino PVO, Ribeiro Junior RM, Esporcatte R, Franco R, Pedrosa R, Mulinari RA, Paula TB, Okawa RTP, Rosa RF, Amaral SL, Ferreira Filho SR, Kaiser SE, Jardim TSV, Guimar\u0026atilde;es V, Koch VH, Oigman W, Nadruz W (2021) Diretrizes Brasileiras de Hipertens\u0026atilde;o Arterial - 2020. 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Acta Psychiatr Scand 67(6):361-370. doi:10.1111/j.1600-0447.1983.tb09716.x.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"SARS-CoV-2, Endothelium, Cognition, Memory","lastPublishedDoi":"10.21203/rs.3.rs-5486274/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5486274/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003ePatients with systemic arterial hypertension (SAH) are at higher risk of developing a more severe course of SARS-CoV-2 viral infection, in addition to potentially developing lasting cognitive sequelae. Current literature provides evidence that the mechanism underlying the worse outcome of COVID-19 and the emergence of cognitive impairments in hypertensive individuals is endothelial dysfunction. Flow-mediated dilation (FMD) is a technique that has been used for several decades to assess endothelial function. The aim of the study was to assess the effect of COVID-19 exposure on the cognitive status and endothelial function of patients with SAH.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethodology: \u003c/strong\u003eA cross-sectional study compared cognitive status, assessed through neuropsychological tests, and endothelial function, assessed through FMD, in 52 patients diagnosed with SAH who were previously exposed or not to mild forms of COVID-19. Patients were allocated into two groups: SAH with COVID-19 exposure (SAH\u003csub\u003eEXP_COVID\u003c/sub\u003e) and SAH without COVID-19 (SAH). Assessment was documented between six months and eighteen months post-infection.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults: \u003c/strong\u003eNo difference in FMD% was observed between the studied groups (p=0.69): for the SAH group, FMD% was 6.7 and for the SAH\u003csub\u003eEXP_COVID\u003c/sub\u003e group, FMD% was 5.4. No differences in cognitive performance were observed when comparing the groups, nor was there a relationship between cognition and endothelial function.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion:\u003c/strong\u003e There was no difference in endothelial and cognitive function between hypertensive patients infected or not by the SARS-CoV-2 virus with the mild form of the disease.\u003c/p\u003e","manuscriptTitle":"Cognition and vascular endothelial function in hypertensive individuals with and without a history of Covid-19: A Cross-Sectional Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-06-23 08:04:34","doi":"10.21203/rs.3.rs-5486274/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"b5b68fb0-b972-4c95-ba85-39a82cd1bd88","owner":[],"postedDate":"June 23rd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-11-13T17:53:31+00:00","versionOfRecord":[],"versionCreatedAt":"2025-06-23 08:04:34","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-5486274","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5486274","identity":"rs-5486274","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}