Impact of CHADS-VA Score on COVID-19 Disease Related Outcomes

Impact of CHADS-VA Score on COVID-19 Disease Related Outcomes | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Impact of CHADS-VA Score on COVID-19 Disease Related Outcomes Gamze Yeter Arslan, Metin Okşul, Yusuf Ziya Şener, Serdar Söner, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6742800/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 29 Dec, 2025 Read the published version in BMC Cardiovascular Disorders → Version 1 posted 10 You are reading this latest preprint version Abstract Objective Coronavirus disease (COVID-19) pandemic affected millions of people worldwide and caused hundreds of thousands of deaths. The CHADS-VASc score is a scoring system used to determine the indication for anticoagulation in patients with atrial fibrillation (AF) and determines the risk of stroke, and previous studies have shown that it predicts mortality in COVID-19 patients well. New guidelines simplified the score as CHADS-VA score, which is free of gender factor. In this study, we planned to investigate the ability of this simplified score in predicting mortality and intensive care unit admission in COVID-19 patients. Materials and Methods All patients who were diagnosed with COVID-19 between January 2021 and January 2022 were screened and patients with accessible data were enrolled. The baseline characteristics of the patients and CHADS-VA scores were recorded and their relationship with poor outcomes was investigated. Results A total of 838 patients were included. Mean age of the study population was 53.8 ± 18.5 and 53.6% of them (n = 449) were male. Median CHA2DS2-VA score was 1 (0–8). Intensive care unit (ICU) admission was present in 177 (21.1%) patients. 1-year mortality was present in 86 (10.3%) patients. In multivariate regression analysis, only the CHA2DS2-VA score was predictive of 1-year mortality (OR = 1.63, 95% CI: 1.05–2.55; p = 0.029). Cut-off value of CHA 2 DS 2 -VA score for predicting 1-year mortality was found to be 2.5 (AUC:0.863, p < 0.001) with 75% sensitivity and 81% specificity. A CHA2DS2-VA score of 1.5 (AUC = 0.725, p < 0.001) constituted the cut-off value for intensive care admission with 61% sensitivity and 74% specificity. Conclusions As a result of our study, we found that CHA2DS2-VA score is an independent predictor of 1-year mortality following COVID-19 disease. Cut-off values of CHA2DS2-VA score can be used in clinical practice to define patients with high risk for ICU admission and mortality at one year. This is the first study to report the recently simplified CHA2DS2-VA score is associated with poor outcomes in COVID-19 patients. COVID-19 CHADS-VA Score mortality Figures Figure 1 Introduction A new virus that caused pneumonia cases was discovered in Wuhan, China, at the end of 2019. The virus propagated quickly and spread to nearly every country in the world, causing a pandemic. The new disease was dubbed "COVID-19" by the World Health Organization (WHO) in February 2020. The virus that caused it was subsequently identified as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) ( 1 ). Since its inception, the COVID-19 virus has killed millions of people. In COVID-19 patients, a number of comorbid conditions, including age, diabetes mellitus (DM), hypertension, chronic obstructive pulmonary disease (COPD), and renal failure, are independent predictors of mortality ( 2 – 5 ). The CHA 2 DS 2 -VASc score is a well-defined scoring system that includes some parameters such as age, gender, heart failure, hypertension, diabetes, stroke, and the presence of vascular disease and predicts thromboembolic events in patients with atrial fibrillation (AF). This scoring system is also used to determine the indication for anticoagulation in this patient group and guides clinicians in daily practice ( 3 , 5 , 6 ). In addition to prediction thromboembolic events, CHA 2 DS 2 -VASc score has shown to predict other major adverse cardiovascular events in other patient groups such as patients with cardiac implantable device and patients who underwent transcatheter aortic valve implantation ( 7 , 8 ). Previous studies have shown that the CHA 2 DS 2 -VASc score is associated with mortality rate and poor outcomes in COVID-19 patients ( 3 , 5 , 6 ). The recent 2024 ESC-EHRA atrial fibrillation guideline recommends the use of the CHA 2 DS 2 -VA score, excluding the gender factor, in AF patients to determine thromboembolic risk and anticoagulation indication. It has been emphasized that the most decisive factor in changing the scoring system is the determination that gender-related risk especially increases with aging rather than due to gender alone ( 9 ). It is known that the risk of thromboembolic events increases in COVID-19 patients and these events contribute to poor outcomes ( 2 ). We aimed to evaluate the relationship between the CHA 2 DS 2 -VA score, which was recently revised from CHA 2 DS 2 -VASc score, and COVID-19 related outcomes including intensive care unit (ICU) admission and 1-year mortality Materials and Methods The screening included all patients identified with COVID-19 disease between January 2021 and January 2022 based on specified findings on computed thoracic tomography, positive reverse-transcription polymerase chain reaction (PCR) test, and COVID-19-related signs and symptoms. Patients for whom data was available were included. Hospital databases were used to collect demographics, comorbidities, hematologic and biochemical laboratory results, hospital admission information, intensive care unit admission, and mortality status. The National Health Ministry's COVID-19 criteria were followed in the treatment of every patient. A systolic blood pressure (BP) of > 140 mm Hg and/or a diastolic BP of > 90 mm Hg on at least two different tests, as well as the usage of antihypertensive drugs prior to or during hospitalization for COVID-19, were used to diagnose hypertension.( 10 ). According to criteria such as a fasting plasma glucose level of 126 mg/dL or a HbA1C level of 6.5%, a random plasma glucose level of 200 mg/dL, or a 75-g oral glucose tolerance test with a plasma glucose level of 200 mg/dL, diabetes mellitus was defined as being under antidiabetic treatment or being newly diagnosed during hospitalization ( 11 ). A Beckman Coulter LH 780 hematology analyzer (Beckman Coulter) was used for the laboratory analyses, and a Beckman Coulter LH 780 device (Beckman Coulter Ireland Inc.) was used for the biochemical tests. Based on patient records, the CHADS-VA score was calculated using the following variables: age, diabetes, stroke, hypertension, congestive heart failure, and atherosclerotic vascular disease. Both the national mortality declaration system and hospital electronic databases provided mortality data. This cross-sectional, observational, retrospective study was conducted in accordance with the 1975 Declaration of Helsinki as amended in 2008, and it received ethical approval from the local ethics committee (approval no. 397, date: 28.03.2025). Statistical Analysis The mean ± standard deviation (SD) was used to express normally distributed continuous data, while the median with minimum and maximum values was used to express non-parametric variables. Statistical significance was defined as a two-sided p < 0.05 value. To find predictive characteristics, the logistic regression analysis was used. Multivariate regression analysis was performed on 1-year mortality predictors that had a p-value of less than 0.05 in the univariate analyses. Cut-off values of CHA2DS2-VASc for the prediction of 1-year mortality and intensive care unit admission were determined using ROC analysis. SPSS statistical software (version 26; SPSS Inc., Chicago, IL, USA) was used to conduct the statistical analysis. Results A total of 838 patients were enrolled. The mean age of the study population was 53.8 ± 18.5 years and 53.6% of them (n = 449) were male. Hypertension was present in 255 (30.4%) patients, diabetes was present in 136 (16.2%) patients and coronary artery disease was present in 117 (14.0%) cases. Baseline characteristics and laboratory values ​​of the patients were presented in Table 1. Median CHA 2 DS 2 -VA score was 1 (0–8). Intensive care unit (ICU) admission was required in 177 (21.1%) patients. Mortality occurred in 86 (10.3%) cases in the first year. Univariable regression analysis revealed that hypertension, diabetes mellitus, coronary artery disease, heart failure, atrial fibrillation, COPD, CHA 2 DS 2 -VA score, glomerular filtration rate, and albumin level were predictors of 1-year mortality. CHA 2 DS 2 -VA score, COPD, atrial fibrillation, albumin, and GFR were further included in multivariable regression analysis. Hypertension, diabetes mellitus, heart failure, and coronary artery disease were excluded from the multivariable regression analysis due to already being present in the CHA 2 DS 2 -VA score. Only the CHA 2 DS 2 -VA score was found to be predictive of 1-year mortality based on the multivariate regression analysis (Table 2). Cut-off CHA 2 DS 2 -VA score value was estimated for both ICU admission and mortality in 1-year. Receiver operating characteristic (ROC) analysis provided the CHA 2 DS 2 -VA score of 2.5 (AUC:0.863, p < 0.001) with 75% sensitivity and 81% specificity for 1-year mortality. CHA 2 DS 2 -VA score of 1.5 (AUC = 0.725, p < 0.001) was the cut-off value for ICU admission with 61% sensitivity and 74% specificity (Figure-1). Discussion In this study, we found that CHA 2 DS 2 -VA score was associated with both 1-year mortality and intensive care unit admission in COVID-19 patients. In our opinion, this study is the first study assessing the association beetween simplified CHA 2 DS 2 -VA score obtained by excluding the gender factor in the latest AF guideline and COVID-19 disease related outcomes. We have shown that the CHA 2 DS 2 -VA score is associated with both mortality and intensive care unit admission in COVID-19 patients. In December 2019, Wuhan, the capital of China's Hubei province, became the center of a pneumonia outbreak of unknown cause. As of January 7, 2020, Chinese scientists isolated a novel coronavirus called SARS-CoV-2 (previously known as 2019-nCoV) in pneumonia patients infected with the virus. COVID-19 disease was later declared a pandemic agent by the WHO and subsequently caused the death of millions of people ( 12 , 13 ). Predictors of mortality and poor outcome in Covid-19 patients have been investigated in detail. Parameters such as age, high Sequential Organ Failure Assessment (SOFA) score and diabetes have been found to be associated with mortality in previous studies ( 14 ). In a study conducted by Yuriy Pya and colleagues, it was determined that parameters such as leukocytosis, lymphopenia, anemia, elevated renal and liver function tests, hypoproteinemia, increased inflammatory markers (C-reactive protein (CRP), ferritin, and lactate dehydrogenase (LDH) and coagulation tests (fibrinogen, D-dimer, international normalized ratio (INR), and activated partial thromboplastin time (aPTT)) were associated with mortality. It was stated that endothelial damage and microthrombi, in particular, contribute to disease worsening and hypoxia in this patient group ( 15 , 16 ). In severe Covid-19 patients, fulminant coagulation activation and destruction of clotting factors occur ( 17 ). In a study published in China, it was shown that 71% of 183 patients who died due to COVID-19 met the criteria for diffuse intravascular coagulation. This study demonstrates the effect of coagulation on mortality and poor outcomes in this patient group ( 17 ). In critically ill patients, inflamed lung tissues and pulmonary endothelial cells cause microthrombus formation and, as a result, an increase in the incidence of thrombotic complications such as deep vein thrombosis, pulmonary embolism, and arterial complications such as extremity ischemia, ischemic stroke, and acute myocardial infarction. Along with the development of viral sepsis, the host's excessive response to the virus may also contribute to the development of multiorgan failure ( 18 ). Based on the evidence of crucial impact of thrombosis on COVID-19 related outcomes, several studies assessing the association between thromboembolic risk scores and clinical outcomes in patients with COVID-19. Açıksarı et al., in their study on 1001 COVID-19 patients, showed that the M-ATRIA-RS risk score was associated with in-hospital mortality and other poor outcomes and was a better predictor than the CHA 2 DS 2 -VASc-RS score ( 19 , 20 ). The CHA 2 DS 2 -VASc score is a well-defined and practical scoring system used to measure thromboembolic risk and determine anticoagulation indications in patients with atrial fibrillation. The greatest advantage of this score is that it is easy to apply and guides clinicians in daily practice. Gaetano Ruocco and colleagues previously showed that the CHA 2 DS 2 -VASc score was associated with both mortality and the need for mechanical ventilation in their study on 864 COVID-19 patients ( 21 ). It was stated that the high risk of thromboembolism in this patient group may be associated with outcomes. Again, in a study by Montazeri and colleagues, including 1406 hospitalized covid-19 patients, it was found that all three CHA 2 DS 2 , CHA 2 DS 2 -VASc, and CHA 2 DS 2 -VASc-M scores were associated with both 3-month mortality and in-hospital mortality and poor outcomes. It has also been stated that this increase in mortality is independent of the patients having AF ( 22 ). The most commonly used risk scoring system for determining the indication for anticoagulation in AF patients in Europe is the CHA 2 DS 2 -VASc score, which includes congestive heart failure, hypertension, age ≥ 75 years (2 points), diabetes mellitus, history of previous stroke/TIA/thromboembolism (2 points), vascular disease, age between 65 and 74 years, and female gender. Female gender is an age-related stroke risk modifier rather than a risk factor per se. The inclusion of gender in the scoring system complicates the application for both healthcare professionals and patients. This application also includes transgender individuals and those with sex hormone-excludes individuals receiving anticoagulation therapy ( 20 , 23 ). In the recent ESC atrial fibrillation guideline published in 2024, for the first time, the gender factor was excluded when determining the indication for anticoagulation in AF patients, and the CHA 2 DS 2 -VA score was recommended instead of the CHA 2 DS 2 -VA score. It was stated that this new approach was recommended because the gender factor was a risk factor that increased with age rather than being a risk factor on its own. In addition, it was emphasized that removing the gender factor from the scoring system would eliminate the confusion encountered in daily practice ( 9 ). Until now, there has been a paucity of data regarding the impact of the simplified revised CHA 2 DS 2 -VA score on outcomes related to COVID-19 disease. This study has revealed that this revised scoring system is a predictor of one-year mortality in patients with COVID-19 disease. There are some limitations of our study. The first one is the absence of data regarding the medications used during COVID-19 disease as they also may have effects on outcomes. Secondly, severity of COVID-19 disease also plays a significant role in COVID-19 related outcomes and due to the retrospective nature of the study we could not assess the severity of COVID-19 disease. Because of the retrospective design, we could not access data regarding major adverse cardiovascular events including acute coronary syndrome, thromboembolic events and arrhythmias. Therefore we could not evaluate the relationship between CHA 2 DS 2 -VA score and MACE in patients with COVID-19. Conclusion CHA 2 DS 2 -VA score is a good predictor one year mortality following COVID-19 disease. Cut-off values of CHA2DS2-VA score can be used in clinical practice to define patients with high risk for ICU admission and mortality at one year. This is the first study to report the recently simplified CHA2DS2-VA score is associated with poor outcomes in COVID-19 patients.Prospective studies with more patients will provide valuable data about the relationship between the CHA 2 DS 2 -VA score and outcomes including major adverse cardiovascular events independently from the presence of AF in patients with COVID-19 disease. Declarations Ethical approval and consent to participate : All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards. The study was authorized by the Gazi Yaşargil Training and Research Hospital Ethics Committee (Date: 28.03.2025, approval no:397). Because our study is retrospective, patient consent is not required. Consent for studies is routinely obtained from patients during hospitalization. Consent for publication: Not applicable. Data availability: The datasets generated during and/or analyzed during the current study are available from the corresponding author upon reasonable request. Code availability: Not applicable. Competing interest: The authors declare no competing interests. Funding: None Clinical Trial Number: Not applicable Author contribution: GYA, MO, and SS were major contributors to writing the manuscript. YZS,SS and IHI performed all the statistical analyses. GYA MO and EB performed the analytical tests and conducted the application of the clinical-epidemiological survey. EB and GYA checked the manuscript. All authors read and approved the final manuscript. References Kaya S, Kavak S. Efficacy of Tocilizumab in COVID-19: Single-Center Experience. Biomed Res Int. 2021;2021:1934685. Xu Z, Shi L, Wang Y, Zhang J, Huang L, Zhang C, et al. Pathological findings of COVID-19 associated with acute respiratory distress syndrome. Lancet Respir Med. 2020;8(4):420-2. Lippi G, Henry BM. Chronic obstructive pulmonary disease is associated with severe coronavirus disease 2019 (COVID-19). Respir Med. 2020;167:105941. Aktoz M, Altay H, Aslanger E, Atalar E, Aytekin V, Baykan AO, et al. [Consensus Report from Turkish Society of Cardiology: COVID-19 and Cardiovascular Diseases. What cardiologists should know. (25th March 2020)]. Turk Kardiyol Dern Ars. 2020;48(Suppl 1):1-48. Ruan Q, Yang K, Wang W, Jiang L, Song J. Clinical predictors of mortality due to COVID-19 based on an analysis of data of 150 patients from Wuhan, China. Intensive Care Med. 2020;46(5):846-8. Okşul M, Ziya Şener Y, Çöteli C. CHADS-VASc Score in STEMI Patients: Should We Use It Really? Acta Cardiol Sin. 2019;35(1):89. Hamid T, Choudhury TR, Anderson SG, Hashmi I, Chowdhary S, Hesketh Roberts D, et al. Does the CHA2DS2-Vasc score predict procedural and short-term outcomes in patients undergoing transcatheter aortic valve implantation? Open Heart. 2015;2(1):e000170. Söner S, Aktan A, Kılıç R, Güzel H, Taştan E, Okşul M, et al. Ability of CHA2DS2-VASc/R2CHA2DS2-VASc Scores to Predict Complications Related to Cardiac Implantable Electronic Devices. Pacing Clin Electrophysiol. 2025;48(2):151-9. Van Gelder IC, Rienstra M, Bunting KV, Casado-Arroyo R, Caso V, Crijns H, et al. 2024 ESC Guidelines for the management of atrial fibrillation developed in collaboration with the European Association for Cardio-Thoracic Surgery (EACTS). Eur Heart J. 2024;45(36):3314-414. National Institute for Health and Care Excellence: Guidelines. Hypertension in adults: diagnosis and management. London: National Institute for Health and Care Excellence (NICE) Copyright © NICE 2023.; 2023. Pippitt K, Li M, Gurgle HE. Diabetes Mellitus: Screening and Diagnosis. Am Fam Physician. 2016;93(2):103-9. Jha P, Brown PE, Ansumana R. Counting the global COVID-19 dead. Lancet. 2022;399(10339):1937-8. Chan JF, Yuan S, Kok KH, To KK, Chu H, Yang J, et al. A familial cluster of pneumonia associated with the 2019 novel coronavirus indicating person-to-person transmission: a study of a family cluster. Lancet. 2020;395(10223):514-23. Zhou F, Yu T, Du R, Fan G, Liu Y, Liu Z, et al. Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, China: a retrospective cohort study. Lancet. 2020;395(10229):1054-62. Kavosi H, Nayebi Rad S, Atef Yekta R, Tamartash Z, Dini M, Javadi Nejad Z, et al. Cardiopulmonary predictors of mortality in patients with COVID-19: What are the findings? Arch Cardiovasc Dis. 2022;115(6-7):388-96. Pya Y, Bekbossynova M, Gaipov A, Lesbekov T, Kapyshev T, Kuanyshbek A, et al. Mortality predictors of hospitalized patients with COVID-19: Retrospective cohort study from Nur-Sultan, Kazakhstan. PLoS One. 2021;16(12):e0261272. Tang N, Li D, Wang X, Sun Z. Abnormal coagulation parameters are associated with poor prognosis in patients with novel coronavirus pneumonia. J Thromb Haemost. 2020;18(4):844-7. Klok FA, Kruip M, van der Meer NJM, Arbous MS, Gommers D, Kant KM, et al. Incidence of thrombotic complications in critically ill ICU patients with COVID-19. Thromb Res. 2020;191:145-7. Wu VC, Wu M, Aboyans V, Chang SH, Chen SW, Chen MC, et al. Female sex as a risk factor for ischaemic stroke varies with age in patients with atrial fibrillation. Heart. 2020;106(7):534-40. Aciksari G, Cetinkal G, Kocak M, Cag Y, Atici A, Altunal LN, et al. Evaluation of Modified ATRIA Risk Score in Predicting Mortality in Hospitalized Patients With COVID-19. Am J Med Sci. 2021;362(6):553-61. Ruocco G, McCullough PA, Tecson KM, Mancone M, De Ferrari GM, D'Ascenzo F, et al. Mortality Risk Assessment Using CHA(2)DS(2)-VASc Scores in Patients Hospitalized With Coronavirus Disease 2019 Infection. Am J Cardiol. 2020;137:111-7. Montazeri M, Keykhaei M, Rashedi S, Karbalai Saleh S, Pazoki M, Hadadi A, et al. Prognostic significance of CHADS(2) and CHA(2)DS(2)-VASc scores to predict unfavorable outcomes in hospitalized patients with COVID-19. J Cardiovasc Thorac Res. 2022;14(1):23-33. Antonenko K, Paciaroni M, Agnelli G, Falocci N, Becattini C, Marcheselli S, et al. Sex-related differences in risk factors, type of treatment received and outcomes in patients with atrial fibrillation and acute stroke: Results from the RAF-study (Early Recurrence and Cerebral Bleeding in Patients with Acute Ischemic Stroke and Atrial Fibrillation). Eur Stroke J. 2017;2(1):46-53. Tables Table-2. Multivariate analysis of parameters that related to 1-year mortality in patients with COVID-19 Univariate Analysis OR (95% CI) p value Multivariate Analysis OR (95% CI) p value Atrial fibrillation 10.12 (2.05-49.98) 0.004* 0.50 (0.05-4.87) 0.559 COPD 3.97 (1.26-12.48) 0.018* 2.03 (0.59-6.90) 0.255 CHA 2 DS 2 - VA 1.83 (1.40-2.39) <0.001* 1.63 (1.05-2.55) 0.029* Glomerular filtration rate 0.96 (0.94-0.98) <0.001* 0.99 (0.96-1.02) 0.559 Albumin 0.18 (0.05-0.62) 0.007* 0.46 (0.10-2.10) 0.467 COPD: Chronic obstructive pulmonary disease Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 29 Dec, 2025 Read the published version in BMC Cardiovascular Disorders → Version 1 posted Editorial decision: Revision requested 29 Sep, 2025 Reviews received at journal 24 Sep, 2025 Reviewers agreed at journal 23 Sep, 2025 Reviews received at journal 25 Jul, 2025 Reviewers agreed at journal 24 Jul, 2025 Reviewers invited by journal 24 Jul, 2025 Editor assigned by journal 24 Jul, 2025 Editor invited by journal 23 Jul, 2025 Submission checks completed at journal 22 Jul, 2025 First submitted to journal 22 Jul, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6742800","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":491198332,"identity":"de884383-e8f0-4672-b726-6f4fb3b72a7e","order_by":0,"name":"Gamze Yeter Arslan","email":"","orcid":"","institution":"Kepez State Hospital","correspondingAuthor":false,"prefix":"","firstName":"Gamze","middleName":"Yeter","lastName":"Arslan","suffix":""},{"id":491198336,"identity":"43ea7984-8a2c-4e62-81ff-e8760279f7d1","order_by":1,"name":"Metin Okşul","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA3ElEQVRIiWNgGAWjYFACNiAuYKifz94D5vLwEafFgIFxY88ZBoYDQC1sRGtpuJED1sJAUItue1vyZx4DBmbGmW8PPv6YYyfDxsD88NENPFrMzhw7Jg3UwsYunZdscHBbMtBhbMbGOfi03EhvYwZq4WGcnWMmcXAbM1ALD5s0AS3NIIdJMNw8A9JST4yWtAMghxkw3OABaTlMhJYzx9Ik5xgwJBj25BgbnN12nIeNmZBfjrcZf3hTwZAgz37G8EHltmp7fvbmh4/xaYGC/0hsZsLKR8EoGAWjYBQQAAA4MkH53XVtmAAAAABJRU5ErkJggg==","orcid":"","institution":"Health Science University, Gazi Yaşargil Training and Research Hospital","correspondingAuthor":true,"prefix":"","firstName":"Metin","middleName":"","lastName":"Okşul","suffix":""},{"id":491198339,"identity":"f18e2357-d8b7-425b-85b1-fb970dfc9a43","order_by":2,"name":"Yusuf Ziya Şener","email":"","orcid":"","institution":"Erasmus University Medical Center","correspondingAuthor":false,"prefix":"","firstName":"Yusuf","middleName":"Ziya","lastName":"Şener","suffix":""},{"id":491198343,"identity":"95217560-35c5-43c6-b5ff-3d2656bc5dbc","order_by":3,"name":"Serdar Söner","email":"","orcid":"","institution":"Health Science University, Gazi Yaşargil Training and Research Hospital","correspondingAuthor":false,"prefix":"","firstName":"Serdar","middleName":"","lastName":"Söner","suffix":""},{"id":491198344,"identity":"1ccb127d-1dfd-4f3e-b3ab-87db264b0ed5","order_by":4,"name":"İbrahim Halil İnanç","email":"","orcid":"","institution":"Health Science University, Gazi Yaşargil Training and Research Hospital","correspondingAuthor":false,"prefix":"","firstName":"İbrahim","middleName":"Halil","lastName":"İnanç","suffix":""},{"id":491198345,"identity":"2fbb6b29-6b1c-4229-a599-49c03821070e","order_by":5,"name":"Erkan Baysal","email":"","orcid":"","institution":"Health Science University, Gazi Yaşargil Training and Research Hospital","correspondingAuthor":false,"prefix":"","firstName":"Erkan","middleName":"","lastName":"Baysal","suffix":""}],"badges":[],"createdAt":"2025-05-25 09:08:38","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6742800/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6742800/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12872-025-05364-6","type":"published","date":"2025-12-29T15:57:28+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":87825831,"identity":"670b4edf-d065-4427-8004-8cb85cd97537","added_by":"auto","created_at":"2025-07-29 11:50:04","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":38258,"visible":true,"origin":"","legend":"\u003cp\u003eROC analysis of CHA2DS2-VA value for the prediction of 1-year mortality and ICU admission.\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-6742800/v1/31017dbf6c126df7ba9f39cb.png"},{"id":99545457,"identity":"aea6613e-768a-4a27-84a2-afb9261dd3a8","added_by":"auto","created_at":"2026-01-05 16:07:48","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":540547,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6742800/v1/620a0a10-79fb-4c58-ab7d-8984b69efd6c.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"\u003cp\u003eImpact of CHADS-VA Score on COVID-19 Disease Related Outcomes\u003c/p\u003e","fulltext":[{"header":"Introduction","content":"\u003cp\u003eA new virus that caused pneumonia cases was discovered in Wuhan, China, at the end of 2019. The virus propagated quickly and spread to nearly every country in the world, causing a pandemic. The new disease was dubbed \"COVID-19\" by the World Health Organization (WHO) in February 2020. The virus that caused it was subsequently identified as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). Since its inception, the COVID-19 virus has killed millions of people. In COVID-19 patients, a number of comorbid conditions, including age, diabetes mellitus (DM), hypertension, chronic obstructive pulmonary disease (COPD), and renal failure, are independent predictors of mortality (\u003cspan additionalcitationids=\"CR3 CR4\" citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe CHA\u003csub\u003e2\u003c/sub\u003eDS\u003csub\u003e2\u003c/sub\u003e-VASc score is a well-defined scoring system that includes some parameters such as age, gender, heart failure, hypertension, diabetes, stroke, and the presence of vascular disease and predicts thromboembolic events in patients with atrial fibrillation (AF). This scoring system is also used to determine the indication for anticoagulation in this patient group and guides clinicians in daily practice (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e). In addition to prediction thromboembolic events, CHA\u003csub\u003e2\u003c/sub\u003eDS\u003csub\u003e2\u003c/sub\u003e-VASc score has shown to predict other major adverse cardiovascular events in other patient groups such as patients with cardiac implantable device and patients who underwent transcatheter aortic valve implantation (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e). Previous studies have shown that the CHA\u003csub\u003e2\u003c/sub\u003eDS\u003csub\u003e2\u003c/sub\u003e-VASc score is associated with mortality rate and poor outcomes in COVID-19 patients (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe recent 2024 ESC-EHRA atrial fibrillation guideline recommends the use of the CHA\u003csub\u003e2\u003c/sub\u003eDS\u003csub\u003e2\u003c/sub\u003e-VA score, excluding the gender factor, in AF patients to determine thromboembolic risk and anticoagulation indication. It has been emphasized that the most decisive factor in changing the scoring system is the determination that gender-related risk especially increases with aging rather than due to gender alone (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eIt is known that the risk of thromboembolic events increases in COVID-19 patients and these events contribute to poor outcomes (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). We aimed to evaluate the relationship between the CHA\u003csub\u003e2\u003c/sub\u003eDS\u003csub\u003e2\u003c/sub\u003e-VA score, which was recently revised from CHA\u003csub\u003e2\u003c/sub\u003eDS\u003csub\u003e2\u003c/sub\u003e-VASc score, and COVID-19 related outcomes including intensive care unit (ICU) admission and 1-year mortality\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cp\u003eThe screening included all patients identified with COVID-19 disease between January 2021 and January 2022 based on specified findings on computed thoracic tomography, positive reverse-transcription polymerase chain reaction (PCR) test, and COVID-19-related signs and symptoms. Patients for whom data was available were included. Hospital databases were used to collect demographics, comorbidities, hematologic and biochemical laboratory results, hospital admission information, intensive care unit admission, and mortality status. The National Health Ministry's COVID-19 criteria were followed in the treatment of every patient. A systolic blood pressure (BP) of \u0026gt;\u0026thinsp;140 mm Hg and/or a diastolic BP of \u0026gt;\u0026thinsp;90 mm Hg on at least two different tests, as well as the usage of antihypertensive drugs prior to or during hospitalization for COVID-19, were used to diagnose hypertension.(\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eAccording to criteria such as a fasting plasma glucose level of 126 mg/dL or a HbA1C level of 6.5%, a random plasma glucose level of 200 mg/dL, or a 75-g oral glucose tolerance test with a plasma glucose level of 200 mg/dL, diabetes mellitus was defined as being under antidiabetic treatment or being newly diagnosed during hospitalization (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e). A Beckman Coulter LH 780 hematology analyzer (Beckman Coulter) was used for the laboratory analyses, and a Beckman Coulter LH 780 device (Beckman Coulter Ireland Inc.) was used for the biochemical tests.\u003c/p\u003e\u003cp\u003eBased on patient records, the CHADS-VA score was calculated using the following variables: age, diabetes, stroke, hypertension, congestive heart failure, and atherosclerotic vascular disease. Both the national mortality declaration system and hospital electronic databases provided mortality data. This cross-sectional, observational, retrospective study was conducted in accordance with the 1975 Declaration of Helsinki as amended in 2008, and it received ethical approval from the local ethics committee (approval no. 397, date: 28.03.2025).\u003c/p\u003e\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eStatistical Analysis\u003c/h2\u003e\u003cp\u003eThe mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation (SD) was used to express normally distributed continuous data, while the median with minimum and maximum values was used to express non-parametric variables. Statistical significance was defined as a two-sided p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 value. To find predictive characteristics, the logistic regression analysis was used. Multivariate regression analysis was performed on 1-year mortality predictors that had a p-value of less than 0.05 in the univariate analyses. Cut-off values of CHA2DS2-VASc for the prediction of 1-year mortality and intensive care unit admission were determined using ROC analysis. SPSS statistical software (version 26; SPSS Inc., Chicago, IL, USA) was used to conduct the statistical analysis.\u003c/p\u003e\u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eA total of 838 patients were enrolled. The mean age of the study population was 53.8\u0026thinsp;\u0026plusmn;\u0026thinsp;18.5 years and 53.6% of them (n\u0026thinsp;=\u0026thinsp;449) were male. Hypertension was present in 255 (30.4%) patients, diabetes was present in 136 (16.2%) patients and coronary artery disease was present in 117 (14.0%) cases. Baseline characteristics and laboratory values ​​of the patients were presented in Table\u0026nbsp;1.\u003c/p\u003e\u003cp\u003eMedian CHA\u003csub\u003e2\u003c/sub\u003eDS\u003csub\u003e2\u003c/sub\u003e-VA score was 1 (0\u0026ndash;8). Intensive care unit (ICU) admission was required in 177 (21.1%) patients. Mortality occurred in 86 (10.3%) cases in the first year. Univariable regression analysis revealed that hypertension, diabetes mellitus, coronary artery disease, heart failure, atrial fibrillation, COPD, CHA\u003csub\u003e2\u003c/sub\u003eDS\u003csub\u003e2\u003c/sub\u003e-VA score, glomerular filtration rate, and albumin level were predictors of 1-year mortality. CHA\u003csub\u003e2\u003c/sub\u003eDS\u003csub\u003e2\u003c/sub\u003e-VA score, COPD, atrial fibrillation, albumin, and GFR were further included in multivariable regression analysis. Hypertension, diabetes mellitus, heart failure, and coronary artery disease were excluded from the multivariable regression analysis due to already being present in the CHA\u003csub\u003e2\u003c/sub\u003eDS\u003csub\u003e2\u003c/sub\u003e-VA score. Only the CHA\u003csub\u003e2\u003c/sub\u003eDS\u003csub\u003e2\u003c/sub\u003e-VA score was found to be predictive of 1-year mortality based on the multivariate regression analysis (Table\u0026nbsp;2).\u003c/p\u003e\u003cp\u003eCut-off CHA\u003csub\u003e2\u003c/sub\u003eDS\u003csub\u003e2\u003c/sub\u003e-VA score value was estimated for both ICU admission and mortality in 1-year. Receiver operating characteristic (ROC) analysis provided the CHA\u003csub\u003e2\u003c/sub\u003eDS\u003csub\u003e2\u003c/sub\u003e-VA score of 2.5 (AUC:0.863, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) with 75% sensitivity and 81% specificity for 1-year mortality. CHA\u003csub\u003e2\u003c/sub\u003eDS\u003csub\u003e2\u003c/sub\u003e-VA score of 1.5 (AUC\u0026thinsp;=\u0026thinsp;0.725, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) was the cut-off value for ICU admission with 61% sensitivity and 74% specificity (Figure-1).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn this study, we found that CHA\u003csub\u003e2\u003c/sub\u003eDS\u003csub\u003e2\u003c/sub\u003e-VA score was associated with both 1-year mortality and intensive care unit admission in COVID-19 patients. In our opinion, this study is the first study assessing the association beetween simplified CHA\u003csub\u003e2\u003c/sub\u003eDS\u003csub\u003e2\u003c/sub\u003e-VA score obtained by excluding the gender factor in the latest AF guideline and COVID-19 disease related outcomes. We have shown that the CHA\u003csub\u003e2\u003c/sub\u003eDS\u003csub\u003e2\u003c/sub\u003e-VA score is associated with both mortality and intensive care unit admission in COVID-19 patients.\u003c/p\u003e\u003cp\u003eIn December 2019, Wuhan, the capital of China's Hubei province, became the center of a pneumonia outbreak of unknown cause. As of January 7, 2020, Chinese scientists isolated a novel coronavirus called SARS-CoV-2 (previously known as 2019-nCoV) in pneumonia patients infected with the virus. COVID-19 disease was later declared a pandemic agent by the WHO and subsequently caused the death of millions of people (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e).\u003c/p\u003e\u003cp\u003ePredictors of mortality and poor outcome in Covid-19 patients have been investigated in detail. Parameters such as age, high Sequential Organ Failure Assessment (SOFA) score and diabetes have been found to be associated with mortality in previous studies (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e). In a study conducted by Yuriy Pya and colleagues, it was determined that parameters such as leukocytosis, lymphopenia, anemia, elevated renal and liver function tests, hypoproteinemia, increased inflammatory markers (C-reactive protein (CRP), ferritin, and lactate dehydrogenase (LDH) and coagulation tests (fibrinogen, D-dimer, international normalized ratio (INR), and activated partial thromboplastin time (aPTT)) were associated with mortality. It was stated that endothelial damage and microthrombi, in particular, contribute to disease worsening and hypoxia in this patient group (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eIn severe Covid-19 patients, fulminant coagulation activation and destruction of clotting factors occur (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e). In a study published in China, it was shown that 71% of 183 patients who died due to COVID-19 met the criteria for diffuse intravascular coagulation. This study demonstrates the effect of coagulation on mortality and poor outcomes in this patient group (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e). In critically ill patients, inflamed lung tissues and pulmonary endothelial cells cause microthrombus formation and, as a result, an increase in the incidence of thrombotic complications such as deep vein thrombosis, pulmonary embolism, and arterial complications such as extremity ischemia, ischemic stroke, and acute myocardial infarction. Along with the development of viral sepsis, the host's excessive response to the virus may also contribute to the development of multiorgan failure (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eBased on the evidence of crucial impact of thrombosis on COVID-19 related outcomes, several studies assessing the association between thromboembolic risk scores and clinical outcomes in patients with COVID-19. A\u0026ccedil;ıksarı et al., in their study on 1001 COVID-19 patients, showed that the M-ATRIA-RS risk score was associated with in-hospital mortality and other poor outcomes and was a better predictor than the CHA\u003csub\u003e2\u003c/sub\u003eDS\u003csub\u003e2\u003c/sub\u003e-VASc-RS score (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e). The CHA\u003csub\u003e2\u003c/sub\u003eDS\u003csub\u003e2\u003c/sub\u003e-VASc score is a well-defined and practical scoring system used to measure thromboembolic risk and determine anticoagulation indications in patients with atrial fibrillation. The greatest advantage of this score is that it is easy to apply and guides clinicians in daily practice. Gaetano Ruocco and colleagues previously showed that the CHA\u003csub\u003e2\u003c/sub\u003eDS\u003csub\u003e2\u003c/sub\u003e-VASc score was associated with both mortality and the need for mechanical ventilation in their study on 864 COVID-19 patients (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e). It was stated that the high risk of thromboembolism in this patient group may be associated with outcomes. Again, in a study by Montazeri and colleagues, including 1406 hospitalized covid-19 patients, it was found that all three CHA\u003csub\u003e2\u003c/sub\u003eDS\u003csub\u003e2\u003c/sub\u003e, CHA\u003csub\u003e2\u003c/sub\u003eDS\u003csub\u003e2\u003c/sub\u003e-VASc, and CHA\u003csub\u003e2\u003c/sub\u003eDS\u003csub\u003e2\u003c/sub\u003e-VASc-M scores were associated with both 3-month mortality and in-hospital mortality and poor outcomes. It has also been stated that this increase in mortality is independent of the patients having AF (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe most commonly used risk scoring system for determining the indication for anticoagulation in AF patients in Europe is the CHA\u003csub\u003e2\u003c/sub\u003eDS\u003csub\u003e2\u003c/sub\u003e-VASc score, which includes congestive heart failure, hypertension, age\u0026thinsp;\u0026ge;\u0026thinsp;75 years (2 points), diabetes mellitus, history of previous stroke/TIA/thromboembolism (2 points), vascular disease, age between 65 and 74 years, and female gender. Female gender is an age-related stroke risk modifier rather than a risk factor per se. The inclusion of gender in the scoring system complicates the application for both healthcare professionals and patients. This application also includes transgender individuals and those with sex hormone-excludes individuals receiving anticoagulation therapy (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e). In the recent ESC atrial fibrillation guideline published in 2024, for the first time, the gender factor was excluded when determining the indication for anticoagulation in AF patients, and the CHA\u003csub\u003e2\u003c/sub\u003eDS\u003csub\u003e2\u003c/sub\u003e-VA score was recommended instead of the CHA\u003csub\u003e2\u003c/sub\u003eDS\u003csub\u003e2\u003c/sub\u003e-VA score. It was stated that this new approach was recommended because the gender factor was a risk factor that increased with age rather than being a risk factor on its own. In addition, it was emphasized that removing the gender factor from the scoring system would eliminate the confusion encountered in daily practice (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e). Until now, there has been a paucity of data regarding the impact of the simplified revised CHA\u003csub\u003e2\u003c/sub\u003eDS\u003csub\u003e2\u003c/sub\u003e-VA score on outcomes related to COVID-19 disease. This study has revealed that this revised scoring system is a predictor of one-year mortality in patients with COVID-19 disease.\u003c/p\u003e\u003cp\u003eThere are some limitations of our study. The first one is the absence of data regarding the medications used during COVID-19 disease as they also may have effects on outcomes. Secondly, severity of COVID-19 disease also plays a significant role in COVID-19 related outcomes and due to the retrospective nature of the study we could not assess the severity of COVID-19 disease. Because of the retrospective design, we could not access data regarding major adverse cardiovascular events including acute coronary syndrome, thromboembolic events and arrhythmias. Therefore we could not evaluate the relationship between CHA\u003csub\u003e2\u003c/sub\u003eDS\u003csub\u003e2\u003c/sub\u003e-VA score and MACE in patients with COVID-19.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eCHA\u003csub\u003e2\u003c/sub\u003eDS\u003csub\u003e2\u003c/sub\u003e-VA score is a good predictor one year mortality following COVID-19 disease. Cut-off values of CHA2DS2-VA score can be used in clinical practice to define patients with high risk for ICU admission and mortality at one year. This is the first study to report the recently simplified CHA2DS2-VA score is associated with poor outcomes in COVID-19 patients.Prospective studies with more patients will provide valuable data about the relationship between the CHA\u003csub\u003e2\u003c/sub\u003eDS\u003csub\u003e2\u003c/sub\u003e-VA score and outcomes including major adverse cardiovascular events independently from the presence of AF in patients with COVID-19 disease.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthical approval and\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003econsent to participate\u003c/strong\u003e\u003cstrong\u003e:\u0026nbsp;\u003c/strong\u003eAll procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards. The study was authorized by the Gazi Yaşargil Training and Research Hospital Ethics Committee (Date: 28.03.2025, approval no:397). Because our study is retrospective, patient consent is not required. Consent for studies is routinely obtained from patients during hospitalization.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication:\u0026nbsp;\u003c/strong\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability:\u0026nbsp;\u003c/strong\u003eThe datasets generated during and/or analyzed during the current study are available from the corresponding author upon reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCode availability:\u0026nbsp;\u003c/strong\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interest:\u0026nbsp;\u003c/strong\u003eThe authors declare no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u0026nbsp;\u003c/strong\u003eNone\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical Trial Number:\u0026nbsp;\u003c/strong\u003eNot applicable\u003c/p\u003e\n\u003cp\u003eAuthor contribution: GYA, MO, and SS were major contributors to writing the manuscript. YZS,SS and IHI performed all the statistical analyses. GYA MO and EB performed the analytical tests and conducted the application of the clinical-epidemiological survey. EB and GYA checked the manuscript. All authors read and approved the final manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eKaya S, Kavak S. Efficacy of Tocilizumab in COVID-19: Single-Center Experience. Biomed Res Int. 2021;2021:1934685.\u003c/li\u003e\n\u003cli\u003eXu Z, Shi L, Wang Y, Zhang J, Huang L, Zhang C, et al. Pathological findings of COVID-19 associated with acute respiratory distress syndrome. Lancet Respir Med. 2020;8(4):420-2.\u003c/li\u003e\n\u003cli\u003eLippi G, Henry BM. Chronic obstructive pulmonary disease is associated with severe coronavirus disease 2019 (COVID-19). Respir Med. 2020;167:105941.\u003c/li\u003e\n\u003cli\u003eAktoz M, Altay H, Aslanger E, Atalar E, Aytekin V, Baykan AO, et al. [Consensus Report from Turkish Society of Cardiology: COVID-19 and Cardiovascular Diseases. What cardiologists should know. (25th March 2020)]. Turk Kardiyol Dern Ars. 2020;48(Suppl 1):1-48.\u003c/li\u003e\n\u003cli\u003eRuan Q, Yang K, Wang W, Jiang L, Song J. Clinical predictors of mortality due to COVID-19 based on an analysis of data of 150 patients from Wuhan, China. Intensive Care Med. 2020;46(5):846-8.\u003c/li\u003e\n\u003cli\u003eOkşul M, Ziya Şener Y, \u0026Ccedil;\u0026ouml;teli C. CHADS-VASc Score in STEMI Patients: Should We Use It Really? Acta Cardiol Sin. 2019;35(1):89.\u003c/li\u003e\n\u003cli\u003eHamid T, Choudhury TR, Anderson SG, Hashmi I, Chowdhary S, Hesketh Roberts D, et al. Does the CHA2DS2-Vasc score predict procedural and short-term outcomes in patients undergoing transcatheter aortic valve implantation? Open Heart. 2015;2(1):e000170.\u003c/li\u003e\n\u003cli\u003eS\u0026ouml;ner S, Aktan A, Kılı\u0026ccedil; R, G\u0026uuml;zel H, Taştan E, Okşul M, et al. Ability of CHA2DS2-VASc/R2CHA2DS2-VASc Scores to Predict Complications Related to Cardiac Implantable Electronic Devices. Pacing Clin Electrophysiol. 2025;48(2):151-9.\u003c/li\u003e\n\u003cli\u003eVan Gelder IC, Rienstra M, Bunting KV, Casado-Arroyo R, Caso V, Crijns H, et al. 2024 ESC Guidelines for the management of atrial fibrillation developed in collaboration with the European Association for Cardio-Thoracic Surgery (EACTS). Eur Heart J. 2024;45(36):3314-414.\u003c/li\u003e\n\u003cli\u003eNational Institute for Health and Care Excellence: Guidelines. Hypertension in adults: diagnosis and management. London: National Institute for Health and Care Excellence (NICE) Copyright \u0026copy; NICE 2023.; 2023.\u003c/li\u003e\n\u003cli\u003ePippitt K, Li M, Gurgle HE. Diabetes Mellitus: Screening and Diagnosis. Am Fam Physician. 2016;93(2):103-9.\u003c/li\u003e\n\u003cli\u003eJha P, Brown PE, Ansumana R. Counting the global COVID-19 dead. Lancet. 2022;399(10339):1937-8.\u003c/li\u003e\n\u003cli\u003eChan JF, Yuan S, Kok KH, To KK, Chu H, Yang J, et al. A familial cluster of pneumonia associated with the 2019 novel coronavirus indicating person-to-person transmission: a study of a family cluster. Lancet. 2020;395(10223):514-23.\u003c/li\u003e\n\u003cli\u003eZhou F, Yu T, Du R, Fan G, Liu Y, Liu Z, et al. Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, China: a retrospective cohort study. Lancet. 2020;395(10229):1054-62.\u003c/li\u003e\n\u003cli\u003eKavosi H, Nayebi Rad S, Atef Yekta R, Tamartash Z, Dini M, Javadi Nejad Z, et al. Cardiopulmonary predictors of mortality in patients with COVID-19: What are the findings? Arch Cardiovasc Dis. 2022;115(6-7):388-96.\u003c/li\u003e\n\u003cli\u003ePya Y, Bekbossynova M, Gaipov A, Lesbekov T, Kapyshev T, Kuanyshbek A, et al. Mortality predictors of hospitalized patients with COVID-19: Retrospective cohort study from Nur-Sultan, Kazakhstan. PLoS One. 2021;16(12):e0261272.\u003c/li\u003e\n\u003cli\u003eTang N, Li D, Wang X, Sun Z. Abnormal coagulation parameters are associated with poor prognosis in patients with novel coronavirus pneumonia. J Thromb Haemost. 2020;18(4):844-7.\u003c/li\u003e\n\u003cli\u003eKlok FA, Kruip M, van der Meer NJM, Arbous MS, Gommers D, Kant KM, et al. Incidence of thrombotic complications in critically ill ICU patients with COVID-19. Thromb Res. 2020;191:145-7.\u003c/li\u003e\n\u003cli\u003eWu VC, Wu M, Aboyans V, Chang SH, Chen SW, Chen MC, et al. Female sex as a risk factor for ischaemic stroke varies with age in patients with atrial fibrillation. Heart. 2020;106(7):534-40.\u003c/li\u003e\n\u003cli\u003eAciksari G, Cetinkal G, Kocak M, Cag Y, Atici A, Altunal LN, et al. Evaluation of Modified ATRIA Risk Score in Predicting Mortality in Hospitalized Patients With COVID-19. Am J Med Sci. 2021;362(6):553-61.\u003c/li\u003e\n\u003cli\u003eRuocco G, McCullough PA, Tecson KM, Mancone M, De Ferrari GM, D\u0026apos;Ascenzo F, et al. Mortality Risk Assessment Using CHA(2)DS(2)-VASc Scores in Patients Hospitalized With Coronavirus Disease 2019 Infection. Am J Cardiol. 2020;137:111-7.\u003c/li\u003e\n\u003cli\u003eMontazeri M, Keykhaei M, Rashedi S, Karbalai Saleh S, Pazoki M, Hadadi A, et al. Prognostic significance of CHADS(2) and CHA(2)DS(2)-VASc scores to predict unfavorable outcomes in hospitalized patients with COVID-19. J Cardiovasc Thorac Res. 2022;14(1):23-33.\u003c/li\u003e\n\u003cli\u003eAntonenko K, Paciaroni M, Agnelli G, Falocci N, Becattini C, Marcheselli S, et al. Sex-related differences in risk factors, type of treatment received and outcomes in patients with atrial fibrillation and acute stroke: Results from the RAF-study (Early Recurrence and Cerebral Bleeding in Patients with Acute Ischemic Stroke and Atrial Fibrillation). Eur Stroke J. 2017;2(1):46-53.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003e\u003cimg 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x3EmC8jFTIGFruWUjKTlbVugtG5pkd988825SRq6q+MWMv5kije/6x5Tp04NZ3oOxHfffRdaz2Xs2LGjdf78+dAF78OpXSSo7wxzWRtqZkeOHAnvcqRqakCtS3bi44033shtDbkn85UrV+am1WDXuqlwWHPVdm14rbmgtmqf23AQVvsMqE1yrXjoXkdR7ddxBgXldac9rFzjoFUct7AFcoTnX375ZW5SjFq8mfIM7iGrrDyNqfMdsVMkxwkXrXz8JXzYK4oH8Az7ijdHE7nujEbfcPhLyqAuKDx9YJsxUYwWqyh5J74XUnjWThOlZ8NgIaPIHyleZR69IzDnXvblng2H7HAQZil6zHWt97lvEgfH6UfI005nIBOQP5JzKNsYK8PoAi9TikJd2ChIq7TjBkrREctrzCTXY4gDylt26oQPUPLIQSnxqiEApxjSL5zDb4YM6sKHUEaRQuSQUhRW0QndS6npfTK1iN+pg96xYbCKU4VG4eYZ97KjsOp9uWfdsPGxCh439awo4zvOIEKedroDyk4KWvLDghlKnefx+HUKWr/IHZQiR1lLvc53LJNfhB2/FD7JyboQN8Jo5bzTDH3D4S9Z56NaYvvc67BYRSd0HyvM1JHK3EVIEes97vU+Z+uuPeIMGNdW7fNUfCz2PVUQHGeQKcrrTntIFsWtXQvKEyVXBvJFShY31ZUtmRdT5ztiJ6W4Udq4rzCrpV+ncmFRI81pD6VdW5PTNMHC/i/PYidgrFq1Kr8amnRhJygsX748vxoiq4kRqhHHz372s/xpNatXr86vLv1NLfV+lnlG+MHfMMTPf/7z1qJFi4J5O/BeptzDNX/pYEKK4ziOQCYh62bMmJGbjGbJkiX5VTHIFtnDzYMHD4YJa0wI6zbI088++6z1y1/+Mtw//PDDrUx5t7Zs2VL497MUCxYsCHF3OqMtxb1nz55WVvMaofy4FzwXZCgpQT4YShEwk1K96qqrwjmrKSYzwX//93+HykHRwgAWKc01a9a0Fi5cGK7BKvCPP/44vxoJ7hMGudEuVARwB/ifpeM4jmDxERoIVibFXLhwIczELsP+LxyYmc4sb2ZxpxY9gdis7kxvwhOjhtePP/4YznX45z//2XrooYfyO6dtMgUaMJel0FVcNAaCOe5wxOPCZd1CdO3oPes21zxjTETPq7qf5RbvxBAOuaPwcMYc9EzhtffCuhFDnG28CX8qHI4zSKTyulMP5BEyQRO5NBvbjkUzZmy7oRm3jru8eR8z2zWNO5hZWWbvm4IffGvCEiN5iPzDHgfXVl4TTxtu3rET0YgX9pUWTnNUFhspbqtAOawSteY6+Ej64KnDKjkpXHsoA1plWaW4AftF9qxbHDbj2WeYc+iesOKm7nXYwoWd2H3HGXQ8H7cP8kFyE6WGfIgVF3KFZ9jBbsoO99ixilvKU++icFGO7YDswg17xBUA3MYPnqXiEituVUCwT7ysvHfag7SEnu/HzXg3Y71FZJljeNykCrqy169fX2mfsR87bu04Tvv0SjY4jtMMlcWO1yqvgnGarKaV343mzJkz+VU5jHNDSmkzLk6ENBFMY+aO4ziOM9HoueJGme7atSvUEuzxbT55q2oCBuDGqVOnwqzJFGfPng1nFDgtfDspzXEcx3EmEj3vKgfcjpk1a1br5MmT+V3nMEuTysDKlSu9m9xxuoh3lTtOf6CyOCaK23GcwcVlg+P0ByqLPe8qdxzHcRyne4xocTuO4ziO07+gsr2r3HGcUlw2OE5/4F3ljuM4jjOAuOJ2HMdxnAHCFbfjOM6AwroVr776an43+BCXv/71r/mdU0RHilu7dtlDq5fxrO7OM+3Cf7et3xMBrQKno9dp2BSFTyA4FFa+RxEsV6vV7wRxK3vHcQaFZ555pnL3wiI7mLMdJ2WIBalSOySmQNYeOHBg1PbI+KEyyYH7Fu6LnlVB2PBX4S3iH//4x3A4OBfF6frrrw92BXF59tlnh/WIUwCT08BcVsIi8tjnYKF5i12sPl6kvhfgv/ybKNjNTMYiDeuib6swceaeb6Bru2mL4L2iDQYU136KpzMSvo9TTFneF0V22DSEjTvYrEObhrAhh928IwW7brGrWIyVzTrsTmSUQ5U1lb2ishkj+yrvZRBPhY/rVNoQd7t7mCDupAn+OSMh/cM5/GbIoIoypS2USas+bjdwxT02pBSs0l4FX2EmjwiuEURlyB37ntM/8G2cNFIy5PEixV1kR7LU5nvssqNWmTKVnVR5oSwVKTzsx/LEKtgycBM/6+4+RrwUB85xHiIcRekFhBX/iKtzCaVj467yHTt25Fet1qpVq/KrkbARSPax8jtnIsAObyxTazd5qdOlt3Tp0tahQ4fyuzTKR9495gwav//971tPPvlk6ZBPkZ0PP/wwnH/2s5+FM/z0pz8NZebNN9/MTUaze/fuYMe+B5THV155pfXCCy+EYal//etf+ZMhsB9v0sSy0/fdd19+l4aubMr/1q1bW7feemtu2j6E6/7772/t3bs3NxkNYV2wYEGIqzOaxoqbjAEI8TjjWFavXj0qkyCYNbZix3rsmAzX1l5qXFTPygoLmVj2OOxYsTVnjFZj9TZMZcg+B2FIjfNaOymFpGc66ijBsjhVYcPDYcNcFW99g4ceeiicRdn3B+K9adOmSns8z2rfrQ8++KDvxvQdpwjyatYyLN0oqczOhQsXwjlWsHPnzm199tln+d1o2LQJOzFvvfVWOPPumjVrWldfffWI8WML4aLcUz6rlDEKO2v9hvBqbJuyHYfbQnn+4osvwvXhw4fDvVixYkVrz549oZJSxpIlS0JcnQSh3Z1hLguhewN7HGXdHCmwz3u4QTcI17arnW4kuU23jLpXOLAP1n+QO9YMZE9hjLtirTv4a/2qi+LDoXjongM3rT9cQxz3lN+prvKqONVB73BwbcNX1L0G+jaxHb1v3VL4uNc1xN83RmEjPZz+gu/ijIQuXPK3unK5tvkdquyonMflgbJAN3EKyQ/KVwr8ojsbf7BHuZP/wsoc7FXJENnTWDnj0piVdbFjV2GI32Vsuw7Eg/ebyLiJDukRzuE3QwZlWEHPx6iLfU9IkOuj6F7uKlNbOzYjCKuMhOxJCcgt7IINj+zwrEmc5AfhFnIz5Y8KpwoeB9d1FXdVnOoQp5UNi8KXQnYUFosNq00/7oXCjn+6jt1SOlg3nP7AfktnCJSPzcPk2zjvVtlBoaKgOaTYUFbIlCKliHup8pMC/7GbKtv4rTLH+HsRRf5Jlkg214E4Wr8Il+R+Spk3ietkgfSARl3lM2bMyK+GxkYstuvVHnSpHD16NLd1qYs4++DhXntplyE78rOq65UuV6C7CL8Yn4FUd/TMmTPDma1Ai/b77iaEnfTnIG0IoyjrLm8Sp3Y4ffp0fjWSKvfpAlR8lH7EKyuU4Zr3FXbiTvcX7Nu3L5xjurnVq+P0Ag3nxEOBljp26Cr+6KOPwljunDlzwjDbxYsXg2xctmxZbqt9Nm/eHIY0U2UbvxnOzJR36Fov6lIv4rbbbgvnOvIb6FZHdu3fvz/cIxeQYU899VSI75YtW4IOcerRSHFrLBJIbCvUJcD1HLKa0qi9sSXkdZRl7E4hU1q/xkIx10GVHJQYYWxCv8ZJqPBpTK9uwXacQYFxYRSNGiEcVE45uGZOSB07cN1114UyTFmm0oqSRdmWjZs3gUlsapykWLhwYX6VRo21M2fOhLOYMmVKOF922WXhXMWGDRvChDQ1ujQxj/9tS68w7u3Uo/HkNKuINRmiCptxVBNtB038qmoFkvGBSRHtoILWSViLwE21luOFE8qoihNpQ5i7XWtVQasD32X9+vUj8ojtpamDvrHj9CtStPZA8XBwTUu2jp0YVgzbtm1b6+23385NRqPyRMu8DpTJm2++Ob8bDe4gW6hApKD8z58/f5RSRZGXvWchXufPn2+7MtJUhkwGGituPiQtaaDrQzXHMuwHo9Yl6FJtohz1LrVWKW/NcgfNjtbsZ+xJkWG/zqxxq/hsWLuFHTaAupWLsjiRhhp6UKWgmyBsIK51x/A94wKu2jQQXsX33nvvDWdx6tSpcG5SUXCciQDll7Lz29/+NnSdlylDygcK8/jx47nJJZDF6vKmrOEmMkyzt1lOlFnhkh/Yffzxx1svvfRSuAe6tLFjV1R78cUXg9zR0qoKr32vCMLBSmgvv/xybjKEKhM0/ggH7t9xxx3BTCAriavLhARZ7S9gLmujyQ3xUTTRqcheJthHmMf3HCL2s2iSRGwvywD5k9HhwK7AHZnbdyyx24QXu9bMTgTTwSQL6z5H7Fb8XGYpf4vilCIVZnvPUTQJRO9yLgL3yp7b9En5o/AUhcEZP/guTjnkX44yYjvkddKWskHZiWd/F4HdlF+YqYwxuU0T3gT3KodMiEvZ0YS5eLKYJs0pvHUXYiFMsR/CupmanEb4UuaTGdIKfD/uAqhVMk7Vb2PIZVC7ZUyrFxO8yB9ZIeuJ24Qbt7NCPlDpPVlw2dBf0CrmP9pMKpuorVFkAl30EzmO7aCy2LirfLKwaNGiMF47SKC0qWz0AmaJZy3/ro+hg1bjiycyOo4zGrq+KStZi7R0EZRBJmtph4VfXGmnccUdQU2PWg1Kqpcz3rsNYWZ8uVuzUWNwd/v27WEMnTTqFozLMU/hyJEjXkgdpyaUR3bWYo7LRFLexIW4Mc7+8MMP56ZOjHeVO41Qt3Y38grDEUye8f9u9zcuG/oXZmx/9913E0bJaQKcK+00KouuuB3HKcVlg+P0ByqL3lXuOI7jOAOEK27HcRzHGSBGdJU7juM4jtO/oLJ9jNtxnFJcNjhOf+Bj3I7jOI4zgLjidhzHcZwBwhW34ziO4wwQHSlulr+kz90e2i2MczdX2OoVhNOGvwzFV3GMid2yy4Oymw5mLDpSBashYXcQ0k8QL7slp02Lsl3ZeCdeRjV2y3EcxzEwOQ3MZS2wz8HuLhZ2rtEz7WrV79idvMrQ7jtxnC3a8YfD7pImM/yykEZ2Vy3uZdea9zPxDm3EW+HXdRxvwMymkUXv+W5h4w/fwXGc8Udlsa0WN60oyATvqOUq2SCedb4nItqfW3tjN4G0gngfalriFtbrZpcsWL58eTj3M7SsWWucb661xrUn98yZM1sLFiwI13bfdKBVTY9C0drqmJNmbPYySD0PjuM4vaax4raKZtWqVfnVSBDgUlQTCZQJlR4qJ01hNx/etRuX0IXMBvIxbG2J3X7fdAOFumbNmlDRsGGts/Y4CrlqC0/lr7hy4ziOM5lprLjVcmKjiTLFgqKyzzVuq8OO9Wr8lwN7qfFRayceY8YtPbPvCPuM8VS5H9sDO25vFUYcRgvjsXp29OjR3PQS9rnCjpmUNsqPZ9Zv3QuUpH1m0y9+j6MuNl6Eyaa9jX8KbcepnghRNT5N+rEbWBXkHyoFpFMqv1SFz3EcZ0JCfzmYy0Ls+C3jvXXR2LDGM+N7YNxYbjM2asd6ZVfjnhwaT1WYNO4c34MNN+Z2HB4Ya9U916B7O86sMNq4yyyOmzWzcVHcbJisH9Zc78tM/iq8SgOuFW7gvgk2zITFpjN+F1FkR+9btxQ+7uOwFrkDiqtNI/uO03s8nR2nP1BZ7PnfwWgpqWWp8c4lS5aE8/r168PZkimRUV3RmdAeNRZ69uzZcN60aVM4L126NJzVFZ0ptREtVsH4NO5nCmF4LNlCTwHwHHbt2hXOKXAff0BxS8UphpbkjBkz8rtqFEel2+LFi8OZFq/Gf+kJUat06Ps2J6uEhLS58sorc5Ni7LhzHBe+Fd+MngT27yYtSVfeIX2UxmqZE178To1nX3XVVeF8+PDhcAZ9G50dx3EmE40UtxXQdfdQtl3Hcdc6Si8W1E1RpUAC3vLxxx/nV5dgwhSgPKrGWEGKOcXp06fzq9Fx6yZxlzrKEEg7/EVJAoqvqpu6KWfOnMmvRqKKUxFUAFDIHFLUdG1r4hqVDNIWhQ2qeL311lvhHGPzG+5Zdx3HcSYTjRS3xhyhG0rXaQYKWsqQQxUPlKQqGJxR7v32bRg7p8dAPSJFFQLHcRynnMZd5bYrWJOTUmjikFq4KWhtddpSVYsthbqUO6GsO9bGramibBJvxdF2F8fgHspc4VXLlRY4ijw1bNAJTbr6aV0TdjsEUqc73mJ7Epjc5pPTHMeZrDRW3LSY3njjjXDNuGosPFFgCFX9X5nxTrXSpTykgDR22wnqetVYtMZ5UXbxuHgdpIA1e77oL29g3Zei3LdvXzgDXdp1FTot0iK7+t84XeZKQ+xqdjvpLZTuVCrUHQ3qXu8WVBRUoajqNmfWedytTT7ifYXv0KFD4Rz/d/3UqVPhrIoO8dbQAd+obvo6juNMGLJWWsBc1iZr3YX37JEJ4/zpSOzMZQ47gzh2J+VuyiwT+uF9zbrWgV8W+4zDzlAG3Ga2s2ZA65D7kAojYCc252z9IE2sHfwB65/sW3scSieeW3ObznHYrN/WPEX8bvydOGw6WPSu4pOCcJY9r/JH4bH5xYYxNRPd6S6ks+M444/Kou/HPQmgVcrkr7oTCuuCu7SaM0Vaa6JfU6rcp/u823FyRuOywXH6A5XFnv8dzBl/UNrdGJaIofs6a92HrmsNUXQTzaFIzR5niKadpWcdx3EGHW9xT3D4rkeOHBmx1Gq3QYky3tzN/MOYP39/S4WdsX3GzduZw+A0x2WD4/QHKouuuJ2uQIsbZdqNrutuuuV0jssGx+kPXHE7jlMLlw2O0x+oLPoYt+M4juMMEK64HcdxHGeAcMXtOI7jOAOEK+5xhP8pX3HFFa2//vWvuYnjOE59WEnx1Vdfze8GH+Li8rCanihu/srDILo9MBPxMy3d6TiOMwj861//Cn9HlAzj+h//+Ef+dCRaW1/HM888kz8ZAreowFs7dZQXf8M8cODAiGWCUeRyC39xOwa3tYcBbqTslEH4q2Q2aaF4cy5amvj6668fkW7E5dlnnx21lLYTwaxyMJdd4dy5c2G5y/nz5+cmI1m3bl3w87333stNxh/CYpcLdRyn+7JhIsByv1pulzNybtq0aUHuWeIlkTm+/PLL/OkQ8VLLuFPFzp07/3333Xfnd0MgvzAHwoT8ZXlgC+a4r7ATj9hOGbxHGKve4bnCx3XKPjpA4bWQhqRn2VLJkxXSPpzDb4YMuknRBwOtva0M1A+QiV1xO85IeiEbBhlkVqx8pdBiRYRMqVJAKNii/QBSoNhQvvE7sT/IsrgSgF8oTCG36ihJKdRUhSCGtJAslay3kF5lbhA3whVXhCY7Skcf486hi0k7gjmO4xTBSn7XXXddfjeEVve7cOFCOAPdw8iUF154IQwVprqkkTuZkgpdw9r5r4rdu3eHZYzjrYHjlQTZWS+rOOR3Q93X+HXLLbfkJq3WT3/60+AWXe5V/P73v289+eSTI7bYbQfSgQWW9u7dm5uMhrgtWLAgxNUZTd8obo3taExEaJyEg4LA+ApjOGRCxkdk346TkDEoCHasR88pHNxTkHCL59jVtpcss4mZ1t5mPEj+4J7G6vGDiRRkYuwoXBx2fErjSQqzHd+yYRG4K7fwE7+te4SL8PIe1zYNHMcZH6SUs1ZkOIO2+v3ss8+CXLn66qtHyCnQtsSs948MojzLrSLYwnju3Ln53WiQkxoj3rx5czjDiRMnwnn27NnhLHBL2+oWgaxB6dddZph0+OKLL8I12zjbdFmxYkWIN5WGMpYsWTK8XbMTEdrdGeaya9AVgrtlh7rK6RrROJEFc7pm6DKx7qlLii4rnnMIxlZid3mOGe7zPm7pGW6pq8t2lTNmRLeSumuwhx26ldQNxT3+4ZbCaMOCHXWr8Q7PwYbF+slzutdwi4Nr7GgugN7BD6UBzxQux+k25C2nHMqeyraFMkz55JnKreSJQHbwPs+wE49dW7CLHcm3GMkx+WXtpbqsochcSK4p3Fyn4mpB5inOnCUDkVm2q74MyTXi7Ayh7zT8tco+XLuUfWBlFpuxlOmsAorHiJQZLDyXW/rYqYPn8iPOPDK3ShSlbt/XoTil4hAXgvg58RGxn0UZlQLIIbATp6t1x3G6CXnLKQaFhqyoUjDIHNLSyjOLFGRKBgjJDCtTUuAHlXwOuRXLJlFkLgi39Y8wxvKnDihv0kkQRlVWUsq8blwnE/pOjbrK6S6hW9Ye6lLuBowTZRmitX79+nBPlxFdODfffHO4L0LPjx492jp+/HhwgzjGh91laurUqflVMXRxZZlmlDtN9p7OMmpr0aJFoQuMrvHUFpWCsEM8dpXVwEM3leM4/ceGDRtar7322qhyG0O3daaoWqdPn85NRkLXseTD2bNnw7ld6NJ+5513Wt9//33rww8/DGZlMi9T8PnVSCTf4x36moIsZ7hg//794Z7ufIYGnnrqqSDbtmzZUnuM3+nDBVhQ2nxIPiIZjokTVWMhej5z5sxwPnbsWOU4UV2oDHQCSj6r0YYCVHcMK35ep5LhOM7Yw/yUxYsXj5qsVgTyTHIqBcof5T5jxozcpH1iZXvjjTeGc9zYYgyacKVgH3+Uqm2sMR7PwbWdn1MGlRsmpKlyo8oE/9vGjMaWxvudahopbjJC3PrstCYWg3tqdTMb8+GHH86fFKPJW8xCpFCgJO2ENCCDxRNDqqAAUUtkEpqUKWdN/KgDGXb16tVhi8qdO3eGVrwmicSoQGtSi2B2KC13x3H6BxoXlFk7YQvZULTYCPCsrAcR+cJk1qLWuxT6xYsXw7kMySz5R+UCmWYbI9ihobNs2bLcZCQ0PGKZj3xWryayrQrk8/nz52tPbIvpRiVmwpElfsBcdgXGaxi/YExDkxosGu9hXDdGYxtZ5shNLoEZzzQxi/Eb/LBjJNxjxx6EBTSOnBoPxhx3GIth/KVovFxjVKk4yExx5lphxV3uNVFD7sdhZ1xK4zqc7T3u8g72hMysO47TLchbzkg0LhwfkjOAHZV15FQ8Xwcz7EhWYBf5pneKwI9Yfkm2yD0O3IplguQJ9rFDmGJZwvMyWYK7KdmcQvJZcRSYE15ko8IuOSmIi01P51JZ7IniJsFxzx42o8XPUpmAj20zucAu70hBpjIZmYSZmXKfazKHKgQcqcyvGdzWPTuBwr4TxxG3FTZrhj0OwsmhONmwcMhdFSbsYk46YFfYd/AvdqdugXKcupCvnEtI9qQOKzusPJAMsqC8JFso75T7WMGlQFbE5Zz3rH9cpxpFYGVa7CfXKZlqwe3Y/yKwF8dbED6FI+UfaVYWjskIaQU/yW/CeEV+Oe7QfcN/HuleiaELnPGVfgmr40x0+kk2OJfkI8NuVRPiBhWGFLJGy4SOYzuoLPblymmMC2c1wfzOcRzHEZp9zr9NNI490cha2q2tW7e60i6gbxQ3E8CoTXAw6eOJJ57In4xEGXWiZljHcZwqmOjFP1TogZxIspC4ELcrrrii1sTkyUrfKO7/+I//CGe6Rz766KPkX8DIpHSdwPTp08PZcRxnMkKr+7nnnhv1L5RBhrjcdNNNpetdOK1WX45xO47TP7hscJz+oK/HuB3HcRzHSeOK23Ecx3EGiL5S3PwFgEkJdhvLMli6T1tcTjaYwEe87ZKDKbOmaeo4zuBAmWdi70SBuLisqqYnihvFoRni8cFyfswaJMN1yu233x42qp9sqMLC/9lFysxxnN5BpRhFw+zuojW7kXNUnJF9VTPAKcPIRtmtgvJ+4MCBsN63qBMmUdc/zfSWDOe6avlonuOm3CZcKQindYu4PPvssyFuTglMTgNz2RVYgYdVcexyd5xZLQcz/GNVHbtqTzvInU4gTFq5bFDQimk23CmzFKR5p2nmTB66LRsmCqw6ppW/UmUOuaJlPCmb2C0qd1otEXeKVhqz4C4ri8VUhUk08Q+7Wr2RM/Kbd8tkN/FU+LhOxZtV0eJlTgF38SO1cuZkR2WxZ4obij4YkBnws9Ml7XCjyI+6EJYqZddvdKK4KRCdppkzeeiFbJgolJW5WPFgB4UXg/xBUdVR2IBiwx2WTE1RJQea+IdbsT25n1K6wvrPOc5DuFEmg4hbVeVgMqJ0HLcx7o0bN4Y9YNkyrqgbZSygK2sydbfTLeXdUI7Te+hStrDLX6Y087sh6NZG/rCfd92tQXfv3h224WxnVbGm/rFbY2xPO0JeuHAhnJtC1ztbfO7duzc3GQ1xY7dH4uqMZtwUNwusKGNrb9bU5Co7VlI2XkKG1FgSismOJXGNmR1rwl0mQbBHNrB9J88Y9wGe23Ed66YNE2F+5plngnkKGyeNd3FwjXu8izuYxZMyuGcMSM+rxqxSWP9JNxY3YNtTu58uZw7sAWkgM/mpNMSMM2FTWjmOUwzljjIDmzdvDmexdu3asEUm8ouyVaec79q1qzV37tz8rhnt+BcjOYg7RfDsiy++CNfs923trlixIuy9nVpky7JkyZIQVydBaHdnmMuukX2s0u4QdaFwpuuErhHdC8ZrNFZClw3P6eoR3PMe7wPdU7Ed3tdzbTOHu6BuH+sndnhHXVEKm9zkmR274v0Uek/hURh4HzOGCfBDY84KEzA+xnN1FeEf76j7LRXu2Mz6b+1xb78LfsRmhMu+Z8fUeEZYFR9nYkM+cNKkyqFFzzniMqNnVg4gJzAr6oZWuSwre0Vhase/FHWG2pDV2MFtzupux5+6w6PIQN4nrM4QpAf0zd/B6H5555138rtLsEOYNnmnyybLBKNa3HSpqPuGVnKWMUJ3EDVDWob79+9vLVq0KNQws8ITlk3NMkNhi5HuGd7BLu/wLq1Udan/8MMPw91E+Jtl/nAdY+N01VVXDYfxscceC+dbbrkldAlR86R2SZgEMysZRmBpV8LwyCOPBHNqqnUpStOYVM037oZTfElTnm3atCncO45TDGUQeZspuyDL+CeM5NfRo0fDmVa45ABLfSJ3nn/++fAs5uzZs/lVc9rxL4by/8ILL1QuSYqsPnjwYIg7Z+7pqaSLXr0O9AbyLyPkW6rXcsqUKeHcSZwnKo0Ut+1C1dFJdyljPjBz5sxwTkFmv/nmm8NHptu4zt+dUIhw4sSJ1vHjx4OyJwPFhxRpzOeff97KaqvJd2DevHmha51MRzcT4/XdhspFVkMe5T+FYDy49tprQ2WG7QTp9rOVJcdxyqFBQSWaBoCGBou4++67R1Tie00T/9i5EeUbV+yrQOEjM5EhQOWFYcqnnnoq+E0jBRnv1GPcWtx8SH0olEAR2LnhhhtaX331VcgwKOEqLl68GM4zZswI52PHjgX/msC4TBHUGKlBT5s2LWRGlBm1yW6jGnI/cOutt4aKBJNi6Hmglu4FzXHqE1d01WCJexCnTp0aZEu36dQ/GimLFy+uNaktBoXPhDQpfFVe+N82Zsj1Jr2Jk51GilvdPvZot9XFh6T2Scu2qPaGMqRW9tJLLwVlWTfDvPvuu0Gx4C6ZFX80IU2QCYuULe/RsqdlaTO5JtNhzvWnn34alBl0e+ETwk+lgEkkqnRw1iSXbjN//vz8Kg3pRUUIZU0NGfte0BynPirH9CDac7y7Fz2RkjUxaoyocdKEdvwTlHtkqbUXy8ciGK6k57TKjyIUZ+cSPWtxk0lPnjwZzlbxaKY0rTbGhlevXh2egTKjxlN//PHHcP7uu+/CmXdxU9eAgsNMXfZkMI6333473JNZUDJ0Pc+ZM2e4i5/ZilQEVPHATxQ5765atSrUQNWy1DvMwAQyK5mW+MyePTuYU2tNEccJzpw5E8628NkxZKCyAoxta5ybMzVeSLlb14zarb6LZpQy3qXvRfxkvm3btuHxJ7rUeEbFhnS5/PLLg7njTFZS5QuQJZRZypHKGrOpmX+jhgpljoYLZUzyi4q6ZFAKlT2GAIsoClMd/wgn8syOORMHGlAckoUchw4dGo5LEcgL5uu8/PLLuckQthJBWtHwueOOO4KZoMeRuFb5MSnJWs0Bc9kxzGbEvdSRfYgRM6yFZjzqwA3IlMzwe9hhRiIzpTW7WjMjMcMeM5/jBQOwg7ncju1oZqWd7chzZp9jjtvYwR0gbMx4JEzxe5ZUnOK04V5x1KG0IY7yg7PSJOVuXTPAXe7xV3EivvJLcSXevJO1sMMZOwqrfdeZ2PC9ndHE5damE2XDPucamZGCsiX5hb1YfsVgH3spysIkyvxTuZdM4xy7p6NI7lnK4lMlQ5HTdfyYTJBW4PtxO45TisuG/oJWMfNq6EWcqK1RWurqKfUW9yVUFvvm72CO4zhONfobF0NXKPGJSNbSbm3dutWVdgGuuB3HcQYM5u4wV4hJtxNJeRMX4sY4+8MPP5ybOjHeVe44TikuG/oXJukyeXeiKDkmy4Er7TQqi664HccpxWWD4/QHKoveVe44juM4A4QrbsdxHMcZIFxxO23DIg4sRKPtQIG/cTCxRAvkOI7TO1g8RePCEwHi4rKjmp4rbmYJsvKOdoFBqGupvF4t3+mMDex0pB3THGeygQxD0TC7WysNxlTZ0X78qYN3y0B+HjhwIKz3LeqEyVLXHqubUUEnXPHy0Sli+0VxwX/rFnFhpTXXDeX0VHHzQVgo4M033wxLeDKozpq1t912W/gPIkK/k93FJiMU9H5JM75lvMY5/7vEnE1JHGcis2PHjrAdJouEFFFlR7tlxVCuyv7DjHKmnNHi5n/dok6YBAq7jj0aXzfddFNYkhQZzmYh3Jf9DY19FlgSWZMaU4oYWfbggw+O2IOCuLADIvtAEDengCxhA+ayK2jpPJa0Sy2NiRnPtLynU49+SzOWNCxaftGZGHRbNkwktKwwy4gWUWSHpUDtUsoCs507d+Z3o5FsZSniFHXChN9a0rnMHhAe7Foo85gXYd3lzL2FMJbJDeJGHFO6YzKjdOxZi3v37t1hV65NmzaNqBEKzHjm1IdaKztzOY4zMWAFtFg+0tK03d8xyFa21+1kVTFaxGyTXAfCc9ddd+V3Q9D6brdFTEudVvvevXtzk9EQN7Z7Jq7OaHqmuNl9C7QLTApWyLHbgtL9o7FwznbshTESulYYI6cLnueMjwAZQc94F3M7wcFOouKa5xp7seCf3OBMeAD3FTbc5T2eK6w6BO7IrKhbu6lfpJXGkxctWjTKP4VF70EqzeSnDpvGMovTxUJhlV8Ks4XnvG/dVVxJd8JknxFfvo3Cxbt2zEvv8oyz9RN72OcZ/hJXC+mgb8271l/HGW9S2xSTZ1HKqcaOQLbOnTs3v2sO5QDFW2ebZMorDbBrr702NxnimmuuCea2rFqy1nTriy++CNeHDx8O94Jd0tgSuCyOsGTJkmE94kSEdneGuewKuNfETbpT6I5R9w9dRbyv3WHs7l7sKsMOV3SlAF0u6nLi4Fr2AHvc082sLiieYaZdxrRjlnaykX/aGUtuEB7scE93j/yKd8DBr9hMtOMXZ3U54a/AjuJg445bRWnG+5x5buF5bGax7wNpSTxJf5C7+EdYgXBjR98G9/UMuJd7hJk8gH0oSyfd63viBs8E8SVt8BOUn5RWTn1sujojUb6zeTqmjh1Bni7Lo+R93FKZSVHmH2UJP0TdsMf+FZkL/EEuYIezyjDlUDK9CslolXfnUlkcLpEy6Ba4V9dNhCt24wxrlRAoI0gYQ9HHRfhLAQB2pGAEZsq0UkIizpjY4x7/LIQFZUVYBfGw9zHt+iVz2VO6pQ7FK5VmILdsuhGmokKieMbfiHdsuiou8p976y5nPdO3Sx28V5VO+Cu3wKa5xu/iI84DTjWkm5Mmzu8p6tgBlbEy4jKQosw/8r+VBXXDHvtXJxwxKG87Vo4soXzjTkqZt+PHRIf0gEZd5XT70u1oj6Ku4CwD5lfVnDhxIpyvvPLKcBbMPoezZ8+Gs7BdLNpQPh7vyWqVjcaDWRv35MmToeuHrlv+6pRiypQp+dUQhOXpp58O3dj6ywPdQPfee2+4TtGuXzFKN75nfKxevTo8E3G31AMPPBC+EbNQge9IF3jRuBl+0TUWfyPeKWPGjBlh9mtWQEN3P99SYePbZYIkGX6GUKrSad68eWGsjjDQ/bdx48b8SSvMls0K/Ch3mbHqOP3Ihx9+GMpIr6CMPP7445Vd1JbLLrssv0pT9VwwJEZZ1Sx6ZOU999zTeuqpp4Kc3rJlS9tj5pORno1xKwNqvLUOFy9ezK+GqFJcFjKGZerUqflVPXif8VIy1+LFi1t/+tOf8ifVWCVIhkTZ2LH7mE78SlFUeSojrnDs27cvTBjpNlQEUKJZa7h16NChMD6PEhbHjh0b9e1EVTpt3ry5ldXaQ9pjh78e2jG3o0eP5leO0/9Q4VdjpRdQRn7961+PaHjJvKgRxjg45SsuS9xjXmecHDZs2BDkixoGVFKASXiYUYEn/k49GilulFHcgilSUKtWrQoflj/TFwlmalgodlpl8Prrr4ezOHPmTDjPnj07nFPMnDkznN96661wFqdOnRr1H+MyHn300RBOWmRUOppUGqwSXLduXahFltGJXxalGy1RW0GiAKYmjsWowkGY+RZltX3VrJsqQ8KCcmb27DfffBMUuCbZ8e1oxacmpHFflU5UADDnP5+0ruGDDz4IZ1r4CCTSQfmPs600OE6/oAp/1foHKvNxI6cOsezmgO3bt4frIllOGWOCmYX7MnlhQTbR61bXfozi7FyiZy1ualEIa1pbCGarWMikCOfTp0+HjIpdlAfdKFI42HnhhRdCplLXjgSwhcyAgl67du1wjZEziujFF18M91ZwC11fuHAhnH/44YegRDDH7/fffz+YA2GXvSKkBGlVlv2VA9r1a+HCheFMoVU6kW64ZWvStGo1m9/GOUYVDtKdcxnUrKkVb9u2bbhLizPCBmUphSiBYuPAM74J/qkGD/p25JE5c+YMh5+ZpNirSifMcJvnVO6YOa6eFhb8gUceeaQ1ffr04C5nWu6O0y1S+T2mjh1aoAzvVYGspFKqIcIUdfwrgrJEObL/0GAIisq3yj2yh3saZ1VQRmm8vfzyy7nJEJJPNLiopCNDmOluoZFAXNVKdwxZTStgLrsKk5GYNJQJ6+AHB7Ma44lXwCQJTVbgzOQkwaQKvc8zC5MtrB9MgLATGvQeB+5o0oM1Izx6n4kSTKTgnmfcyy5+F02WwJ6dIFVEu34RT+KGXTtJjHfkHs+VtmVpJnCT55o8VobSGfsKA98SM96P05XviRnh0XuEQzNMATdxQ+9wredl6cR7uI8d3JQdi538whn7TnNIP2c0tnzpiKljByi3tlyUQT7G3RR1/RM8t+WCckUZi8sSYSOM2MePumEts1tWdgFZkDKfzOh7+n7cXYT/DLOoQd1xn36Aluvrr78+XJt2nBiXDf0FrWLmc9BTNVFbo7TUs4rChI5jO6gs9qyrfLIhxTdIShsBQDfWfffdl5s4jtPvMOTEMGTWIg1leCKStbRbW7dudaVdgCvuDmBshhoQB39t0Jh6v8PYMmFmzBch4BuCOM5gQRmmh4/5QxNJeRMX4sY4O38HddK44u4AZlpPmzYtTKDgb0llfwHrJwgvUGMvWy/YcZz+hVb3c889N+ofNYMMcWHnMeLmFONj3I7jlOKywXH6A5VFb3E7juM4zgDhittxHMdxBghX3I7jOI4zQAys4ub/x8w85P9+dcCe9qauAzPGmbHJmAKbWLBCl/WPlcAww047EBZmhYqUe536IQgzYSfNHMeZOPA31DrLG/cDyDNWzHQ6Z8wUN9P8UR7jlcn4XyA70LCEZhWElZmN27dvb507dy4obpYytbA+uNbc7gYp97rth+M4YwuVZmQelfQipaUGBY0E7NWtYFOpP3DgwPASy/orFe5wcG33ACiC96gAYL9OIwH7+K1GDQo5BfGy8p5/3bCHBHHEDacDmFUO5rInsPwkfrBsXhlVzztBywFWwVKrRUsKWnCrjr26pNxrx49epqEz+ahTZpw0LPWrZT1TS+6ypCdLjGppY8nJqiWIkVEsCWrBL7nDGTmA2yxjWgZuYbeurCEexEnLDqf8YDnTOHyCcHI4zVFZHDPFzYcmU+BP0dq1ZNZehkP+V4G9OhkYt+rYq0vKvaZ+9DoNncmH56fO0Br+KcWdWhccJZqyK7SeuFXu+BHLVflr93woo66swY7syQ/OgvBJsRfBc/uOUw+VxTHpKqcrJcuMoesZUt3ldJ2wIIjTPp6GjjNY0EXO7nyWTCGHnfiK2L17d2vp0qUjlgOlGzpeblkLQrWzS1gnrFixIuytrV0dUzz00EOtTZs25XdOU8ZEcf/hD39oPfbYYyFjocBTG1owtsKC8sDYCfd2QhljNYynaHwE5R+PrzA2hJnGeBiHaQJu8R5bzHHInSL/BM80RoWfGr8hnsSDsS3iwXPC2HSinAW3Nb7EYcOUSkOw4RC4Uza2hpv4w3tc89y66ThO57D9LIqa8WWVbVYNK9vzgG1v586dm98VIzlUVglohyVLloTtfHGfrTez1n/YVheQMTyvWkWSLYqRsZrs6zQktLszzGVXoTuHbhFBtw1+MZYTQ/eLDQdjJNxzMGbCO3QRaVwFc3W3qItY3UIpf2L3i8Aeh0j5B9xjLjONT2msSe/gFuGjC4xw2XhZZNcSm2nMjG4odUnZ9MWuddeGw3a/YQ+35A7X2CGdQe/gttKUZ5ilvp0zcbH5yWkOZTAufxbJKspcVdmSnLNyqAjciuVJGbhbx76VF8gHyQxt/VkH3OB9lyXNIM3COfxmyKDb8IHtx9EHS2WQWOmAzHjPQiHAXBmYTMM9GVtwHyur2P0U2IvDF/sH3Mf2GK/CnPCqwMZjWJAKS8q92AylT5oKhUuk3I0FhxSwTSuIKwGx32DdcSYHcX5ymhGXvxjKI2Uaxc1RNAcI5JaVQymQPyjRuIyXkSrvdYn9kxKXm7H8hrI0cdKQZtCoq1xdyfZIdR0LulLopmXnLNlnRypo2k1SNl4CdC0NxWuou4Yu5PHglltuCecTJ06EM0ydOjW/6hzSk640urXpXluzZk3+pD7Hjx8P53jLPMbHs4KX3zmO02soz3SXU6YZ5soqzuGvqJ12IW/YsKH12muvjdm2mPjHhify78477wxxyRR20AM8d7pHT8e42enl6aefDgrVHlltMTxnkkU3YcyWSRsoyvh/12PFxYsXw3nGjBnh3G001v/uu++GfbSzGmv+pDkaAxPdrGA4jlMNY9qMCQNK7+DBg2HeyY4dO4JZO9BwWbx4cek4eTeh8gHaHhgZRQMA+USD66677vL1KLpMI8XNhINYCZdNQnj++eeHFwew8A61sXg2ZScwQYwFVj755JOwj+tY1TRjUKjErVf+UxunZUwNvd19tGfOnBnO8XaALI4wf/78/M5xnF4TLwiFoqN8nz9/PjcZiRoEaiDEoEQp3/TGCSoHvZoEhrsvvPBCa+PGjblJMySLnGb0pMVNS47MMm3atEIFpm5Z7Knlp5on97SedZ1Cf3FQBtb9mTNnwjuqBYJmS8utIjeBZ/YQsX+AgmZ2pYYL8JPj7bffDvdFhQvkdtEZUmYUdHVnU7M9fPhwuKYAcZ9KwziNKNQo6LVr1w6HnTNhf/HFF8N9WXjG+u8ljjPIxOXP8qtf/aq1bdu2EeWQ1in/wkmBPEXuaLjLQkubYUk7NMlB76PkMP8K4R8iManyXgfkOF3ydiiTlj5hfP3114N7zILHnkXxXbBgQTg7DclazQFz2TFMRsA9HTHxc9lhQgOTM7KPHq6tPcwEExrsu0zUYFIEdrjnPe6ZHJFyiyOFJn7Yg/dS/gETLjSpBPMscw5PLLFuEQY7CSMVFnvP8yIzhQU/mY2qiWaaABenYRwnhSMOO2mleIF9B79jdxQeZ+LD93baIy7rcVqmyqFmaRdBGY7LnybFpg47OZb38MMSyzcOKwuK4D394yTGylzO8eQ03ovD4VRDesJP8ptQM8svHcdxhnHZ0F/Qir366qvDZLbxGhLsFObpMCmv3eG+yYrK4pgswOI4juN0B7qlmeNC93PTru1+gPlIWWvblXYHeIvbcZxSXDb0J8wP+vTTT8NM9Kq/y/YLjMO/+eabAxXmfkJl0RW34ziluGzoX5h4+91334V/0vQ7TEh7//33W0888YQr7TZxxe04Ti1cNjhOf6Cy6GPcjuM4jjNAuOJ2HMdxnAHCFXcEi5iwSAFdEvxlwS7kkoIxJpYo1MpEnNvdstNxHKcJyCdmaQ8CjHEzOc3pnJ4obj4Ois8e9oPFz/plj2f+WsGSotu3bw+L46O4Wc6vCevWrQtLr8ZLGTqOM7mgUh/LOh22QUBjgco+8kYritWBWeUHDhwYsaw07uIOfnCuqyhjmZ1aXU0gJ/FbfhSFmTjZSgVLXbOsMm4P4t/Y+gomp4G57AqslMPqXUWr42iln6pVgroBfmjFsDJYzSdekagdtGKQ40wEPC+3ByuikXapw64khozUyml1ViwDZBUrNVq0iqJWM9MqinX2vNaqkzqKVkQDZCn2iQPX+BGvjEZY4vAJ0oXDaQ7fBnrWVc50f2pjRdP+tRPVlClTwrmXsPFHHf7yl7/kV47jOJ3BsBn7CiBvdWRKNCycYuUi/8VmF8W60FplnwF69iysDc7CJvprGGuGZwqytWfPnnBfBK10dlW04Sz7exn7I0i2L1y4MPQu2m2MCd/jjz/eevnll3OTkbB4DOunN+ldcEYy4ce4yZS+pZzjOGMJSnvv3r2jliSla5vtLjuB7ZBRtLHbzKthGVTNtwEqDnfccUd+l2b9+vVBkdL9bd9tlxUrVoTKQtl/tR966KHWpk2b8junKX2nuBlrsWM02tkL7MQxDq6V0ai9kfEwQ1mTiblmpxxYs2ZNeCdVy8OMZx988EE45D7gv8LDgR+CmiVjODwvqj3KbQ6NN9nxJJ5bd/CPcNsJb5gxLoR9zOuOWzmOMz6gVGPFRTlHQXa61Ce7bc2dOze/u8SqVavCjoy06JGVkoNlrWfkD8qdgwbOrFmzwntlsAMhuyISn6NHjwY/Z8+eHZ4hm3hett0z0FJH1najojAp+XeOuewaGustO+yYDuPeGo9hzERjROz0BYyraNyE8RueaaxEY0TY4Rnm2NWuVnXGuAmvHePGX97VeA9n7hVGje9gZuMRj3Fr7MmGATf0nnWHNNDYFGfexUxjSHEYHKfX2LzstA9lt2hsFxkgeVCGZFKRPcyRHRxFfqXgPclbDmRPEVY2I2+RUcA7dXf8wg3edznWDNIsnMNvhgy6SawILXFG1YdMHVJ4ZEb7oWP3sRtnHNy3bpQRu0dG5F1VHCB2K1XgcAMzkQqDzPSe3FEhEMQH8/iw4XScXkJ+czqHslykEFNyJEUsN2JwH6UqudFUMaqR0UTpA/IbPyUrpcRxC1mlhoeFZ1YmOtWQZtCoq9x2+9qu3m6gyQ2ELT5Wr14dnp0/f7518803h64cuo7paokpG1dpCpM78B/Uhd9r4sl6jFllhXRUmrBIv+M4gwFdwkziQqb0CrrH77zzztbGjRuDfMiUbxgqtMONVdCNz3tNu7A3bNjQeu6554bH3QkH3e6Zwg5d6jx3ukffjXGXVQRQ2DfccEPrq6++ar322mutrCaXP+kd/BeRiSDMgmd8ajxgHMlxnMHlrbfeCmPPvWTr1q2hcUHjhUNbfzLDuwmLFy9utM+3xsQ1dk8FImt5h0l4hOOuu+7yCcJdppHiZsJB3PKrmoRQlxkzZoTz7bffPqKGiCJn4haZgdojm69v3ry5pzVXgb/85eKTTz4JEzyaZGaLJm60A7VWJtYRFmquwNlOknMcp79hQtkDDzyQ37WP5OTFixfD2fLDDz/kV5dAedJT2QQaRvfee29+Vw4tcxapopXfDjNnzsyvnCb0rMWNctHMQykcy4ULF8JZGRClyKpjdCf9+te/Hu6KX7RoUege//HHH4M9trADlDvu6zrlB6higX+aaZlC4bThVRjPnDkTzOy7qlzE8QC9r7O677/44otwpjKyb9++cH3//fcHd+VODBUVeOSRR1rTp08PacKZWrHjOP0PcmfatGmlFf+UHEmBG1Tmjx8/nptcgtncDB9SyQeU6rPPPjviP+L8Y8WuiobskSxDXvEuMrhug4wWPb2fdoiSRhVh5H/luEmlJe5tUM/qggULwtlpSNZqDpjLjtFEC3vYSQjxMzvRihnUTELDnMkNdrKWJn0xk5HJGbKrGdoc3DOb3KIZkNhPoQkf9sAvJlrgl70nTJgx+SKOJ+4ojDoEYSRsHLyHXdzBnHDJvuJmwY7CwdkndDhjic3HTnMo32Urkans67DyMAXlv8gOz8pkBe8hwwTP5W8sb6vg3aJ4IR8lCznHk9N4z4bDqQfpCb4ft+M4pbhs6C9oxV599dVh4mq7w3fjDWPx9CZ2+p/2yYbKYt9NTnMcx3GKsRPPNBw3SNAdn7W2XWl3gLe4HccpxWVDf8IEVdY5569fdoy5n+FvtW+++eZAhbmfUFl0xe04TikuG/oXJpYxYbdsWdN+gQlp77//fuuJJ55wpd0mrrgdx6mFywbH6Q9UFn2M23Ecx3EGCFfcjuM4jjNAuOJ2HMcZUFhARQuuTASIixaEcYrpueLm7wraoIP+efaH1YbtqWU7ZY492f+v//qvsPqQhWepg5WB7IdP2dGBXdYib7qgvuM4DnIDRcNKZKk98pFDKbnDoVUYkWt2r31kX92/eGH3wIEDreXLl4d73kNWyo+U3ATCJXncxD/kpdzmQHYWgb+yz7lIxhJ3G0biwmpvKd3gGJicBuaya7B6DiuFxSvycI0ZftpVwrQCGisNaXs4zlpZjOcW7U0tN+xWctau7Fkzu/KZVl9zHGc0lBFnNKzIqFXK4hXKQCs2pg5WEkO2YUeyDhmELKpaOQ2QaakVIiULOSMLcc+uWoY5ZrLHO3X8I4xxHJChReCmwsd1yo+iFeUIL2F3mTwa0j2cw2+GDLoFiU8GIWPHy90BZjyzGY0w8DFTSHnbCoDekRugDIbfImVPqHLBoQLkOM4lKDtOGsmWlOJGWcUyBWUkhcZ1LBvVmChTipKt1m3CEb+jsFnliMy1MlZuVSlJFHwTRWrTRHGyELayCgNxI1wp3TGZUTr2rKt89+7dYbH6TZs2Jf+zhxnPBJttAP/xSyHzqi3qtAQgfteBBfFZhB/7O3bsyE0dx3Hah67hvXv3jlqSlK5tduwCurJj2bhw4cJw1qZKKZCtbDVs3WZTkHjHRLvBEtAlnSnE1i233BLuAf9xi3AVQVzYlpNdwBgS6HS1Nt5H3pM+RRA3NiAhrs5oeqa42REG2NmrCDIumUsZKquBFf4xH/P58+cHe6lxG6FMldXWwrkOGiOyu385juO0C4onlmXIJvb0L1vqk93BkF1lu3MhW+fOnZvfFSNZiFyFEydOhHO8zTBuEa4i2EscWBudLYZZJ71MBgN+ajfEw4cPD4cBVqxY0dqzZ0+hrBfsdiY94oykZ4obBQtVHwfKapcWuRXb11Z41AyZCAF2K7sqmrbSHcdxmoICpLFSxrvvvlsqu5BxyFa1zMv48MMPg8JUS/z06dPhnJLJZbJv9erVrXPnzrXee++94B5277zzztKW9/bt28P+4ExO0z0wmW/evHm1tg299tprQ1yLJrZNZibE38GYhciMzFmzZoVMRSYhszmO4/QL7FtdtjQprVjWHi+TXWfPns2vykGp0rXNZiTdAGVPTwFrjK9bty4oVCoGRVBZwC7Dspy5J36kwebNm4Mdejg1uz01Q33KlCnhXDfOk4lGipu1ZvVXAB3aED2mSVf1ZZddFs5lNTjLjBkz8qshXnzxxdb58+dDJjl58mRjpa0aHYrfcRyn2yBjaFTE49AC2bd169ag5LrBhg0bgpK04+BTp07Nr0bTRF6jeJGVasHXgfjRzb5///5wT3rcc889raeeeipUArZs2eJDlQ3oWYtbXUJ1/kxPZiYjMIZS1C3Ch//ggw/COLfNjN1AYzhM0nAcx+k2yBi24Szi0Ucfba1du7bW0GIVTCBbvHjxqErCjTfeGM5xY4sx6KayD/szZ87M76qhIsGENMlutdaZX4QZXfCMezv1aKS4GZegVWuPorGKVatWhVoc3dhFLWlqWFLsbKoORTO7NbuQ1nU3oftm27ZtIawbN27MTR3HcboHk6weeOCB/G4kdBOjtKVokZdFY+HqbdS8nhhkKgrVvs9iJjSI1EA6evRo/mTIr2PHjrWWLVuWm9QD98omHluQ8fSIVo3vFxH3sDoZmfINmMuuwf/+cJc/09v/X3/77bfhv30cFtnnf4bYAc76D3f8P0ItrGLdTlFnAZay/006zmSGMuKkQfaQPva/0THIFmRgDP9R5j/dvB8f/G+6iEz5jpKdIHkWH9gX/H9a8g7/8ceGTf/rtvHBXclH5HGT/3RjH/fj/2NjTtiQzbitawv+2rA7l8piTxU36EOTGfCDg8xapGzJWDyXfc68HytWuWWPFCl7On71q1+FzBJnKsdxLkFZcUaD/IhlSgqUYKyUAIUWv6+jrDGCQsNvixo3qSOuVKB0UYg8Q7Za+ZdS3DaeyOZYFpfBu0X2iaPCEYcR8CtlPpkhrcD343YcpxSXDf0F3dv8l5o5Qd2e79Mv0BWfVWwmdBzbQWVxQvwdzHEcZ7LABDb+5pW1SAvnDw06WUs7zLJ3pZ3GFbfjOM6AwUQvdtZiwamJpLw1MY91Ocr+8z7Z8a5yx3FKcdnQvzBj+7vvvpswSk57i7vSTqOyOEJxO47jOI7Tv4xS3Pml4zjOMC4bHKc/UFn0MW7HcRzHGSBccTuO4zjOAOGK23Ecx3EGiEaKm78e0MceH6yF2y7a1q1TdxzHcRxnMtBIcWt/VTFr1qxw38mer2zD2Y94JWJ88HR3HMcpx7vKE7Dt3SuvvJLfOWOFK23HcZxqXHFHoLQXLVqU3zljBUrbK0uO4zjVjInijsfG2TO2CGs33vAdrDscFjtezmby+MM15kJmOvBP8Mwq7fhdlIt918YD/2Sud3T/3HPPDV/rABsW65awaYHfNn6ptLHPYzuxWzzTvbBmHDbuLPpvn8V2uY/txNj0s+nOtZQ2Z56TnsLGy5pXxSkOIwdhFDLDnuM4zsDw7xxzWQl2OerslYod2WPLTr3LtZCZzLUvNwfbgorYLL7XHq8c+MmWdZxlR/vVym89wx5gzrXcsMgcN1L3oO3v5K7846xrDht34lq2t63e4SAOvGvvBffa6q8q/QgfdhVem+YKi57JTbDucoBNL9yFOF3B+qXvpOc2TvYdkDnEYQQ9T8VJZoJ7pYeNS+ynMxLSyHGc8UdlcbhENimcEngS1GVIiCMorYDmWsjMClCZSTFK8Vk/JaT1nhSCNeM9vSM3JMwVNusv13JDWHcVbiv4hcIjM72nd/TcxkHxK0Lu2TAq3PZd2cMvGzYpKpCZ4i979lphU1hlF6y7ilMqvRQ+vYvdIjsKn57beMbfS+lp00/vpeKkZ5il0HPFxUmj9HQcZ3xRWexJVzldj+r6ZdY4/p0+fXpEN/SZM2fyq3JOnToVzocPHw5n230rDh06lF9d4qqrrgrn1atXD89c55qwMAueLtJMEQRz232a4tixY/lVqzVjxoz86hJxV2umWMKZLenw75e//GW4X79+fTjjL+nDezNnzgxm7aA0Afzh2LdvX+uee+7JTVuts2fP5leX0FZ57MLDO/aatCJtPvjgg2DejVn/R48eza8udU8r7VPhE4ofYeEdpavetaTilCnscCY9eD9Gaabv4ziOMwj0RHGjPK688spwrXFPhHDWsglm4wnjoigAhL8UwViBgshahuF6z549QaGhaLqBxnNBCqspGoPmOymc3UbKsonSJCzxe3WwShyIm49nO44z6PREcTPBSC1TKcf7778/nJty7733hnPZhupLly7Nr8pBMdF6QxEUuaeWukWVkCKatNiUDmrRdsKSJUvCmcqRejOUXk1h0hffje/V7Rao7VUoUpypSpS+UadphfLevn17uKZSCXYinStzx3EGiY4Ud6rL0nZlxwLRdpmmUJe1utlRsFIiWuQFIS57EuirVq0K5ypslzpupMIfg7InDCtXrgz3b731Vjh//PHH4SyFUBdagVJSy5cvD+c6aNY1aapw633blQ8KWxNstzt0o2IhbK+CrcBpJniMhhFsJQS7IjVckgJ7yitKK1XM9B1h06ZN+ZXjOM4AkLVGAuaykEyRBnt1DpEpqWEzTTbSoUlBXIN1n+sUeq7DYv3isBOdwPqPXTuxytq17lisfQ476SmOG0cRvBeHrQi5FfsdT6iyz+KwZIp+1LeL05cw2efWDezihn3OEYeJdIv9sfG05hw2/YiPzO071lwHYYGqOOGO/ZbWXRsf7DjFkEaO44w/Kou+H/c4QIuS7vc6XdJ8F8iUTkdLyzppaNnTfe5pW4zLBsfpD1QWx2QBFmeo21ZdvMyw7/Y4stMezA2oO9TiOI7TD7jiHiMYl+bQmKszvvAdVHstm/joOI7Tb3hX+RjB5CrN2q7732j+umYniTV513G6hcsGx+kPVBZdcTuOU4rLBsfpD1QWvavccRzHcQYIV9yO4ziOM0C44nYcx3GcAcIVd034vy8TzOw+0lUwc/mZZ55pXXHFFblJGuxh569//WtuMj4Q1tSs97rxcBzHcXpPTxQ3614ziG4PzET8rIkyHC9uv/324WVH67Ju3brWli1bWt9//31u0t/wd7XUX6PiePC94m9ov6/jOCP5xz/+ESq/rOWQWub3X//613C5ooKsZZ/rgpssLcz7vZKnhJFw4U9dP3hH4SJepAFmTocwqxzMZVc4d+5cWEpy/vz5uclIMmUQ/Hzvvfdyk/6H8MbLalahZTn7nS+//PLfO3fuzO9Go+8lsM+9XUbUmZgMQv7td5CD06ZNC2kZL1cMlCOW4UVuqqyl7KXgXdxmmWLKZV2QTXX9AOQD8SBsdeUg9iUjiB/3d999d7h3mqOy2LOu8p/+9Kehdsk5xdSpU8N5ypQp4eyML3/+859bN998c343Gn0vcd1114Vzajc1x3FG8umnn7aefvrp/G4kDJFt3Lgx9HYhLzdv3hzMv/7663Aug+E73P7oo49aq1evHi6XveDhhx8OftWF1jm9dFpOmPi9+OKLrf379yd7HZz6+Bi3EyjqJnccp7fceuutIxo4zCnJWtClFWl49dVXw/Dda6+91lOF3S4HDhwYXuZZsNQzcXv//fdzE6cd+k5xM1bKx2ZMhLMmbNkJUnY8iDP31OD0Xjz+wnO9y/Prr79+1EQwxqDkJu7UHWPCX9zjPdynBpwaw4nDh38CvzDTODF2NRHOuh/Hqw514oWdm266Kb8bAjP5a7fldBynd1A+77777tCCrqpIr127Nmx9jAKX/OmnuSY//PBDUhYuWLCg9fnnn+d3TluEDvMMc9k1NL5bdtgxFsZ2tNUjYz2MjWCHsRHGRfQO4+I81zgr/mh8lmeY2S0jeY5bvGPd1fg6ZowRaSyGMGk8ikPILyF7ioPu7bi+0kDhww5j/9pK0vrFGBXoHjtl8aqibrxId9JYkK7Ys2HW2JaFe4XZmbjE391pD22VS3lKYeUlZZLyWwRuyJ7GxiXXVG5j5HbZUac8Y8/KwSIUHitbALnm49ztQXqGc/jNkEE34eMWfeA4E5PxuE8dykzK2JaUH/YdKbxU5rHKEzu2QFEgUu5aMzvxQmhfaynYVJgVJlUc5L8tNLFfENupom684kLE8zheKoSWpuFxBpP4uzvtQVmJy2OMbaRQVouQWzFWrlVBOS8LSxH4G8uQFJI/yEnkO4fkY1HlwilH37xRVzndtnTJ2AOzbnDixIlwJmzxwaSLdjl+/Hg4x91OdEdlhSS/Gw2TsewGHyk+++yzUZOzNC7F1p1FMKYFCttYEscr1U3O8zhePgnNcXoPcoru8kwxNv77KVTJtbGE8eyscRImqE2fPr21YsWKYblYNX7vlNN3Y9zdqgjExGMtdpY0GSyrFbb+8Ic/BHuMp+/atSsUniouXLiQXw1RNIveorDMnDkznHtFnXj9uWI2ebsw1pYa33Icp5olS5bkV2kkOyjTFuTatGnT8rvxh0YKOxrSADt48GDr8OHDrZUrV/pE2A5ppLhRBHFrGLNuMGPGjHBmoRM7cQxFzuSLdlEGf+utt8JZnDp1Kig1wcxMJlNcffXVYfvMpUuXtvbu3Zs/TYM9/tpgFZQK0rXXXhvOKT788MNwZpJGr6mKF7XzuBBR8Clg7UJ68H6dSozjOKOhQVA2KVSV7ZRcK3ov7i2lZ23RokUjzHo5uU2Lr/DXN6dDMuUbMJddgfEMxlo0vhHD+A1+apwXZBYfGp/GLe6te/JD8Aw7dnyI50y20ngOZ3uvsKbCKeSu9Utj1Yz/8pyDazv+o7FhjXlr4pedZCZ3FOaUXzKTHb1TNsbMO2XxIiypsSaNn3HmXewp7XEPNDHQpjNojI54OxMDvrPTOZJvVuYB5YXyJXnEc2SE5B5QDjGz5Y3yaeUYZTl+r9tIDlnZJBSeONzEB5nIO0WyyKmHymJPFLcEvz0wE/Ezq+jImHx8zPnQyuTYse+AvecgA9t7uUtmQZFYd5XZIX5PB/alYK25DS/hwz3ZJ/xx5iTuKDzs2DhB7HecdviViheFlGsp0hRV8SKsRYVchRD72OMeAYOb8bdIHbZi4gw2fE+nM+LyYWUIZUVljfKshoCFe8kXiy2nuEmFulfEsokDeSAUFskU2UfmuTzoDqQn/CS/Cd0k+eWkg+4b/uvMZLOYLCO2zp8/n9/1H3Q/aaWlmEGOl9M/TGbZ4Dj9hMqir5yWcebMmdaTTz4ZEsQeWS03TKToV1DM8VKklkGNl+M4jlOMK+4M/g711VdfjVjNDKXIJLJbbrklN+kvmMDHxJSyv8oNYrwcx3GcclxxZ/zpT38Ks6vnzJkTuiKuuOKK1qOPPtqaPXt212bNdxv+ZsGi/2UMYrwcx3GccnyM23GcUlw2OE5/4GPcjuM4jjOAuOJ2HMdxnAHCFXef41tqOs7kRn/rnEywYmY/bVHab/REcZPg9MXbA7QvtA6bGVPvFB3sE122FjYfHYVn7bNwP8uRNs0M+MG7uFdUeLDD/tn4ZfcQB2Z0Yx6baa9r7Bct6Up4Z82aNSrdODxTO87YQzmOy6KO1F73om6Zj+G9G264ofX444/nJkNrNzDRFLdw08qWIpBRkom8q+VH60AYCLPCzn0MZpJTnFN2iiAcyDP5gfxm8izLtxK/uuGcVDA5DcxlV9CSmKwEZFcBYlUgzOMVgEBL/Wn1H7nBCjyCVXl4F3NW5ImR+7yjFXw4axUfu2JRHVihTCujFb2LuVY7IszEQSsKafUyrRxEWHiue55zn1p6FLM4LfDHccYS8p0zhORL6rByztKkzFtwD/kpGQDIMStLWM0Qv+0KZimQYZIdvMc971aBXeQtYeEaWUfYbVy5tvEhfLGdIiQvcRf5H79DmF3mXYJvHc7hN0MG3YQE56NY9JFTSpAPHyt0wmUVt1ABshlWyrmoQGBepHyrwN3Uu2RSntkMRzi0FCmZ3YYzlRGxn8roccHCnVRaOE4vId85QyADKNMWZECZEmxS5i3Yid+LZZvkaZn/hE/ySCCPrFwqQpUEofdsZYIwxo0o0ikOe4yUdpVMI+xV4ZwsqCz2VHFTg8JduzY38EExjwsAH99mCMBe6sPKDX1QZeA4g8ZUZaYi8CuluCkwsTlxwL7iwrVIZVTZt+mkmq4FO1WZ3HG6jc2/kxnKZErRIgNiGWepW+YtkmexPEyB/EnJJpGSUYD7qZ7PMlDksZJOxY8KBuZFED9kdVmFQ+B2WfwmEyqLPZ2cxiIh2cdrvf7667nJEFojW9tbAuO5bLh+3XXX5SZpGO9gfIhN5rMMNLyQCG7xfpYRwn0Rf/zjH/Or7sA64PPmzcvvhlAc/v73v4dzVlkIZyCM8R7esn/8+PFwBuLzm9/8Jr9zHGe8YfvbeKta5NGhQ4eCrCuibpm3SJ5VyUMgDHfccUd+Nxq29U2NE7Ot8Oeff57flcP7jEPv2bMn7KstJLfjbYyvueaaYF401s2qj1lFqDV37tzhse2isfGFCxeGLUi1ZbIzBrPKmRBh96zWGYXOXtGCjPrUU0/ldyNZs2ZN+LAc06dPbz3yyCOtrAY2IgOdPn06nMvW7u4FZL4iP1VYbWUhq2WG9LAoQ1p3Pvroo1qF1nGc8QMFVPXPj7pl3vLxxx8HGVcF7iCDli9fnpuMhgoHDYxY8Z08ebJ1+eWX53flIHeRw8eOHRuxB/jZs2fDecqUKeEc8+OPP+ZXI/nLX/4S0gWFTziOHDkS3L7zzjtHVTJY6RF47gzRc8V92223hbNa15yXLVsWMrvNTChxbQ4fs337dvoHwkEm5Z4aGLMtm8xe7AceeuihEAdmoQPx3717d7i+8cYbwxkzMrXjOP0Ncqtq6eE6ZT4mVrJFrFu3LixtHPcEWO69995wpjcSpcjBDHjCxH4GdUD2olyRSzSc6sxkLwP5Tbqop4KeUxo4hEm6Qihuapw5DRU30/TV8tWBWRnqLj9w4EC454yCVmbiIymTUjOsAjtsrLFz587wkbdu3RrMx7qlLYhbEakwEXYqHhQc0m/Hjh2hS4kCoRY2aeLd5I7T3yC36nRn1ynz7YB7KN6ybnpAKb733nvBT1rOK1asGFaCaizFfznlPgZ36OW0w5+XXXZZOBdR9dyisLiCrqbnLW5Qd7lax9SgyARkXGqsKKoHH3wwPKuLarnqgtJHf/PNN8N5rFi6dGnr8OHD+d0QqswU1aYpyIzzU4vduHFjKICbNm3Kn7bXTV72v3bHcboPXcZVc2pEVZlvCjKG7vSq1r5AudMljf8oX2QWc2/qNJYsyG7GxgVyCkV+9OjR3GQI7jEvkmPIfv6nbVHLerwaYYNEI8WNsuXD2wOzKtRdjnKmm1yQ6ekuf/755wu7yYuQcmSCGpAB6TbCPQpFChSbuqu6BfFh7MUqTTJtndo071D7pWKjcbJ2uslxh4JY1l3mOE532bVrV+uBBx7I7+qRKvMpkGdWplhoAL3//vsj5s4g84rkXowWX6ECIVDmVq7b+UMxvGvlOPGIGy/cl8UP2U94bRzV81qkC2bOnJlfOXykgLnsCVntK/hh/06hv0TEfy8Qem7/wsX7/CVB7tn/9/EMtzDnLwTfmr+b8beLLLMMm3Eve1Xgblk4+auCwkh4CFvZ30MIg/5bGf89jb9RpP4CorSI/76BW8QrdsdxugX5zhkJ5bFMHsTPysp8Cuym0h25ItkXH5JtyCDurQxChnGvsFk5XAZ+WbmJ/InjhlvYI8ygv4LpHUDOWjO9Q1pwjTnupv6epvhY9yYrpEM4h98MGfQKPhAZIIaMHC8qAGQwwpQ6lJms0raQgcgEso8fZAibWfFTz8ogw8kdHbG/uEt45F6Z0la8isKfSqOytNChQuM43Yb85YwEeZKSWxAr7qoyn0KKzdpHrtgybw/rH+9gJjkkGYadpnKCeFo/iho6qshgj/jGjY9YcQN2lDY8K3KbdLbxm8yQVjDp9+Om22jz5s35neM4MZNVNow3zFthHLjba08MGvzP+6WXXqqchDcZUFkck8lp/QrjKz4RwnGcfoTx808//bT22PVEhMW2sta2K+2ISdvi5n+I3333Xe1ZmY4zWfEW9/jBRDT+8kWru2yy10SEHgf+JcREOZ94O4TK4qTvKnccpxyXDeMLPYOPPvropGp5868hZs4/8cQTrrQNrrgdx6mFywbH6Q9UFif1GLfjOI7jDBquuB3HcRxngBh3xc1YBquZpdbG7RasyMPfvq644orcxOkXmCQ4mWfNOo7jNKUnipvZgPTFxwf/x0NJ22Xubr/99rC3di9Zt25da8uWLWGRfWc0zFylYsP30VKyMXxTKj4cXFuY7Xr99dfnd0OoosR357mWM4x59913W1999dWovNLLipzjdAtkGflb+Zbrqh0LKStxGQLKni0DHFZWpqhbzjqFcMRh06FlpKmEp55zVFXOY50RyxMngslpYC67Aiv/sIoYK+PoXquVsQqOXcUMM9mrA+82sQ9aoacJrBpUd6WjfqDd1YV4j5WLSJ9UfFnRCDusekTac21XOSJt7Qp0pJu+MQer5vHcfnOh5R95hh295/QP3ZYNEwnyr8oMZ5WlojxMuSE9U6uE4RbPdKRWUbQ0KWcpKLd15ZuWYE0dWqEtDr89qsJEuK39olXpJjukTTiH3wwZdBMyRqxg9XHth+E+tlcGmaiJfcB+0ziSmQZFcaNUO/mGEihxfOWuXcYVO5hp+UK+qb6H7OsZUGhTSxripl2CETeaflen93SSryYylIN4aU+VjZTiscuCxmWB8oK8qUuTclYEZa2ufKOMp2QD/gncs+EByndVBQQ7uO9Uo7I45mPcV111VThfuHAhnJtCN1S3d/hKgR9ZJszv+hu6sbLCkd91F21qb1cuYke4rMAOP+ObLlmyJFzLzG4XyP8w2f403nKVbvKmu8I5Tr9AOYh3ANRuiSn5tmbNmrCNcQr26GbbT7q7i4arLE3KWTdgoap4J0jCkCnccE0X/d69e0dtE3rgwIHWfffdl9+lWb9+fevQoUNB5vaqq3+iMeaKWxm6bKlRlLPd2J1rPigHqwgxVv3BBx+EZxorQnnx4TXewztVY008t+NTvI87jBtp3H3RokXhWRGxv7iHmSDM1g+uFS47rqPCauMNuMWyf4w/M4akMS0O7oF32M4UeI/7bkFYs1ZCfncJ9uRl33C49tprwwH6vjYNYO7cucNhtPjiCs5EQvk+a32Gs6Cs33HHHcmtfnmHMWDk2v79+4PMQaaU0bScdUoq3FRCfvOb34RrFHZclgkbCrlsuVLkHg0kDmTurFmzfLJqHUK7O8Ncdg26TugaEhrjjseAMLNdpHQZqXuF7iWe266U2D7YnXforsFf2/WEfRtH7PAOZ+BdwiV/irqOY/CHd4iPwqqwq+tK3WYKF2byV7vvWH9wT2ElHNiXu7yHu8SnLH5NKYov7sZpDUXmGguzXeBAnIiHiLvJochNZ3zpJF9NNsjTcR5GLkgmAOmZ6s7Gni3vZeO8dcuZBftVRypcKQhrVdc+4Zc8rQK5I7nHgfvOaEibcA6/GTLoJmRgMhHKSh+EDBx/FMxtZucdmyFjgR7bRwnI/fiQIsI+90IKM3VAkSKzEMY485L5VEjxI36O4sVdZeiUPzITdezE8WtKUXzjtBdF5qqscOg7831IByu8iL+tvEGRm8740km+mkyQn5F1qpQL8rTN66Qn5a0I3qf8lCnGuuWsDMJVJt/KQLaVVSyAtGiqgCXL6yr8yYbKYqOu8tTfFarGY+hSZYcb/OSgGyTV7WJhrIexT+zytwC6xcs4fvx46JqSH/aIx2XE559/3soKT/Kdupw+fTqM9VrYDEBdPfhBF7eFLqUsQw/MWM7ll1+eX40m9YzuMrrQ+e5z5swJ8b948WLoClu2bFluawjvJncmEhs2bAjdx3acly7yxx9/vFFe533kCGWmiCblrBfQpV82PwX5Rtd/layPoVs9U9oDIx/Hi3FfgCUFiu+GG24I/++lIKCUqzh27Nio8Z4qDh8+nF+1D+NJZZksFaZBUljMKUhVnDDjWQoKKzv6UAk6efJkqOBkLYEwvg+MzS9evDhc14UKosb0HaffQEGTp2NFxYS0X//61yMaOzIva/igkCkzZVSVs15BmGmwxBPRLG+99VbbE2ZJxzK3nYaKm9arbZlyFLVo24XJUPfcc0/YOH3z5s21amwzZ84Mtbt4QhqFyd5byBgon3gmY5NMrwl2ZFDrBhPIuMcPFHscBgrZvHnzwrUmdfUrqlVbAaPrOjPCUbbbtm1rvf3227lJe7PJ//CHP7T+8z//M79znP6BhgYyyMoOyZVYXnKAevuK5Oc///nP1kMPPZTfVZMqZzG28sCB/NPkWx3IzCr27dvXevLJJ/O7NLt27Qr7ibcDDbZ77703v3OSZJknYC67AmMwjLcwzlEG9vBb9hhz4V7jJxq3YTyGa+Aa+7yrsSLuec8evCf0XGNNGkeK39HYisKBn4QF+zGKo31fYQX5gd96H7cwUzji+Gpyi9ziPY3HK/4gM7mjMWrueQb4KzeqSPkhcFvpjVtcy48iiBdpSVzjca7U+JXSErctmOM/z5zxgXzhpFG5i4+y/MpzyS2grNjxYsogMkBlG7imLMXlrqyc9Qorv1IQjrgcC8lugbyTzMFN0iElH5whyDvhHH4zZNANUpnZZlSLtSOFZxUXGZPMSmbRhDXOsq8MxJlJGXKLa2VkuadDKINhhvtkGOsez6y/KVBk1l/rBuBHHK5YkUppEl8yMWlFmHWtdzlIjzg+mOEPYcUNxVv3RWkvrFscuB+jb8BR5h5hwQ35a9MCiFOcnnEcU4cX5vGD9HdGo3KbOmIFa+G5LUOUCcoV5kXllXKEHblbVc56BWFFhpVBGG1FxIJssYrbln3Mcd8phnQC3497gsMY++7du1urV6/OTRynGS4bHKc/UFnsy8lpTvdgksjy5cvzO8dxHGfQ8Rb3BIWJMSxJeOONNzb+S4bjWFw2OE5/oLLoittxnFJcNjhOf6Cy6F3ljuM4jjNAuOJ2HMdxnAHCFbfjOI7jDBCuuB3HcRxngOgrxc3SgSxbqmX3mBmt/afHCzY5IQzjCf/FLtqfN04zx3EcZ2IzZoob5YMCfvXVV3OTkbD+NcrJbmixbt261pYtW8I65JMZ/tZ122235XeXiNOMe2YdxofjOP0F+xewoxflk3PRngoWZCjroatcc13nvXZh/XOFETmT2jCpDBo8NCqc7jNmihvlgwJmt68ULLb/zjvv5HdD0Jr8VY2dwXoJW5Ky2cl48vHHH4ft7mJIs2+++Sa/u7QJzN35rjzffvut/43HcfoMehL//Oc/tz755JNQRlGO7LRXpRhRgthXuaYhdOedd+ZPq2lSiacR8Nvf/ra1Z8+eYRmyYsWKcK4D79PocnrDmCnu9evXByWc2i3LKaaqMKe2CJ07d244+9Z4jtN/sAUxjQHKLmUU2Uij5syZM7mN0SAzkZ3PPffccLneuHFjUOIoyW5z//33h32xtXsZfhFuGlNVILN+97vfVW5L6rTPmChuMtb8+fPDVnZQ1F3ujKaom9xxnMEk3joYhY18LFvh8LLLLgtntsQVvDdt2rTCrUHbhUoCFYJbbrklNxlqICxdurR14MCB3KSY3//+92HbT3oSnN4wJoqbvZQfe+yxkDHJoHVqbTEof4232H23Nd6jsRTsyUwTtjBjjEbvyR1NOqMiQbeTfQfse0BNEru8z/iPJs5xcN8U/JK/FOZU6zrVTW79JYyO4wwelHdkAN3RBw8ezE3T0Mpmzs8rr7wS3uHdNWvWtD766KPcRvc4ceJEOM+ePTucBT15hw4dyu/SII9Q+nHlxOkuPVfcjOfQxaNa4YMPPhi6hZoq76+//rp18uTJ1pEjR8JZYzvnzp0LZ4E/ZBzL7bffHjI8mf1//ud/wvs7d+4MYzBksGuuuaZ1/vz5UDAoDITZvifYZWvt2rXB/ddffz1sFM8Y84IFC1qPP/54bqseFD42vqfgEQeU8PTp00dUHlKKnIoEhYc0xe+jR4/mTxzHGSQo78gbuqDZDKgKuteZv8I7N9xwQ+jBLGql2waMDojNUhX/06dPh3NqGK5sojDyatOmTa2XX345N3F6Rc8V944dO8LHFNqpilpmEx5++OFwRjG/9NJLQXnSyk1lrnhsF6UM2FXrVe5Ri1SlQl1DZ8+eDWe9J9ga8+mnnw7X9CDgD24uWbJkVGWhisOHDweFT8HDDcaQgIqJtuCMu8kpZFQk9u/fP+y37/zlOIMJk74o74wFP/LII7V67ZBXjD0jb2gEpSr3gEzDfXtAbCbZ1w3oIme8PiWTne7SSHGnanGpGpsgU9Gyvueee4btU8sE/sKklm1TpHyPHz8ezhMBZXbbgo67yfXMVkziSorjOIMDipNucsaq6cUrg942+OMf/xgUPspbw3jdZOrUqfnVaAhnCumBblYEnGJ62uKm+4cWalzLI9MBXc/toFrmzJkzw3kQoWudyosyvLrHFy5cGM5FNelOwV355TjO+EOlnd63MpibQ2+b5AMKkmE2hszamTNUBlsBQ9woo5eQCWop6FVl6NE26pBvHFy7zOkujRR3qvulrIb1/PPPJ7tyeYfuIbp824EuZFBmZ8LboEFLmi4vMjwZe9euXa333ntvOD1Ts8lVEy7r5aiCytQgV3gcZyJChXrZsmX53Wh+/PHH/OoSmux74cKF3OQSyAirRDkgNkvJEtxFPtveP8LHWHxRGOk1iHUDf//l4FrDf0536EmLm49Mtw7dKkVduUyyoKsHe2pdXrx4MZxtRtT7qlVS8+SdN954Y/gZNVYmnOEO3e+q3TH5ixnYcl9nUDe99Uv+65x6T/ZlB2QmeyyTyszzsqEAZqeTPsrwhN92i6dmk1MJ4h3+Ixm31Imr/mb3xRdfhLMNN5CGTK6rqt07jtM7mIjKpFjJB/27xc7EplxjT3aY4a2yLzPKOzK0qHFklWjRUdTwYg4SMgV5ixzZsGFDUOYKI2aET2F3xpjs4wXMZcdktazgno6Y+DnHkSNHRtxv3749t/3vcJ1lmmCe1TD/nbVM8ydDfPnll8PPs1bsv8+dO/fvLJOH97KMPcJd/I79wgy71iy+T9nBnTgumOE34cF+Eak04MCcMBOPFMRV7+KH4o5fpEvsXnxg13GaQL5xuse6deuGyyPyLCUnMEOOIAsEZT1r8Ay/yzVmvSJrHI2Sq0IylrgUgZzicLoH3wJ+kt+EbpP80ukC1EgZwy/qItKkvRT8VU2z3h1nvHHZ4Dj9gcpiz/8ONllhLLnsr1r8V5L/b/MR7MHEvbJZnY7jOM7kxhV3l2H8ibEnZmYWje/znMlobDJgx6EZT2JCiK865DiO4xThXeXjAMqaxQqYVc/kEmB26F133eWzL52+w2WD4/QHKouuuB3HKcVlg+P0ByqL3lXuOI7jOAOEK26nMfyPnpofR9l/1R3HcZzu44p7HOh08hmbEdjFGZrC++0uk8h7ixcvDt0127dvL1wC0XEcx+kNPVfcTMRiFSBWE1MrDcXFyl+YawUwFsvX86KjzJ5WI2Jm9lhA2OMw1FnwH2U7a9as/G58YDP+m2++Ob9rBmmsigcT6Zhc561ux7kEMkjyjhUUtaJhCslH7GE/tQSphUo3PV7Iu15i44BfdoXLFFToZZ/4lMFqa7iJXd6psyuaE5G1nALmsmuw6g8rA8WrnbHaD2b4yUpjAnPM4pWEcMeu+BXbYxWfnTt3BrN4taFegr+Ei7jYVYXKIJy9XO2oDkWrsrWDr8Q28emFbJioIHuQQaw6BlpJkXIfgxzgGauLIR+rZEi8UmNT6r5DHJARkqPEReGMIczIP+QA9qpkLyut4ZbkPu8QrrGS2YOOvuHwl2wnI1ShD5rKkPrgVnED4ShaAtCSsqelBFPv94qmy/qxTOF4goCQUOkUFXBnYtML2TBRoTzEZQJ5hLKyclBKux1ZJeXdlLrvIB9imU04ed82OiTDkWkpGZ+COMfLpOLGWMrsQUbfsGdd5XQPseUcu1+lNlbH7LnnnsvviqEblq6XOv9v7vcVxwa9mzxmx44dYW9gx3GGoMv4qquuyu+GyBRt6/vvvw8LLgFdznfeeWeYH9KP6zYwFBbLbG0nancpe/TRR0O8Xn755aSMT0EXebwrZNYACGnk1Kdnivu1114L5zIlwe5XZduCgrbwrMOpU6fCuem2lRQ2xqepIHBN5uLgmkLGmIzGejoZjyEuv/nNb8I1SlxjPfihsXvO3DPWpXEvO3bOMypFPNN4mA2/npWNNVHIYncUR+4Z3yJ8ChNm8Tg2fjJJzXGcS6DI4m022SYTjh8/Hs4sh4yymjt37nBZpayN1fycdmA3xKy1PCyvCSsKmMrHihUrhuVElXx86aWXQtypHCCDGDun8q80cmoS2t0Z5rIr4F6Rm+rqsYeIzTlS3SjWnO4buqcwa9p1qzEovauue+3CQ7cOXcJ0BRHueEwXM4462G5yuc+h8S3iwT3uaUxMO36pe5s4K7yE1YbfDj1o2ICwC9tNbt3hWnEkfhyYcY859my64oe9b5rmzmBBHnHqofJjoQyRhirTkiOUR1AZxqxOlzPvV30T3MRO1SF5UQVlXPIWuOZ9dasTR+QPZrY7PYWdj9StYbvJAukWzuE3QwbdAvfK3FRmjoU+ZjaD8JHtvZD7Osg0KghNUSa3/sjMZmxlVktdxU1847GdVAFMuReHTeFQ2OqGn7S2giF2B6riqOf2sO87E484PzjFqHxIrqncYyaFxrUtq4ACw7yOIkvJjTq08w4QbuSrJSWnimR6DHIaOyhujipF71xC37BRVzldqnSJ2KPo7wvZBwnnou4fbcARjwfFlO2wlWV+YhF21GI8vZ+x3eTjSd2xqCIYkyPN7VE13OE4kwXKB3KJoSTkI/NA6D7PWtOl3cEaUmTXwH6C7uytW7e2Dh48mJsUg0zPFPyoYTUL6UJ3Od3jyGzS5aabbip9xxlNz8a49V/fsv8w1gFFUzWBA8VBYfntb3/bV+NEVGo05vPRRx+N6zgO4fAxacfpPcir8+fPh0rtxo0bg7Jikq5AWWk+jlCFut8m2DIBbe3ataMq/CjpkydP5neXwN7ll1+e342GMe0lS5aEa9ygQsA8Hyo4Tn0aKW4UZN3WFhmWVvcrr7wyJsqUwrJgwYLWgw8+GGqJ/cAf/vCH1n/+53+G2iSFdTzp5mxyx3GqQQ4xccsuWgR33313UOZWTqnF2a0ymuodhdisqMcUmLCK0laDg/AqHrfddluYZBa/jzJftmxZfjcaeh8sKHrSg4qOU5+etbj5ILQyUd5z5swJM5yVOckAZNwYKfi4Nhoje/Hszb1794bMdMMNNwy3dPGTGp2dmR3DjEmw7p05cyac9Qz0XAWOMxnVFkDgnvjSFUStsqib3LojYvd0bcOma4UtFf74GcS15tgdUNrHYbD3juMUg8xBviGHKP/xXyafeOKJcN6wYUMoV9hHea1bty7YB+QHcksy06KyWFYmU42s1JFqeOEuCnrLli1BdkvJT58+PYQJ+EfQr371q9bvfve7EEbeoTWNvJdyxwz7VAAE72zbtm1Y4XOmcffYY4+Fe6cm2ccLmMuuwmQoJmJoxqEOJjbYiRjc2+ccqUlPVfa4ts80U5sZmyn3YvuElSM2i/1lcoW9Tx2apGFnk4vYPbD3HHHYeCcO28svvzziPhV+0j6e9BLbwa84TLH/HM7kw797fVSGKPMpeSOQS7LLBC3Ko4V7zJnwJVLlMX6vG8Sy2h52AjCy3cpBru3kV66Jg52Uq3cw5x38andS8WSENINJsx83LfApU6YUdu07jpNmossGxxkUVBZ71lXeb/ztb39zpe04juMMPBO+xc0Yytdffx3+VhaP8TqOU423uB2nP1BZnDRd5Y7jtIfLBsfpD1QWJ01XueM4juNMBFxxO47jOM4A4YrbcRzHcQaICae4+dtX0cIFFhYFuP766/O7/kULGziOM7lBFpQtJDVRYUEX4u5coieKm1V/GEQvO8qW2nMuwaprLC/YDqRxKu0dx2kGqzVS0af80DCgMh0rEylW2UmtDgmxfKzTgMB/VmJ7/PHHc5MhaKgQFq1olqId/4DGD3tNYB83YvDbumuPVNyRRyhhnscVkJSsUvqyhOrVV189JktnDwzMKgdz2RVYIYfVylgdyIJ51apC3QY/43AMClp9rRNIb76vXYXJcerSbdkwaFBuKIcqP6xCyMpfsUyRHeSNtvJMyTnkIs90aJ/uIiRL4+0vcVurr3EU0dQ/QXz0bmqFNp5bd+1BmC3Y1QpxqW08Y7fi1SZJc1ZZi92dbJA24Rx+M2TQTchUKYVJhhtLxc1HH0TFTSYlQ3cKhaUX39eZHEz2vIP8iBWGypSUEMt2xnZ4HitJ3GpapvGr7B0p7xTt+GdBTuN2SnHjb9wYwL9Y6eI/SjelsAE3qCBUgTupcEwm9J2Hv3bRh++ElOLuJBO1A5klVTseBCgE3VjH1xW30wmed0YjhVbUAEEZIXdixYaC4kAOxs9SUBnAnSKlB2WKu6l/MUWKG7dSrV+UtpVZVFx4vyz8hI04VvXE8gx7KX8nC/rOw1+76MN3Qqy4+XgpBcqH1sL2fBhlEjIHXU7KuGRA7PEB+di4hXLjOfb4oGQU7GGH93mGuzpw27orcAf3eC43ZL8u1l2u1UWNW9xbcFdhw14qM9pKjo2z0oJ38Q8Is9yLw8w95o7TDp53RoPMsvLDgixJtTApw6SlPbBbBs+r0h+ZkLLTjn8xcqOOHFQlw8I94UN24Q731i29Y8No5V4Mz5vGYSJB/MM5/GbIoJsoQ9kDMwsFQEoXVEPj40jxcWAPMz6yPjTKi8LBh8auVYZkOMG99de6C9jVe6oYAOHCLFa6RVh3CQtx4l3ctplR4STs2FGm1nsgc2HDpxqt0gp/y8KMm5g5Tjt43hkNZVNl1WJlnpVrFsqqLfOxgrdgL5aZMfKziCb+xfAu76TiGoM8sjJL75IOyCMr67BrIUySi6nnAvln/ZhskDbhHH4zZNBNyFA20/Fx4kzIh8Dv+JA9Zcq4AGDGuzFSUlJkYN0TclekMqjMrFtVxO4CZtb/+J64xf5QSZGCFtix70GdMCtNHKcdPO+MBDmWkj0CJaVKPEqrCMo3dsoUUSwrUvC8zjeq41+M5ImVMUWQJrZSUCR3aHBxpFBDp+h5nfSYyCg9G/0dLDVlv8nfuq677rrWvHnz8rshPvvss1aWOQjNiOPgwYO5jSFSG4RMlE1DFI+jR4+GM3z88cdhs3rHcfoH/qK0devWUfLJ8rOf/Sz8HSpTMK1XXnklNx0N5TtTopVrTnSLlH+xPE/97asOuPn9998HGV9FVqlpZQo6vxsJaffHP/6x8LkzxJgvwLJ58+b86hJWYU0G+C/mBx98MFzpUWFZuHBhOI/lYgP41W5hdZzJxqOPPtpau3ZtrUbDkiVL8qtiFi9eHJTVWNEr/956662gkC0zZ84M57hiMnXq1FbWqs7vRrNgwYJW1uLO75wUjRQ3+1nHLeNO97jmA61Zsyb80V8Ki/NEXi1MNd9NmzaFWu6uXbta77333nBadrLoSlMocCpgjuMUw2qLKG21KpFTLChSxIULF0qfw1dffdW6995787vRoGS7WZGP/Yvl+erVq/MnzUCGPfDAA/ndEDfffHM4I2Msp06dKk2Xf/7zn62HHnoovxvNWFZ0+pWetbjJbCdPngznsoz30ksvhfMjjzzSmj59elBknKkZQurdMvcoLHDx4sVwBrqsFA61LuWGzrKv90FmOlNwWaGIFYOKiN0Fru09lRRqnHS3UVhIJ9stnuomT7mrmmxZmOGLL74IZ/su0J2HIKKG6zhOGsoNimbLli2tOXPmDHcrI6e0YhnPWWFMvWjICLrJV61aFe6B8ibZgZvIAbqXyxo/yEGGE8tIyQZox7+YlFyMYUUz5FmsUOmV2L59e2vbtm3D6UIYCJfSBXPMBOFFJ8SVAEFPpXTDpCZTHAFz2TGalGCPsskNTMRiMgL2OMuuJl3IXMiMSQxMAhGxv5qghfvc4x4Tway7smfvcSd2i3v8iv20xO6CvZdZbE8H5kzOSE0eie3FYcYsDjPu2PvUYdPVcVKQTyYzRRNoOTSBVP94wYwyRdmLJ9Ta8omb8eTTFLiBu5JlllgGcOCHaMc/S0pOpWACXtEscCAcShvctBPYCJNNNxv+GN7DXpyukwl9g5/kN6EGmV86FdDyTo3V14Ua5z333JPfjSQrAK2HH344v3Oc8cdlw/hCLyHdy0zamswwfJop+Y5k76Cjsjjmk9MGHbp2fvGLX+R37XH69OlWVmsMH8AeWQ06TNxwHMcRdBt/+umnocI/WaE7/tChQ60nnngiN5ncuOJuAGMxjPnE489NwA0mcnzyyScjxqTImMyur5rM4jjO5IKx4tdeey20OCej8mbc+84772y9/fbbE+YvwJ3iXeVjDMr697//fWv//v3D/1WcP39+66677mp7Rqfj9BKXDf0BsoO/o0025c0WoAwT+GzyS2VxhOJ2HMdxHKd/GaW480vHcZxhXDY4Tn+gsuhj3I7jOI4zQLjidhzHcZwBwhW34zjOBIEJbEzm6jX8O0arsjljT0eKm9mN9LnbQ0uKcmZJzvi5Dt79+c9/nnxWtOkFf4domil5J+WHPYogHNYe/+EmTkXhKyOVVhx2hmgcVi0TGEO6tRMGx3H6H5QvcoG/hjaRd/yl9IYbbgibGAncklxBbjRRtlZGxzJn+fLlrWeffTa47YwDTE4Dc1kL7HPES2baZfZYvhPs0nzxcp7Y0TOWwytD9uRuEwin3hdaCpUjDpeWC7V+aQnAsmX5yoiXKEyh9CiKo9zwpUqdsaIorzq9geVDtcxqlUwULAOKTLDLiQLva/lVnhUtnxrDUqT4r6VM9S4yU+Am4bRmTm9RWRwukU0KJ3Y5YmUnYuXTDcVtKwTtKM6U4garvOWuwpQKD+FvV3FDVTwwKytYqjxw1CmAjtMp5DVn7CHd6ypu5EYsWyXb7Nre2KtT6Wc/BpSyhTXJ4/AgK1Ho1g+nd6gsNu4qt10jducbC3+UzzJRftcdWG1M2OtOoTsqy8jhmu1FLexEY7uyoSjOdaGLSaTiwZrERbv30E1PmMS+ffvyK8dxJit0h7MDV7zHwYEDB8LOiHa1Me4zZRu61ctg1zN2JbN7afPeHXfckd8Ngaxnd8Hdu3fnJs5Y0Fhxs1UdoOzKVrLp5ko3jPUuXbp0uDJABkqN/2Km8eEmY8C4LXCDcEuZsxmIxniAZ3aFM8ag5GcdeJ/CA3E8uC7bso59bbNa9HDY9C0cx5m8sH8/23Vqn3CB4p03b15+N4Ts/P3vfw/nImigsKFH1vIOSp4GDMo8tQHSkiVLutqYcqpppLitkpEiawrKRoqOQ0qoDFqWbP5uN4DftGlTfnWJRYsW5VdDrWdbW6zLmTNnwpkF7S0oWcJr403lwLaA607UWL9+fX41stXMddla5RQOnttN5n2SmuNMbti/X40BCzKraNOisv21gQbGO++8E9y46aabgh9Fu5Nde+21wV478tZpjzH/OxitZrrqdfDBq0CJ0n3MIUWPwrQZhRrhkSNHgpvKxGfPng3ndiDjWrcE4dVMT7q1sYO/UDfj2nio1cy7V111VbhOQaVJPQNV3e2O40weeqUwL7vssuGhRORUPGwopkyZEs6dyFunGY0U94wZM/KrVuvkyZP5VW+hRWlbmPaarmNBBtPYMF03UDRWXMaVV16ZXw1x8ODBoJztmL1a2aqBxv7WwcaDAkFcrEKOoYdBPQ5l3e2O4zhAV3cRaonb3k8O9eDRPc6OXBs3bgwyEPnHsKH/d7s/aKS4Y4UxFl0jtCjp9lbGshPIilqbtIQZC66L7RZHCROvuAsaJa2WNdi4c02tVGPf+u+jPeK0skqarnPCTPqm4F0qCwwFyD2fpOY4Thn00B0+fDi/G0KV/BtvvDGci9i6dWuQY0xs40D+Md5t/yPujB+Nu8rt+OyOHTvyq9F044/5ZDIyDy1ee9RpbZaNFVt4X93127dvD2eIZ5iDurg5rJKltWyVP70RcZhjpRxXgqompRG22E3hk9QcZ/KCLGFmecyyZctax44dG/GMPf+RX5qkFssUNT5++OGHcLbcd999rfPnz+d3o7E9sk6PyT5WwFxWYv/7vLLgf9n2P8ZcV9nnyBRZbpp2R1j3OCzWDcIpssw6yr7124bLmlv/FW/rLs/5b6Suebcuco+wFSE7KfBX4bTxdpxuUpT/nN7B/6JJ9/i/1CnKZARyQbIN+cR/rllcpQrJFi3AglwjLJJ1FszKZJjTPfSdh792O4WTDMF79og/YPxcB5nNKlN73HvvvSPurZtWWdlDCtSa4UcqjPZIZTgyqTI7Gd/ajxWzfdZO5uWdVGGAOOwKE8Th0uE43cbz1diSknG2ARGDkkchp+zwjMVUcANZU0dpCylkvVskp3CfxVmc3sO3gAmzHzdj0nH3dpaR25qgVhfSzJIp0zCRw3EmEoMuGyYDyD/myRT9ZatXMP8ma4mH/4wXzdFxuofK4oRR3I7j9AaXDf0P49j8TfXJJ5+sPb+nG+AX//NOLczidB+VxTH/H7fjOI7TXZj5/dprr4VJwUX/t+4mVBRQ2kWrqTm9xRW34zjOBICZ4t98801Yo7zX8E8XWtpj3TXvDOFd5Y7jlOKywXH6A+8qdxzHcZwBZESL23Ecx3Gc/gWV7V3ljuOU4rLBcfoD7yp3HMdxnAHEFbfjOI7jDBCuuB3HcRxngOhIcae2r8TMcRzHcZze0JbiZmUelPS3334b9r1msJyDew6exftZN6Ub24I6juM4zkSjseJm/+p77rknXKO07bq4LDLPxh7Ahh/tLr3nSttxHMdx0jRW3Pfff39+NbTAfAy7cc2aNStcr1+/PpybgNJ+5ZVX8jvHcRzHcSyNFDdbuNEVDmxhWYTGubFLCx1lrDFwdrDBHd1zqGXOMyltzjyzXe52TD0eS8cfPePALRH7F9vlPrYTQzj0LPbbhouj02ECx3EcxymikeI+e/ZsflWO3Zf1zJkzYSF6tcLBdqlbbAt95cqVYdx89erV4R6FqDH07du3h7OUM4p30aJFwQ/ewe0PPvhgWMHiH936ArvYww/dL126NJgpnLa7nmu6/jWeb/1GSStcPCNsjuM4jtMr2pqc1ivoZk+hFiytfJTwwoULw73YtGlTOKN8Qe6gTFPj7KlKw8mTJ/OrIWiB66xegAULFoQz4aBiQIWBzetBip6KhiobjuM4jtNtGinuGTNm5FflSOmBlF0nHD58OL8aAsVM6/bgwYPhHiUKV111VThbPv744/yqPY4dO5ZftUJrnJa//FNvAmDGs7HYC9dxHMeZvDRS3LR2NbYt5ZVCrVcUne0275S4VTzWqDtchybnca1ud2bc2252x3Ecx+kmjbvK7Th0qnWJGQoO9uzZE84QT+gqwo6FCyl/3LWteZF6RyxevDi/ao8rr7wyvxrZ+o6h5a14+6x4x3Ecp1c0Vtx0U2uiF61LxnkF1/Y/3qkxa7Wa9+3bF85lUAnAzVWrVuUmIyeNqTKgCsKuXbvCWWFCoaf+stYE4qCKgeIGjLsTPs4ag1ePRFlFwnEcx3E64t855rI2mZIK79kDsxRZa3SEvZUrV4645zkcOXJkhB0Rv8+hd8C+x2HDkXo39j9TtqPiY/3nuX22ffv2YM45dstxJhKepx2nP1BZ9P24HccpxWWD4/QHKot99Xcwx3Ecx3HKccXtOI7jOAOEK27HcRzHGSBccTuO4zjOAOGK23Ecx3EGCFfcjuM4jjNAuOJ2HMdxnAHCFXcCVl5jhTa7p3e7PPPMM63rr78+v+sM3ME9x3EcYPXGV199Nb8bfIjLX//61/zOKaInipslQPmjuD20LKj417/+FcxYtpTnV1xxRVCWrEWuZU1jNzgssT/dULRw++23+3rjjuOUgqxC0VChjuUboICsfLKH9nmgIp56zpHal8GCnDxw4EBr+fLl4R6ZyhLPep/rf/zjH+GZBTP8RfbaJavLqIprDH4gjwkH56K44J4NI3F59tlnRyxt7SRg5TQwl13h3Llz/54/f344uLZ8+eWX/542bVp49t577+Wm/w7XmBEWljCVGfc7d+4M9zHyBze7CW4WLd/qOJOJbsuGiQJLHWspZC2BbImXQraHZGK8lLIO5E8ZyMO77747vxsC/yQ3OeMGcjaWvzLHH9mvoiquMchOhY/rlCxdt25dUq5Lpr/xxhu5iSNI/3AOvxky6CapD8ZHIdOQCeIMBZjxzGbAqgyWyhSdUpTZHGey0QvZMFGQfEopM+SH3U8BUEZSaDQ2UIixHMSsqKECkqHxXg1x40VhS7lFeKvkakxZXGOsPfllwa0y+UrcUpWOyY7ScczHuHfv3t36/vvvW5s2bWr99Kc/zU0vgRnPHMdxBhW6hvfu3Tu8JbGga/u+++7L74a2A47lIN3o6v5OgQxdunTpCLfZxfC6667L74bQ7owXLlwI536BLv37778/pE8RxG3BggUhrs5oxlxxa+vNm2++OZxTMDaT2hK0XcgojJlo7Cc1tkNh0Xh7PNnDTlZjPEb2NFEM+4zRY2bHfyi82OGZsGHhzDiYwmLHhQiPnYhWNGEOvxUezkX+c63xL+wVjTk5jtM5KJ5YIVP2Dx061Lr11lvDfaxoAXmAUk41agQydO7cufldMfgHWcs2nMcS/Pziiy/C9eHDh0eEYcWKFWEr5rI4wpIlS4b1hTOSMVfc3377bThXfbRusmHDhlBgzp07Fw6gxidQkihFMtNQb8SlfcNBk9UoCP/zP/8Tnu3cubO1ZcuWoAyvueaa1vnz51vr1q1rrVmzZlgpco8dehjEW2+9FeziD/uMP/744/mTVmvr1q2tO+64Izy78sorw7siNWEOJf3aa6+FuPHOU089FfyXwrf+4+/LL78c0h//d+zYEew4jjM2UAaRF2W8/vrrrWXLluV3o0G2UIYXLlyYmxTz4YcfBoWZqiD0mu3bt7d++OGH0FDQPdDQmDdvXq2G2bXXXhvi6o2M0UyKv4OhqFSL5XjooYeGKxBqAdNlpcz08MMPh7PgfeBd1ZZlh5qv3rvlllvC+ezZs+FMhSCu7arbCn+pldthATK6nuPmypUrwzUoDIL3UdJPPvnkcJcZYeIdlDWZ3fq/evXqEH51QXlhcJyxhUp2LFsslGkq4WXKXbKlCtx64YUXglwbD6gsHDx4MDQoOHNPjyJpsHnz5mDH9nLa3kUxZcqUcK4b58lEI8VNdy2JbI+4y7mKadOm5VdjBxmEDEw3FIUChSdOnDgRWqS0cC1kqF5ALXL//v2tq6++OlQYUKJS/NRECZu6vDdu3BjMUxBuiMN92223hbNndsfpH6goI2fKWr+0kKta5HWhlxElqUr9eKOGBrIPSI977rkn9BLSiKKxgZx26jHmLW5lzLp/sp89e3Y4Hz16NJxT2G7tFBqXfvfdd8PEEHXbjAe02I8cORJ6AOj6njVr1nCGpSb6xhtvhMoNmRzlbv/jmOLixYv51RCqpTqO0z/QTX733Xfnd2kYqlPFuxOo9C9evHhcusiLoCLB8KQqElRSgEl4mNEzSPydejRS3LQM6fqwh1qLdWFcF8XEn+yphaVAkUmx072LcmOCQwpa/PPnz8/v0tx0002h0NDqVle3uOyyy8K5rGLQTShUM2bMCHGkpknYlWFpgVOx+fTTT4Nyhw8++CCcY3ADGBOznDlzJpxV4XEcZ/xhktUDDzyQ342GFigNkFg+xajcxxV2gVyZOXPmiJY7cmU8h8aQ5Qz1tduboDg7l+hZixulbA9B7QoF+tlnn4UZ0rblTeZCsZ0+fXpEBn7ppZeCAmMcRBlQdqnFrV27NpgVQReVxrRpwaoSILeo7W3btm245cuZQoSfZHqF38ZD79q/Wqgw2UKVepdKBO+TFlRKLr/88mCOmfxD8TIbfOrUqeFZ7A7vMvmMrifNgud9xrXoUaDCAyn/ubb3juO0h8p62V+ukDk0VtTaTEELtKpFDpIZx48fz00ugTyk+5nDDmcybh77rfDGFQDkAnInNeZcJ64xyCQaaUyMtehfRfREkD7IWibmWmhMEdeydJu0ZK3mgLnsGP3h3h6YWTJFGhYa4E/2ssPCBHYlNQvmmYIdtst72K+zYprCwzssRqDV2Fi5B/iTP2GRHS2SgBnhlJ8chEELEVizOM7c2/ByAOaEWc84a5EBnhG2LLOGZwofWHd4R/CO7HO2iy2k/Lf3MnOcMjyfpInLV1E6UY7LFlQBVgqru/qjZIsFP+Kw6LByBOLn1i1kETIwfqduXGN4ryheRbJOIINT5pMZpftP8ptQM8svHcdxhnHZ0F/QKmb+C72WE7U1SkudYcSJHMd2UFmcFH8HcxzHmSgwDMZwI13rE3XIK2tph3UtXGmnccXtOI4zYDDRi521mCc0kZQ3cSFujLOX/ed9suNd5Y7jlOKyoX9hcu933303YZScJtq60k6jsuiK23GcUlw2OE5/oLLoXeWO4ziOM0C44nYcx3GcAcIV9wSABWOYpMICDIK/UzDBo+7Sso7j9DdM3Iq39R10mIg2UWfG95KeKm4+CEqFjzPRMly/oH26i5ZGdRxnbNCMaMYhObgu2msAu1S0tTtW1WZNuHPDDTeM2AYYqJhT/qmkp8AfnuMHftWpyPMO8pp3cFcrSpZBXLDLoQlmMfhNmljYwrTOngxOBJPTwFx2DVYLYkUg3I5X+nGKYbUgVmeri1ZyY0WlMlgVyb+D05ReyIaJCLKOg9UWgZUXWRkshpXEWJ2MssjqYVo5sQie4068Ahnl3q5oloLnhAM35G+VbNGKkbyDLMLtsnckf3Bf17F93CNtUnFlpcqiZ85I9J17qrgFbrvCqA+FtKpwWVRYqhQ3BcS/g9OUXsqGiQJKi3RCEQsUEWa2LEt5VpVVC3ZRpkVIecdQ3jG3ChG3UpUJkapI4EbZkq24af3nOo4fYSyTacSvSZpMVpTOPsbdZ9CtldVO87vuQVcUbjuO0320yyBbBwt26suU9PAOinRB33nnnWFL39WrVwezKniHDZDa+V/zgQMHwgZK2nAIuEe+FHVNs7mTtc9cGeKgTUHagW70JUuWlO4kee+994Z4El+nmr5T3Bof4rDj4hpz4QCN3TCmIrs2MzKeovEjDqu07GQudsHheWrsR+PHclvuaeccxnLkv50YBmT4svGuVBi4Z49uWLRoUTADxVVuEY6qMTHrPmFha1N2SWMsXH7JPQ4bfplhx3Gcaliak2U6Kb+UJcose+p/9NFHuY2hnbBQmnPnzh2WJZSxIiUK7BpGuW1nb23W+Z43b15+N4Tc+fvf/x7OZSBDWFaVOJQtPbpw4cJwJh6SSzLjnt0YqyoqKHXiqX26nQpCuzvDXHYd3KarpA4aC6E7yYI5XTzqxmHnGHW96B11AXGPn+re4cw9XUe8g9sKk95NdQXJHs/VBSa3rP8aB8ItIIy8KzflB2Zcl4VB3U62W0ljZbjLwbXt7sIu76irybpvu5/kn5A94mLR7miOA+Qbpx6UG9KL8hmPSVP2MJcsUflT2U5B2a+SnTxPfaO4/Isic4vc5EC+FYVP4B5x4ZDbvINck1ysArtlQwLOpbLYd4obpIhQIIIPqnsyPs9TB+9qvMlmGO6VoeQ+GbIK7MVht26B3OMMuGsVKxAW7ChjFoUBd61bgDCwGVp2hNxKhcmacR/HRW7ZtCLsdQubM/Gxec0ph/JEWSXNUERW4cXlETQObWWdhfJaJTt5nvpGKf+gyDwGGaCKSB1ZGcO7qqSQDmWVGqgT18mOvnOjrnK6PdSNqqOqy7aM2C1119Jtkn3A1vr168M93U5sBq9xFjaR5znxiA/epTuIa8BNuqVSTJ06Nb/qLp9//vkoP+lqygpy6La21AkDXVbsBqS/U9AF1y0eeOCBMIa1Y8eOcM/3JOy+K4/jNEPDcZTVrOIcusWrhpsk006fPh3O3YRyXUQduYMMQPYgazWEVxfeyxR0GDOHDRs2hK77TIGHMX7G+p326dvJaShtMj4ZgHEPPradNHHs2LHSiQyMG/MOGRSlP9akwmbD3wSNrzPx5b777mtlteX8SecQpqeffjoUTCoV+/bta91///35U8dx6kAZpQxpbJcGBGPDKCtkGKDITp06Fa6FZEIvGhHIP8aXLWpo3XjjjeFcByaWNYG02LNnT+uJJ57ITS6NlxNfJqIh2ztp9E12GiluMmOqhdsusVt2AoNtdb/wwgsjZlXOnDkzTGSIJ3bQuuaeSWNbtmxpffLJJ+G9sW494h8F1oYNTp48OWqySB2YWEampyavGmw3Uat73bp1oYDFiyQ4jlPOjz/+mF9dgp4/etkuXLgQ7inDlC9bqVcPXNGsbWRJWQOlDBY3iRs4R48eDRWIJpPdCH8TmfDggw+GxkU7DRXv6atHz1vcyjTtZD61uskANqORiSgQKMc5c+YMd7Xv2rUr2FNB4e8Y+KsaL9DdfPHixfyunFTYVdDkB8g9nVetWhUUIRlY9qlMnD9/frgWWhQG1dh5zju8TyWFdAAqA6pF84x7uZUKkzWjIkRcOOwscrW69+/fH86O4zRj9uzZocz/7ne/G1HmKbfLly8P9yr7dBtTBrGHMqfCXKSwFi9eHORcGSk5BcjJBQsWBP+AFi5/uXrppZfCPWCG7NS/aniHfb7VGsacngRkWh3o6UTuxRUD3EW+EMY//OEPIa3iRh//eCG+Tg2ylm7AXHYNJkDgrj3spKs6MMEjNXHDTnbg4FoTHrLCEiZAYJ4pq3CPO5hpVjgH92WTNGRP7mjClzWL4yj3CEscPsIB1p04DJqJmWXs4XjLD8wIvybnMWEkDhN2U2agiTCE206aAe55pjA6jiBfONWkynw8CYt7yh/PKc+27KegXGIvJTfjcs4Ru2flJLJGk8WE3JA5MgL/ZJ+JdrGsKAK38CsFbmjSHu6m0oVndf2arJBG0Nf7cVM7Yx1bWqpOb6Fm/frrr4/onXAc6EfZMJmgd4yxcYbKJipM7MsqDK3NmzfnJk4KlcW+nZwGdPFktbT8zukVVJCeffbZMPHNcZz+gjkon3766YStVDPcxwRiO5nNKafvFDfjQtQqOMio/jF7B+NOpPP06dPDOHcvJr45jtMZlM3XXnsttEonmvKmp4+/hr399tttTWabrPSd4v6P//iPcGbyGX+n8I/ZO2bNmhXOd999d2vv3r3h2nGc/oPJXt98801Yf3wiwUQ5WttNZrk7rdaIMW7HcRzHcfoXVHZfT05zHMdxHGcI6em+npzmOI7jOM5IXHE7juM4zgDhirsD+BuVNjEZz3V3Wa2I1Y56CbNZWWLWrrg2aDCDlf3TtbJVP0N+0l7wTjr/jUW+d7rDRJAf0C/xaFtxI/wQLAhC+t1RXkQGZaZdciwIIv39SPaxh32h5ffiAz94V2t/40/KHgfuYrcbf5vADQSD3MZdwog55927d4clBFnWcCIjJcKShM7YcPvttzfekWmiMpnynxSDZA7yR/JGyqJM/unAvnXHHrE8bRc1XFIyEnPOMFG+X1/Fg8lpYC4r0dKZdkk/lqqzy+VZWOoOc5br1JJ2WvoP83j5Oy3RJ1iOD3vWLu6wdB7Lg8pNztjFjPdTS3vWgXfssqNyA78VNi0tyJn71JKEEwktjVi1RGMZWqJ1LOCb8f0HGeVhZ+h7dpr/+h1kSyxzWIJYS4XauPMc+RfnD8xxR+UMmWXf5bmWfcavdpc45j1kJIddRhX/JH9tWe+G/OgHxjse+A2NW9zUOu65557hnW70/zv+b01ti/9eW6h50XL405/+FHbq0v+yee/gwYPhv8TsfmW7L+fOnZtfDcHCICz3x2YbW7duDWa4Q+uas9zkjF1WGWLFNWpGv//978OzJqxYsSIs7E9ciJMNM3Em7k5z2GRgrGArWGfioDI4UaHbn/IRyxw2H0H2xStI8hz5F4P5Y489lt8NySwLz5HDbGyCPH3rrbfyJ81ABvI+Mtwu3CS5ninv3MTpBY0V96ZNm8KZbTNT8OGUyVDGa9asCR+xaFWu5557LmSAHTt25CZprrzyynD+4YcfwrmKjRs3hrVvCWeTMU0qJih84hBnelEUd6cYupjGakiBLkD8c5xBgPyKTCmTOcizOpDv2XWrarvlTvb/ZnVLGjboglSFCjPkutM7GiluFCBKDUVctm+qFsNXq+euu+4K5xQ33HBDONOSLUPbVF5++eXhXAWZh5or2NYX4zvUbovYt29fON92223hnIK4273DBe5qDEnjO6QZ5phRQKkl2wk1FALMeI+zxrFAYyqMVXGtsSTuhXXfgl/EX+EpizMwXiV3eAe/tNWfhW1CbTxteDW/gWeceZ9wY1/jtYsWLQrPsau4Y4844Z7SgkPo3sYb8Fv2CS9xJj3owaEySF7lGfasf4QJM7krO8AzmXENNi05iBvupeAdfTPytMKnd6z78tOGRX7GxOHXN+Be8cZPmXFv6TSfAd9JbnDwjiCu2MddhU3u6FDcOMvMhiNG+ZFD74pUvieNCBPuclb+E9wrTHHeJQ2Vfhxc2zRU3HkPu/gt5C/P9C526vLnP/85nMtkDvIsJXMsygd1YNMSmDlzZjgL8gnxKHOH5VehaA9xoKFWVXkg3fQNSbdY5vDtlC+Jm/Ke0l5hxSzOR9hPlVlbjvALt3GD7YxlV3nG5ocy8Mva5VrpZ+NAGcEvm3faJnSYZ5jLQtS/X3fcjXEA7FeNB2DH+q/3NM6Dv4zHYGbHTQhHWVhS/uMOY61F4F7sTxnyg3Elxn0IM24w/gSY85yDsSDNAwDeZTxI40wae1L4FGfc4hngBma4A9Z9gXu8q3fkru5TEOasxh/Cz8E172j8St9e4cUO4cRMYcF9wgPYIdxKR6WTvVf8cIexMe7tGJnAL8zst+YdGxb8UroC71v71j+FQekU5wfiQTgAO/q2wLu8Q/qkwH0OwqO00zfTO7onTII0tGED7hUHG36ubbw5MONecbLh41mn+Yx3uddzucFzpQn3hBe7+Icd2dN7gvDFZhae2+9LHHCHM6TyPe4V5T/iQ3xxCxQuxQ+7elfjwjYNiZ/yBGGweYv3bJ4i3LhXF9zCP/vtheJtD9nTe/aw4RKYK92IA/HCzMZPkC7ElXgUIb9SpMIEhJlrhQOwSxj4JhwKl8qN8hTpKTN9N5vmfFfMFGbOPNc99nAL9/Ff7vIe6aFvK3fsd1CYRCoeZXlHfmFHaS+77aCwDIfIBq4IBTqVOVIo09lIpsCO9V/v2UxgP57geVlY6vpvkZ/245UhP6x9mQm5KaEBXGMmwSGUUZTpuI7jiJmNk9wXuKGMA/glQZpCQjourGQ2CaBUhgXc5QCekSkVTwl1KEun1He18QHMlA6EMw4vflFIBM/jdEuFgcIa27PppMKcOorgWeymviuk0lJmNmyxO2VpaOEdvdetfCaBZNPcPlf4Sa8Y3LWKDDfsfYzcsn5xbf0D3MVM8Kwo/5FHsRsfijN5x6YR5jY9sGvTXeVLZSd1WPtlKB5F9lV+ORQ3iMPIN7L3Ig4X7sRlrglypwh9KyuD9E31/erIHMBOHCfrDshtpV9VmeVdruM0kLn9DjITcTygTt6RjOwUhaVRV/lll12WX9VD4yh0r1aRfaz86hJMciCsHEw4KxonL6KoO6iMul3x7WDHg06cOBHOGrsX6i47e/ZsOLcD3TRZZsrvhvwl/ZiUkuL48ePhHA9/ZEKwclyaYRDGu+Daa68NE2zYQ53uoQULFlR2l8GUKVPyq3oobew4Hd1i7ezbzpaJdKmra5O000Y38Pnnn7eyQjqcD+3RBH3XuMu313QrnzH2qjjTLUlXY4rU2On69etDPtJwGBOiHnrooXCd4ujRo+Fs82PZ0Jwoy3/k0UzojvqGyBgg79D1SxjpsiVPWDLBG4Z5eIYdDQdSdjIhPcpdjjp5HyRzvv7663COofzaowi+0bx58/K7kSgPkwYqr+0i2aIyE6NvddVVV4Vzik5kThV1y2xTuVNEVd6Bsu/WDo0UNxkDBUvAGCuoQmMgZbOJNabBB+smhE+CggJcl2XLloXz+++/H869RmP3oluZqZ0Z3PE3rTOBhUqZKl1UrBAMS5cuDWPamOsb9IJuzBxHcCCUGfcC/psfVxAPHz6cX7WPvuuMGTPCeazpRj5jbI5vS75gR6e6oMBQbihw2LVrV2v58uXhuptU5T9VCFJgj/k2X331VRjDJbwWFDzKgLkT/KsGAa3ycuzYsVrysAjJnOeffz6cO2Hz5s35VRq+BfH47W9/W6h4q9DcIZWZTmhH5tShG2W2LlV5pxc0nlXONmywYcOGcE5BAaflglBct27diNp2DO5Rg+v2vtuEj0JGJq1TWxdkSgQ5Bb8oY2NeNqmmDhLgr7/+ejiLM2fOhPPs2bPDuR2owZPmmpAhVOBi1CMR/zWEHgvSogwqCAhKIE2IF98a/3l3z5494VkTiloNQj0/xC+efFSUz8p48sknC783eYeKKn7ZCTtFaVkEFUEUCe518m2b0q18hpBm5vMnn3wSem6alClQq1vlq+x9Ce+mvRNl+Y+05x8uxENlgjPfle+OMkYWofhSM7uRJ0wOO3nyZGvnzp2h1UpvBmUHOcPkI5t/CEuR/IghTRD2hLkbyrAK4kFj5sEHH2yrwqF/7JTJyCo6kTlVtFtm6bFpSp280wsaK25qtStXrgwfjYSwH45rEusXv/jFcMEkMtjH3BYa7JLZqa3G+25/8cUX4VyWqXhGIeIse5wR3tSGCR/+xjMxr6gxq0+zJpmdjBCw7nPPf8nlroYBbItGZva9GNKHSg2KT4WVTPbCCy+EygbpkXpf13b4Iba3du3acCYNpk+fHmY60rUZ/z9eSJjynoQlZ+L64osvhnuUJYWVmqwKA98UM/tXFXpOVGlDWKobcOHCheFMOhFf7BQNoUhwk0eIE/b51hRG8gyFA38QmJqlznd9/PHHh3t5EIS8y6FKVupbAe8QDzb0/81vfpObDrFq1aphIUV8NHMU/8ogX9u05H1VepXXlc95rn8z3H///aPynEiFX8NB1p7iDd3KZzqj8HlGGAVlLk7TGLW6CYf9n3EKWuOk+e9+97vhNNQ3ZKVCxSMV7qL8p7R/5JFHhssE58WLF7d+/PHH8Oy7774LZ+JDftM18P3k74033hjOlAmVHRT5nDlzhvMHvQrkU8JCXiHflsF++LhD+GK5asMjiHMs/1LInbis4R8VBVqKiiMQR8JLuIsgzyCz+UbEmW8j+4TF5g2h/KFw1JE5ipeNn/yx8ZHbOleV2TgthHqhNGRBWNRyR37idxyPqrxT9m064t855rIWDNJnhSS8x5ElVJiMwASJFAzeZwV32H6WoGESgZ1sgZt6roN3YjKBM8qeDtwlHLiVgnDibxWEC39wT25nGW3ExKU4HPhp4xgfuBVj/eBs3bfv4m6cPpjF/gnsEl7MiDP+lEF8STfs8g7vxmnIt9U31/e23w8/NEEGO5z1nDNu8h55waYd8bZ+Yde6ITdt/sIO31HhlT2BHzYMqW9lwW3ClwJ3bVrG8Y7BHvYVB+JnJ68A97jFQdgIj+zhtsLJgTup8Mt9a2bvOQTvd5LPMiE//L7uiaPckl3u8SsFk4F4Xgebj3iHe7lt84cO4Jl9j7P9TqQtbshNG07rF/FX3tJ3wy6Hvpn9nvhhZSHXyoucrbtV4G4cN9JZ8Qau7XMOGxcRu8NhwxB/Z+BbEj++bxWEB39VNnTgr02f2B+FlffLZI59BzdjdzCL00Juk+4KF+6rzFr7qW/Cd9cz8iv28YfrongonVN5R3a5J190Cm6B78ftOF2GspQV5uGJT84Q9HTRRVo0SXIiQ+uLFl3dCWuOk0J6unFXueM4TlPosqXrsheT0gaBv/3tb660na7hittxukhqXG4yw7girQTGQlmdys5lmQwwbsu4cbcn3zqTG+8qd5wuQjkS3l3eChNFmQS1cuXKyr8qOY5TjvS0K27HcRzHGQCkp72r3HEcx3EGCFfcjuM4jjNAuOJ2HMdxnAGibcWtlc/oc2dVGVbPYQapVuFhVi2zKXmmlXHGAibDdGW/U2fSQv4hHzn10QphdhUup32QmawuVrXiGuldtdJZU/CbVRHL/MY/yolWI+slY+nXoNCW4kYpsxzo9u3bW+fOnQvK+c0338yfDsFmDSxnx4xSp3dQyKg82SNV4Fi+D2UkOwgF3sWcsyph9sBcpPypAxW6+D0tX+k4llQewyyVh0TqnaIDORWvX23BnOcoCNnHb+Qd5nUpCm9cxmw5jd+5/fbb29ooqBvgN/+5L2PdunVh7XqWHe41Y+nXwMCscjCXlbAsHsu8VaHl5eyyciw7V+fdOrC0XLxk3SDAUnzdhiX9SOt4qULSG/+0BB/3wJKAWqZRS/fxjPuypfnwxy6XWQeFgUP+N6EX6eX0Hr5107LOOywdST7UsqGg5SNTeUH5Vstsyg3rN2ZazpMjLidy3y5XyjuYY59nTbBLneKOUDlFdsWwrCZ+yX/stSMrtVRnJ9Txm+dN06VdSK+x8qtT+N7tfLc6KA3aanH/5S9/ya+a042tGMV41Ug7gVp9p/vhptDet9rcRaxYsSL4x6YAtLK1AAYbINDazgRVuAc9K9qMBPDnmmuuye/qgbv2aEKv0svpPe2UdfLHpk2b8rtLkHczYRh68OLFbdj4JFPowQ7gBq1lC2Ystco+2rTc7K5UtNrZ4YmyQJnQDk+8g5uUnabgBv9dZ69mm+e1sxZ7RsewUQXvyP92effdd/OriUO3tvscC7qp44oY08lpjIs36XIqA3cGrRsegWMVZa9BILGjVpkwoAuqXxnr9HK6RydlXTu8/fnPfw5nwc5pKN1YMGKPLSrbRRWForIgJdyU2267LYTXjvurMkC5jLvs2ZUw3p2uKVQ8qrq5nd7RTR1XSmh3Z5jLQuLdUXQAXUp0D9guGttVTteUupx08Ny+p+4Qunr0vt7hrC5a2bMH4A9dUXE3BeZ0sckd7Kj7inDhHuZc01WGPbq4uE+hbjfsEFb80/t0c3GvcHEtdxQG+wxwjzAprpjbbsI6KK0tuImZ0rMO2MetInhmhyfUJVjlB3FSfCFOQ30DDrlVlF5AOHgXc7kBNg/Y7x77rbThzLuKk80PwHvyn0P2lN4cAndsPitLRyDtlN+wj7/ChpGDOMrvsvwHRWkTY+Mgt218waYH10Xlw5ZjzLEvdziq0iIGf3DDQpxxi2eWOCxAWDgspANu2rTijJt8t7oQDutGGdiLw6s0xB2BW8TDgh3iQD7R97Ru2XzA9yN+2LGHvqvNaxzkLd4vAjv4rbim3uE55hbiYf3hOpZlhMmWk1RYeEd2cEN5tYyy8gRl/iou1g/dKx8Rt7KywKG00tE031eBm+EcfjNkUAciosgACaIA24AqsZV5gHu9a9/DjIiTsGQWjTnpoyuRsAMpt61bQn7Inu5VUOUuB27yIfUB+LApsCe/+JCEkXvOfETcBO6xY90hbJhZsK/wKQ3iQlyF0sMiv2waVYF93CqCZ9Y9xbFIOQjCYr+LTUPiT7xJe+zYuKfSizQnfwDvkL7Y0XfjGjckGCXQ9A7m+ka8g13FyeYHoffjOBIOFXye2Xv8sH7GKKwKo+zrnjgRLtzj4FrpUpb/ytImBfZ5br+p3gGbHviLmwq78jXvKjw273Bvv3kTVP5tmuOWwqN0Js76lhblm/ggDXlHEHbMm4STb0R8i9LUorRUeDkTXt6XDALc1LcXCq/M43xs84G+n+JjvwPhxE+FV99L3y8FbmBH7up72HfisknceEfhxT/iiFnstw0v9zYtlJ/lDnZ4bv2KwX37DmfsWzeq/I39ID6YKW/UKQvA8yb5qQkK33AobYCrIFBxwEgIRUhwjZkSC+JI6T0EiIUEl6AC2ZNbKbchdp+EjzOoMqEKAPa5t6TiaJH/sTDnI8pdiN2J/VJhTB1x3MpQeCzyq4k72LffMIZnTdwTcTpA6hvG8YjTi8LCfepQuLmO/bLPOVMIcQv4XjYMsZ9APtL7wLv2O6vQx0ccDkGetPlSQkKChvDZ53G66N7mvzppEyN3mnwDwMzGjfdjf7gvin8ViovSAAHJdVx2bUXFEodP34vyacuowt1uOKuIlS1nDuKCuRQa317XIhUuzGwax98v9R1UOUsdRfAs9lvukJbAc+sGz63MBuKEHX3HuvI4tqP0KoLn9p24PNX1N/YDM5sOdezw3N53E/ndNwuwxJMPmEhy8uTJ4TED/qLQDkxs0sQtoTG006dPh3MnsMeuhckouK+/XzGWVcbx48fDpBu+SXx0ug3g5Zdfnl9NHE6cOBHOqfRavXp1eFbFtddeGyY2Xn311SFvLViwoDKtn3zyyda2bdvyu6EJKMpHQD7LhOaoMBVtMsL4ZqZA8ruhsc9PP/10eK9q8g8TqRgfZUx0zZo1wTzG5r9upE2/QHpklZeQDkB6M2ZMmpNuBw4cCOZ8R/sdirATzRh31jjkZZddFs694tZbbx0RXs6E99577w33xEtj3fHE0m7BRLhMkSfzRRNuueWWcFY+i8GfeFIgccqU5nAc68hjZGZsJ76PqSpPvdYDY03fKO4YJibxP0cE1uLFi1t/+tOf8ifNuXDhQn41BB+1VyBobrjhhtZXX30VJpuglKs4duxYiG+3WbZsWTi///774VwHCtnhw4fzu9GcOnUqvxpfmHjXLghTlOzSpUvDRJ6slTCsIIqgkCPwZY/vG+ejo0eP5lf1KPtXBBVWhCAzhO+7774geOvSSdr0E+RfpTn/ZOG7SQGTdsST/NqkPDPRjDKJu7zPPd8fZdGLMggKL98UCC8VRfxFRqC8O5lcV4eyMl2XixcvhvOMGTPCOUUqDePv0yt5XFaeYCz1QK/pW8X96KOPhkxAi4WMH7ds60Lh4IPaDKXaHy2vbkLB5G8lL730UtjCsM7fOmbOnBmECJUUFWxgQQZ73w6kG4IN5VTkFub4JeglKKpIYHbo0KGOewI6QUKDHhg7WxchzEp9dSC+uINC+Pbbb0Ma7dmzJ3+ahkK+cuXK1vr164O/v/jFL/InQ5DPqGQSBqUd56IZpvSG4DfPbVrzzYAFjmhx0upGYdWhnbTpdhnoJmoRvfDCCyNao7S8gVnmqpzWhbQmf8Ps2bPDmfIKGzZsCOcUrNwludEUhRflbMPL96Ul+Pzzzw/HtReQdlRMyGs2DsprdaESST4v6hnAnPjEsoae03nz5oXrOvKYlnPTikZVearjr8I4CDRW3ETcHkK1MVur0bWeAbVdvYsAtc8sP/zwQ1Bo2COBbasRobRw4cJwzfsIJewoPDZcFEo+KIVS/u7YsSOEQwIx9Z7sFhHX3uDHH38MZ/6PCYSTTKtrWLJkSTjjNsJAypUMP2fOnOGVk3bt2hUUP/G64oorRqyylEItYWVGQY0eUAQoKhtX7rdu3TqiG3XVqlXhzP+/VQBll56E+D+22CG8VlHE8L49RCp/yEz24vRCOKxbty7kjV//+tfD6bVo0aIg/PSe9UfX9pshNEkr3KNQ22GFlBtA9yZ56dlnnx2lTCX8H3nkkdb06dNDmDjTW5SCVQWBSpXs08LWf+iJH34BaSxBRpi5T+W/qrRJoQrx119/Hc58Z/lFeIrKFdf2PlX+47JeNy8LKktSblJ+QNoj3EmfVLzwj3IXh5E8it+kDz0YanHhHpUyvgXl0SoerlEGVNSksJA3xCMua0UovMTDhld//eKZ3BYKtw2/rm0a61rpr0o15oSd70mZxg/1LilfEIcisEcaqvcGdzjefvvtcA9xGOUPFRSlDWnF8OETTzwR7uvI46effjpUNMgzPCceWpkz7ooXVeWpjr8arsU/nhN20oCwKM9ibs8g90Sc73vCv3PMZSGa+GCPLJCjzJkYwWHNsAOaEMB7dmJWllFGTKjgWZYJwjMmPWimIe8x8UCTDzDT5AK5xYE9gVvYxRz7uBdPsNAB9l5mFhs3wq24gdyTOX7ZMCoePNfsVsKSCahhN7nWM84pf0Sc9hw27oD7hBk3ZIf00MSNGPwkDITTumknQgmFL/UM4nzAgVlsTjzib4EZ7sfpBUpX7BEX+W/fx704fTDDb9ySf5zL8oOFcOB3Cr6x0pgz/pRB2Gy+tPaVPpjznYgf9/ht0w5/cMdSlDZFYF9uYRf3SQeuU+lh7zniNFY8bFknfZVXUmEuAjeISwwTjcijMTZtUgdhUVmMIUy2HOIv/th8B3wPnmWKIDeppii8pEWqHMZhjtMYsziuSlP84t7mU+Jg8xp2lOdT8Aw7ykdWJkEqXwB2bBpyHacT+cqGhXDGYSFu8lt5HrfK8g3PisoTVPnLteLFmbhwVh5IxdneyyzO991Efvwkvwk1lPzS6UNoLdA6Gs9uasfpBp6XHac9pKf7dozbGcnf/vY3F3TOhMDzsuN0hre4+xzGmBh/XL58+UDPgnQcz8uO0xnS0yMUt+M4juM4/csIxe04juM4Tv/jY9yO4ziOMzC0Wv8/Ap2joPzLpjsAAAAASUVORK5CYII=\"\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"604\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 604px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTable-2.\u0026nbsp;\u003c/strong\u003eMultivariate \u0026nbsp;analysis \u0026nbsp; \u0026nbsp; of \u0026nbsp;parameters \u0026nbsp;that \u0026nbsp; \u0026nbsp; related \u0026nbsp;to 1-year mortality in patients with COVID-19\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 203px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eUnivariate Analysis\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;OR (95% CI) \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;p value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 213px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Multivariate Analysis\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eOR (95% CI) \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; p value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003eAtrial fibrillation\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 203px;\"\u003e\n \u003cp\u003e10.12 (2.05-49.98) \u0026nbsp; \u0026nbsp; 0.004*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 213px;\"\u003e\n \u003cp\u003e0.50 (0.05-4.87) \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;0.559\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003eCOPD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 203px;\"\u003e\n \u003cp\u003e3.97 (1.26-12.48) \u0026nbsp; \u0026nbsp; \u0026nbsp; 0.018*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 213px;\"\u003e\n \u003cp\u003e2.03 (0.59-6.90) \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;0.255\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003eCHA\u003csub\u003e2\u003c/sub\u003eDS\u003csub\u003e2\u003c/sub\u003e- VA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 203px;\"\u003e\n \u003cp\u003e1.83 (1.40-2.39) \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026lt;0.001*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 213px;\"\u003e\n \u003cp\u003e1.63 (1.05-2.55) \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;0.029*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003eGlomerular filtration rate\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 203px;\"\u003e\n \u003cp\u003e0.96 (0.94-0.98) \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026lt;0.001*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 213px;\"\u003e\n \u003cp\u003e0.99 (0.96-1.02) \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;0.559\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003eAlbumin\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 203px;\"\u003e\n \u003cp\u003e0.18 (0.05-0.62) \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;0.007*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 213px;\"\u003e\n \u003cp\u003e0.46 (0.10-2.10) \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;0.467\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 604px;\"\u003e\n \u003cp\u003eCOPD: Chronic obstructive pulmonary disease\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-cardiovascular-disorders","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bcar","sideBox":"Learn more about [BMC Cardiovascular Disorders](http://bmccardiovascdisord.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bcar/default.aspx","title":"BMC Cardiovascular Disorders","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"COVID-19, CHADS-VA Score, mortality","lastPublishedDoi":"10.21203/rs.3.rs-6742800/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6742800/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eObjective\u003c/h2\u003e\u003cp\u003eCoronavirus disease (COVID-19) pandemic affected millions of people worldwide and caused hundreds of thousands of deaths. The CHADS-VASc score is a scoring system used to determine the indication for anticoagulation in patients with atrial fibrillation (AF) and determines the risk of stroke, and previous studies have shown that it predicts mortality in COVID-19 patients well. New guidelines simplified the score as CHADS-VA score, which is free of gender factor. In this study, we planned to investigate the ability of this simplified score in predicting mortality and intensive care unit admission in COVID-19 patients.\u003c/p\u003e\u003ch2\u003eMaterials and Methods\u003c/h2\u003e\u003cp\u003eAll patients who were diagnosed with COVID-19 between January 2021 and January 2022 were screened and patients with accessible data were enrolled. The baseline characteristics of the patients and CHADS-VA scores were recorded and their relationship with poor outcomes was investigated.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eA total of 838 patients were included. Mean age of the study population was 53.8\u0026thinsp;\u0026plusmn;\u0026thinsp;18.5 and 53.6% of them (n\u0026thinsp;=\u0026thinsp;449) were male. Median CHA2DS2-VA score was 1 (0\u0026ndash;8). Intensive care unit (ICU) admission was present in 177 (21.1%) patients. 1-year mortality was present in 86 (10.3%) patients. In multivariate regression analysis, only the CHA2DS2-VA score was predictive of 1-year mortality (OR\u0026thinsp;=\u0026thinsp;1.63, 95% CI: 1.05\u0026ndash;2.55; p\u0026thinsp;=\u0026thinsp;0.029). Cut-off value of CHA\u003csub\u003e2\u003c/sub\u003eDS\u003csub\u003e2\u003c/sub\u003e-VA score for predicting 1-year mortality was found to be 2.5 (AUC:0.863, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) with 75% sensitivity and 81% specificity. A CHA2DS2-VA score of 1.5 (AUC\u0026thinsp;=\u0026thinsp;0.725, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) constituted the cut-off value for intensive care admission with 61% sensitivity and 74% specificity.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e\u003cp\u003eAs a result of our study, we found that CHA2DS2-VA score is an independent predictor of 1-year mortality following COVID-19 disease. Cut-off values of CHA2DS2-VA score can be used in clinical practice to define patients with high risk for ICU admission and mortality at one year. This is the first study to report the recently simplified CHA2DS2-VA score is associated with poor outcomes in COVID-19 patients.\u003c/p\u003e","manuscriptTitle":"Impact of CHADS-VA Score on COVID-19 Disease Related Outcomes","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-07-29 11:49:59","doi":"10.21203/rs.3.rs-6742800/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-09-29T07:08:25+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-09-24T04:11:07+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"58890201039781821977628329506760448088","date":"2025-09-24T02:12:34+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-07-25T14:33:25+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"312735337225505689427072735797885896249","date":"2025-07-24T14:07:28+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-07-24T09:04:59+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-07-24T08:53:48+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-07-23T04:59:21+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-07-22T17:26:17+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Cardiovascular Disorders","date":"2025-07-22T17:23:20+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-cardiovascular-disorders","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bcar","sideBox":"Learn more about [BMC Cardiovascular Disorders](http://bmccardiovascdisord.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bcar/default.aspx","title":"BMC Cardiovascular Disorders","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"7ee9af40-4198-4f69-8a0b-df60c0402c32","owner":[],"postedDate":"July 29th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2026-01-05T16:04:42+00:00","versionOfRecord":{"articleIdentity":"rs-6742800","link":"https://doi.org/10.1186/s12872-025-05364-6","journal":{"identity":"bmc-cardiovascular-disorders","isVorOnly":false,"title":"BMC Cardiovascular Disorders"},"publishedOn":"2025-12-29 15:57:28","publishedOnDateReadable":"December 29th, 2025"},"versionCreatedAt":"2025-07-29 11:49:59","video":"","vorDoi":"10.1186/s12872-025-05364-6","vorDoiUrl":"https://doi.org/10.1186/s12872-025-05364-6","workflowStages":[]},"version":"v1","identity":"rs-6742800","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6742800","identity":"rs-6742800","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}