Incidence and Risk Factors of New-onset Hypertension Up To 3 years Post SARS-CoV-2 Infection

Incidence and Risk Factors of New-onset Hypertension Up To 3 years Post SARS-CoV-2 Infection | 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 Article Incidence and Risk Factors of New-onset Hypertension Up To 3 years Post SARS-CoV-2 Infection Montek S Boparai, Jacob Gordon, Sandi Bajrami, Tharun Alamuri, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6074295/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 06 Aug, 2025 Read the published version in Scientific Reports → Version 1 posted 12 You are reading this latest preprint version Abstract COVID-19 can trigger new cardiovascular events, including hypertension, in the acute setting. However, few studies have reported sustained new-onset hypertension post-infection. Moreover, these studies have a small sample size, inadequate controls, and a short (< 1 year) follow-up time. This retrospective cohort study of 64,000 COVID-19 patients from the Stony Brook Health System assessed the incidence and risk factors for new-onset hypertension after COVID-19. Contemporary COVID-negative controls were obtained and propensity matched for age, race, sex, ethnicity, and major comorbidities before analyzing outcomes. The primary outcome was new-onset hypertension up to 3 years post index date. About 9.93% hospitalized patients and 4.66% non-hospitalized developed new-onset hypertension after COVID-19. Hospitalized COVID-positive patients were more likely to develop hypertension compared to COVID-negative controls (HR = 1.57, 95%CI [1.35–1.81]) and non-hospitalized COVID-positive controls (HR: 1.42, 95%CI [1.24–1.63]). Non-hospitalized COVID-positive patients were not more likely to develop hypertension compared to COVID-negative controls (HR: 1.05 [0.98–1.13]). COVID-19 was one of the five greatest risk factors for developing hypertension. These findings underscore COVID-19 patients are at increased risk of developing hypertension well beyond the acute phase of the disease. Close long-term follow-up, holistic workups, and vigilant blood pressure screening and/or monitoring for COVID-19 patients is needed. Health sciences/Cardiology Health sciences/Diseases/Infectious diseases Health sciences/Diseases/Cardiovascular diseases/Hypertension COVID-19 SARS-CoV-2 hypertension long-COVID PASC Figures Figure 1 Figure 2 Introduction The long-term health consequences of COVID-19 have garnered significant attention as multitude of persistent and systemic effects of the virus are uncovered, collectively referred to as post-acute sequelae of COVID-19 (PASC), or “long COVID 1 .” While much focus has been placed on respiratory and neurological sequelae, emerging evidence highlights the potential for COVID-19 to contribute to the development of long-term cardiovascular conditions, including hypertension. Hypertension, a leading global cause of morbidity and mortality, often develops insidiously but carries significant implications for cardiovascular events such as myocardial infarction, stroke, and heart failure 2 . Mechanistically, COVID-19 may cause hypertension by persistent systemic inflammation, endothelial dysfunction, and/or autonomic dysregulation. SARS-CoV-2 infection has been shown to directly impair endothelial function through downregulation of ACE2 receptors, promoting vasoconstriction, oxidative stress, and pro-inflammatory states. In addition, the virus may exacerbate pre-existing subclinical cardiovascular conditions, potentially unmasking hypertension in individuals with predisposing risk factors. Chronic dysregulation of the renin-angiotensin-aldosterone system (RAAS), a pathway critical to blood pressure regulation, may also play a central role in the long-term sequelae od COVID-19 . The association between COVID-19 and new-onset hypertension is poorly understood as only a handful of studies have reported on this 3 – 9 . Moreover, many of these studies have a small sample size, lack COVID-negative controls, do not adequately distinguish between new-onset and persistent hypertension, or do not provide an in-depth analysis of risk factors. Most studies are limited to at most to 6-months follow-up 9 . As such, the long-term (> 1 year) effects of SARS-CoV-2 on developing hypertension has yet to be adequately analyzed. This study of over 64,000 COVID-positive patients investigates the long-term association between COVID-19 and new-onset hypertension at 3-year follow-up to the capture sustained effects of SARS-CoV-2. Moreover, we stratified the COVID-positive patients into hospitalized and non-hospitalized cohorts to compare the effect of COVID-19 severity on the development of new-onset hypertension. We also identified the major risk factors for developing new-onset hypertension. Understanding long-term risk of hypertension in patients with COVID-19 is essential for guiding post-COVID care, including targeted monitoring and early intervention strategies, to mitigate the broader cardiovascular burden associated with the pandemic. Methods Study Design and Data This is a retrospective cohort study conducted on the TriNetX research platform using de-identified Electronic Medical Record data from over 1.7 million patients from January 2020 to October 2024 in the Stony Brook University Healthcare Network. TriNetX is a global web-based platform that allows researchers to identify and characterize patient cohorts and analyze outcomes. Broadly, the data includes demographics, diagnoses (based on International Classification of Diseases, 10th Revision, Clinical Modification codes), procedures (based primarily on International Classification of Diseases, 10th Revision, Procedure Coding System, Current Procedural Terminology, Healthcare Common Procedure Coding System, and Systemized Nomenclature of Medicine codes), medications (based on Veteran Affairs and Anatomical Therapeutic Chemical codes), laboratory values (based on Logical Observation Identifiers, Names, and Codes or curated separately by TriNetX), and genomics data. With one of the largest global COVID-19 datasets, multiple studies have used TriNetX to study the outcomes of COVID-19 10–12 . Details regarding the data extraction, transformation, and validation performed by TriNetX have been published 13 . Other external validation studies have also confirmed the reliability of TriNetX in analyzing large-scale data 14 . Due to the retrospective nature of the study, the Stony Brook University Institutional Review Board waived the need of obtaining informed consent. The data reviewed is a secondary analysis of existing data, does not involve intervention or interaction with human subjects, and is de-identified per the de-identification standard defined in Section § 164.514(a) of the HIPAA Privacy Rule. The process by which the data is de-identified is attested to through a formal determination by a qualified expert as defined in Section § 164.514(b)(1) of the HIPAA Privacy Rule. This formal determination by a qualified expert refreshed on December 2020. All methods were carried out in accordance with the TriNetX guidelines and regulations. All experimental protocols were approved by Stony Brook University. Patient Selection We queried the Stony Brook TriNetX database from January 2020 to October 2024 for patients with COVID-19 and without COVID-19 who did not have a pre-existing diagnosis of hypertension (assessed on October 10, 2024). Details regarding the search query, identification codes, and inclusion/exclusion criteria can be found in the supplemental materials. Briefly, COVID-19 was defined as a positive SARS-CoV-2 PCR test. COVID-negative patients were defined as those with a negative SARS-CoV-2 PCR test who never had a subsequent positive SARS-COV-2 PCR test. Essential hypertension was defined using the ICD code I10. The COVID-positive cohort was then subdivided into those who were hospitalized during the time of their COVID infection and those who were not. These cohorts were then 1:1 propensity matched with the COVID-negative cohort before analyzing outcomes. Follow-Up and Outcomes The follow-up period for this study was between 1-month to 3 years after COVID-19. The primary outcome of this study was a new diagnosis of hypertension based on ICD-10 code. Cumulative incidence was obtained by assessing the number of outcomes on a monthly basis. All outcomes in this study were categorical. Statistical Analysis Statistical analyses were performed directly on the TriNetX platform which, for the purposes of this study, used R 4.0.2 software. All variables in this study were categorical and expressed a frequency or percentage of the total cohort with the exception of age which was expressed as mean ± standard deviation. Patients who met the inclusion criteria were 1:1 propensity matched for age, race, sex, ethnicity, and comorbidities including heart failure, ischemic heart disease, diabetes, chronic kidney disease, asthma, chronic obstructive pulmonary disease, obesity, and tobacco use before analyzing outcomes. Matching was performed on the TriNetX platform by greedy nearest neighbor matching. Hazard ratios and confidence intervals were generated by the TriNetX platform for all outcomes. Multivariate odds ratios and their 95% confidence intervals (CI) were calculated using Microsoft Excel. Results Figure 1 shows the cohort selection flowchart for this study. From January 2020 to October 2024, there were 64,250 patients who tested positive for COVID-19 and 225,980 patients who tested negative for COVID-19 and never had a positive test. There were 172,660 (76.40%) COVID-negative patients and 42,900 (66.77%) COVID-positive patients who had no past medical history of hypertension. The COVID-positive cohort was further divided into 5,500 (12.94%) hospitalized patients and 37,350 (87.06%) non-hospitalized patients. Prior to matching, the number of patients with new-onset hypertension at 3 years follow-up was 410 (9.93%), 1,650 (4.66%), and 12,030 (6.94%) for the hospitalized COVID-positive, non-hospitalized COVID-positive, and COVID-negative cohorts, respectively. Table 1 shows the baseline patient demographics for the three cohorts. Hospitalized COVID-positive patients were more likely to be older (50.4 ± 23.7 vs 35.9 ± 23.8, p < 0.001) white (63% vs 56%, p < 0.001), male (54% vs 45%, p < 0.001) and had a higher prevalence of CAD, CHF, CKD, diabetes, obesity, COPD, and tobacco use (all p < 0.001), but not asthma (p = 0.68), compared to COVID-negative patients. Hospitalized COVID-positive patients were more likely to be older (50.4 ± 23.7 vs 36.5 ± 22.4, p < 0.001) white (63% vs 52%, p < 0.001), male (54% vs 42%, p < 0.001) and had higher prevalence of CAD, CHF, CKD, diabetes, COPD, and tobacco use (all p < 0.001), but lower prevalence of asthma and obesity (p < 0.001), compared to non-hospitalized COVID-positive patients. Non-hospitalized COVID-positive patients were more likely to be older (36.5 ± 22.4 vs 35.9 ± 23.8, p < 0.001), less likely to be white (52% vs 56%, p < 0.001), less likely to be male (42% vs 45%, p < 0.001) and had higher prevalence of CAD, CHF, CKD, diabetes, obesity, COPD, asthma, and tobacco use (all p < 0.001) compared to COVID-negative patients. Table 1 Patient demographics. * p < 0.05, ** p < 0.01, and *** p < 0.001 compared to COVID-19 negative patients. ^ p < 0.05, ^^ p < 0.01, and ^^^ p < 0.001 between hospitalized and non-hospitalized COVID-19 patients. Demographics COVID-Positive Hospitalized (5,550) COVID-Positive Non-Hospitalized (N = 37,350) COVID-Negative (172,660) Age 50.4 ± 23.7 ***^^^ 36.5 ± 22.4 *** 35.9 ± 23.8 Male 3000 (54%) ***^^^ 15,680 (42%) *** 72,810 (45%) White Race 3,490 (63%) ***^^^ 19,510 (52%) *** 96,640 (56%) Black Race 390 (7%) ^^^ 2,040 (5%) *** 11,130 (6%) Asian Race 160 (3%) 1,280 (3%) ^ 5,890 (3%) Unknown Race 1,500 (27%) *** 14,380 (39%) ***^^^ 59,040 (34%) Non-Hispanic 3,720 (67%) ***^^^ 22,200 (59%) *** 111,260 (64%) Hispanic 1,130 (20%) ***^^^ 6,080 (16%) *** 30,250 (18%) Unknown Ethnicity 700 (13%) *** 9,080 (24%) ***^^^ 31,800 (18%) Comorbidities CAD 300 (5%) ***^^^ 990 (3%) *** 3,190 (2%) CHF 190 (3%) ***^^^ 350 (1%) ** 1,300 (1%) CKD 150 (3%) ***^^^ 360 (1%) *** 1,100 (1%) Diabetes 340 (6%) ***^^^ 1520 (4%) *** 4,660 (2%) COPD 200 (4%) ***^^^ 460 (1%) ** 1,780 (1%) Asthma 450 (8%) 4,510 (12%) ***^^^ 14,320 (9%) Obesity 550 (10%) *** 4,350 (12%) ***^^^ 13,510 (8%) Tobacco Use 140 (3%) ***^^ 720 (2%) *** 2,700 (2%) Figures 2 shows the 3-year cumulative incidence curve for new-onset hypertension. At 3-year follow-up, hospitalized COVID-positive patients were at greater risk of developing new-onset hypertension compared to COVID-negative controls (HR = 1.57, 95%CI [1.35–1.81]). Non-hospitalized COVID-positive patients were not more likely to develop hypertension compared to COVID-negative controls (HR: 1.05 [0.98–1.13]). Hospitalized COVID-positive patients were also at greater risk of developing new-onset hypertension compared to non-hospitalized COVID-positive patients (HR: 1.42, 95%CI [1.24–1.63]). For the non-hospitalized COVID-positive cohort, the results were then separated into two distinct time periods: 1-month to 1.5-years after COVID, and 1.5-years to 3-years after COVID. Non-hospitalized patients were not more likely to develop hypertension in the 1-month to 1.5-year time period (HR: 1.00, 95% CI [0.92–1.10]), but were more likely in the 1.5-3-year time period (HR: 1.14, 95% CI [1.01–1.28]) compared to COVID-negative controls. Table 2 shows the multivariate odds ratios for patients with new-onset hypertension at 3-years follow-up. COVID-19 patients were more likely to develop new-onset hypertension compared to COVID-19 negative controls (OR = 1.76 [1.62–1.92]). Confounders included male (OR = 1.22 [1.15–2.30]), older than 50 years old (OR = 2.39 [2.24–2.55]), Hispanic (OR = 1.12 [1.01–1.24]) and have greater comorbidities (ORs ranging from 1.12 to 3.07). Table 2 Multivariate odds ratios for new-onset hypertension between 1 month and 3 years follow up for all COVID-positive and COVID-negative patients. Odds Ratio 95% CI COVID + 1.76 1.62–1.92 Age > 50 2.39 2.24–2.55 Male 1.22 1.15–1.30 Black 0.99 0.87–1.13 Asian 1.01 0.84–1.22 Other Race 0.87 0.81–0.93 Hispanic 1.12 1.01–1.24 CAD 1.68 1.54–1.83 HF 1.14 1.02–1.26 CKD 1.39 1.23–1.57 Diabetes 1.50 1.38–1.63 Obesity 3.07 2.86–3.31 Asthma 1.57 1.43–1.72 COPD 1.24 1.09–1.40 Tobacco Use 1.95 1.67–2.26 Anxiety 1.74 1.30–2.10 Depression 1.48 1.36–1.61 Insomnia 1.77 1.56–2.01 Substance Use 1.32 1.23–1.43 Discussion This study evaluated the risk of developing new-onset hypertension up to 3 years post SARS-CoV-2 infection on 1.7 million patients in the Stony Brook Medicine health system of multiple hospitals on Long Island. To our knowledge, this is the first study to report these findings at up to 3-years post infection follow-up. The main findings were: 1) 9.93% hospitalized patients and 4.66% non-hospitalized developed new-onset hypertension after COVID-19, 2) Hospitalized COVID-positive patients were more likely to develop new-onset hypertension compared to propensity matched COVID-negative patients (HR = 1.57) and non-hospitalized COVID-positive patients (HR: 1.42). 3) COVID-19 was one of the five greatest risk factors for developing new-onset hypertension, along with obesity, age > 50, tobacco use, and insomnia. Incidence of New-onset Hypertension A few studies have investigated new-onset hypertension after COVID-19. Zhang et al. analyzed 45,398 COVID-19 patients in the Montefiore Health System in the Bronx and reported the incidence of new-onset hypertension to be 20.6% and 10.85% in hospitalized and non-hospitalized patients, respectively, at 6 months follow-up 9 . Hospitalized patients with COVID-19 were 2.23 ([95% CI, 1.48–3.54]; P < 0.001) times and nonhospitalized patients with COVID-19 were 1.52 ([95% CI, 1.22–1.90]; P < 0.01) times more likely to develop new-onset hypertension than influenza counterparts with adjustment of confounders. Notably, the Montefiore cohort was predominantly Black and/or Hispanic patients and had a high prevalence of pre-existing comorbidities. Our cohort were predominantly Whites and was comparatively younger and had a lower prevalence of comorbidities. Despite these differences, we found similar risk factors for developing new-onset hypertension including age, male sex, and major preexisting comorbidities. In a study of 168 COVID-19 patients, Akpek et al. found the incidence of new-onset hypertension to be 12% at 30-day follow-up 3 . Delacic et al. report an incidence of 16% in 199 COVID-19 patients at 3-month follow-up 6 . Vyas et al. report an incidence of 32.3% in 248 COVID-19 patients at 1-year follow-up 8 . In addition to small sample sizes, lack of risk factor analysis, and a relatively short follow-up period, these studies do not have COVID-negative controls nor statistical analyses for comparison. Azama et al. conducted a larger study of 5,355 COVID-19 patients and found an incidence of 17% at 1-year follow-up. This study was conducted at a cardiology clinic which may have inflated the incidence. This study also did not use COVID-negative controls for comparison, but they did identify risk factors associated with elevated blood pressure including increased age and comorbidities, which is consistent with our study. Lastly, Cohen et al. found COVID-19 patients ≥ 65 years old to be more likely to experience hypertension compared to propensity matched COVID-negative patients (risk difference 4.43, 2.27–6.37) at 3-month follow-up 5 . They did not report the percent incidence. Generally, the patients in these aforementioned studies were older and/or had a higher prevalence of comorbidities compared to our cohorts which may explain the elevated incidence rate in these studies. Differences in experimental design, patient profiles (i.e., age, race/ethnicity, and pre-existing comorbidities), comparison group, regional and temporal differences in the severity of COVID-19 cases, duration of study (observation time), and other factors could all have contributed to differences in findings. Studies of populations from more affected regions and studies consisting of the first few months of the pandemic, likely have a higher incidence of outcome. Both the magnitude and the rate cumulative incidence of new HTN in the hospitalized COVID-19 cohort were markedly higher than those of COVID-negative controls in the first year post infection. By contrast, the magnitude and the rate cumulative incidence of new HTN in the nonhospitalized COVID-19 cohort were similar to COVID-negative cohort. These observations suggest that non-hospitalized COVID-19 patients experience an initial indolent phase followed by a late onset of hypertension. Indeed, whereas a more severe course of COVID-19 may lead to a relatively immediate diagnosis of hypertension, a less severe course of COVID-19 may simply accelerate the progression of the hypertensive disease process in patients who may already be at risk of developing it down the line. Risk Factors Not surprisingly, patients with age over 50, male sex, and major comorbidities (CAD, HF, CKD, DM, obesity, asthma, COPD, tobacco use) were found to be at higher risk of new-onset hypertension. Age is a well-known risk factor for developing hypertension and has also been shown to be an independent predictor of COVID-severity 15 , 16 . Sex differences in developing hypertension have been hypothesized to occur, in part, due to differences in the influence of sex hormones on activating the renin-angiotensin-aldosterone system (RAAS) 17 . Likewise, this differential activation of the RAAS in males, coupled with the dysregulation of the RAAS by SARS-CoV-2, may explain why males have a greater predisposition for increased COVID severity 18 . This increased severity may lead to greater rates of hypertension in males post-COVID. Obesity was the greatest risk factor for development of new-onset hypertension, which is unsurprising considering obesity is a known cause of hypertension 19 , is linked to worse COVID-19 outcomes by several studies 20 – 22 and is associated with every other chronic comorbidity found to be a risk factor. Despite black race having a well-known association with developing hypertension 23 , we did not find black race to be a significant risk factor for developing hypertension, which may be due to having low proportions of black patients in our cohort. Moreover, the high socioeconomic status of the area around Stony Brook Hospital (Suffolk County has the third highest median income, $ 141,671, in New York State) may contribute to lower rates of hypertension in our cohort, regardless of race 24 , 25 . COVID-19 status was the 5th greater risk factor for new-onset hypertension in the multivariate analysis, greater than even well-established risk factors such as CKD, and diabetes 26 , 27 . This may be because very few patients in our study population had these pre-existing comorbidities, thereby leading to underestimation of their risk on developing hypertension. Indeed, the absence of comorbidities in younger and healthier patients may make COVID-19 a greater risk factor for new-onset hypertension in this population. Mental health during COVID-19 pandemic may also play an important role in the development of new-onset hypertension. Prior studies show increased levels of anxiety, mood, substance abuse, and sleep disorders among patients with COVID-19 compared to contemporary controls 28 . These conditions have been associated with an increase in the subsequent diagnosis of new-onset hypertension 29 . Likewise, we found anxiety, depression, insomnia, and substance use disorders to be independent risk factors for developing hypertension. Moreover, certain antidepressant and antipsychotic medications are linked to increased risk of hypertension. Dedicated studies analyzing the relationship between COVID-19, psychiatric conditions, psychiatric medications, and new-onset hypertension are necessary. Although we used COVID-19 negative contemporary controls who experienced similar pandemic effect, there could be differential pandemic effects in COVID-19 versus non-COVID-19 patients. In addition to effects of the SARS-CoV-2 infection, the social and economic stress imparted by the COVID-19 pandemic lockdown also contribute to the development of hypertension. The increase seen in hypertension diagnoses and mean systolic/diastolic blood pressures 30 , 31 after the COVID-19 pandemic cannot be explained entirely by those infected by SARS-CoV-2 32 . Instead, the increase in mental health stress, financial stress, weight gain, decrease in physical activity, and limited access to healthcare 33 – 37 likely also play a significant role in the development of hypertension post-pandemic. Mechanism The exact mechanism by which COVID-19 may cause new-onset hypertension is not known, though several possible mechanisms have been proposed. One mechanism is via disruption of the renin-angiotensin aldosterone system by the binding of SARS-CoV-2 to the ACE2 receptor, thus, preventing the conversion of angiotensin II (vasoconstrictor) to angiotensin [1–7] (vasodilator). This imbalance results in excess angiotensin II and leads to sustained vasoconstriction and increased blood pressure. Another mechanism is the “cytokine storm” whereby COVID-19 triggers a systemic inflammatory response resulting in irreversible damage to the vascular endothelium by cytokines such as IL-6 and TNF-ɑ. This permanent damage to the blood vessels impairs their ability to relax, resulting in hypertension. Lastly, it is possible that during the acute phase of SARS-CoV-2 infection, sympathetic activation, which is typical of a viral illness, may persist beyond the acute phase of infection, or may even have some degree of delayed-onset. Despite the resolution of COVID-19 symptoms, it is possible that sympathetic tone could remain persistently elevated, resulting in new-onset hypertension in the post-acute setting. Regardless of its exact mechanism, we found COVID-19 to be an independent risk factor for developing new-onset hypertension, even after matching for other major comorbidities. Clinical Implications Diagnosing post-COVID hypertension may pose a unique challenge to healthcare providers. The onset of hypertension can occur well beyond the acute COVID period and in relatively young and healthy patients, making it difficult to determine an etiology. We urge healthcare providers to not dismiss new-onset hypertension in COVID-19 patients as white coat hypertension, and to instead conduct a holistic workup with a particular emphasis on patients’ mental and psychiatric health as well as new-onset comorbidities. This study also highlights the need for close long-term follow-up and blood pressure monitoring in COVID-19 patients. The implementation of post-COVID blood pressure screening programs may be beneficial especially in populations/communities with predisposing risk factors. Limitations There are a few limitations to this study. First, this is a single health-center study although there were 1.7 million patients within the Stony Brook Healthcare System. Furthermore, our analysis was limited to patients who returned. We did not study outcomes with respective to COVID-19 vaccination status because many patients could receive vaccine elsewhere. Moreover, there may be patients in either cohort with white coat hypertension or, conversely, those with masked hypertension. Hospitalized patients may be screened sooner and more frequently after COVID-19 which might have contributed to an earlier and higher incidence of outcomes. As is the case with any retrospective cohort study, the outcomes of this study may be affected by confounders that were not accounted for. Conclusions This study reports an increased incidence of new-onset hypertension in both hospitalized and non-hospitalized COVID-19 patients compared to propensity matched COVID-negative contemporary controls up to 3 years post index date. COVID-19 was found to be a major independent risk factor for the development of new-onset hypertension, comparable to other known risk factors for hypertension. These findings highlight the need for close long-term follow-up, holistic workups, and vigilant blood pressure screening and/or monitoring for at-risk COVID-19 patients. Declarations Author Contributions: MB contributed to the study conceptualization, study design, data collection, data analysis, manuscript drafting and editing. JG, SB, TA, and RL contributed to data analysis, manuscript drafting and editing. TD contributed to study conceptualization, study design, manuscript drafting and editing, and supervision. Competing Interests: The authors declare no competing interests. Data Availability: The datasets used and/or analyzed during the current study are available from the corresponding author on request. Ethics Declaration: The TriNetX Network is compliant with the Health Insurance Portability and Accountability Act (HIPAA), a federal law protecting the confidentiality of health information. All data acquired from TriNetX was de-identified and displayed as an aggregate and/or average rather than an individual patient basis. References Davis, H. E., McCorkell, L., Vogel, J. M. & Topol, E. J. Long COVID: major findings, mechanisms and recommendations. Nat. Rev. Microbiol. 21 , 133–146. 10.1038/s41579-022-00846-2 (2023). Psaty, B. M. et al. Association between blood pressure level and the risk of myocardial infarction, stroke, and total mortality: the cardiovascular health study. Arch. 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Racial/Ethnic Disparities in Hypertension Prevalence, Awareness, Treatment, and Control in the United States, 2013 to 2018. Hypertension 78 , 1719–1726. 10.1161/hypertensionaha.121.17570 (2021). Leng, B., Jin, Y., Li, G., Chen, L. & Jin, N. Socioeconomic status and hypertension: a meta-analysis. J. Hypertens. 33 , 221–229. 10.1097/hjh.0000000000000428 (2015). HDPulse : An Ecosystem of Minority Health and Health Disparities Resources. National Institute on Minority Health and Health Disparities. , < https://hdpulse.nimhd.nih.gov (. Ku, E., Lee, B. J., Wei, J. & Weir, M. R. Hypertension in CKD: Core Curriculum 2019. Am. J. Kidney Dis. 74 , 120–131. 10.1053/j.ajkd.2018.12.044 (2019). Lago, R. M., Singh, P. P. & Nesto, R. W. Diabetes and hypertension. Nat. Clin. Pract. Endocrinol. Metab. 3 , 667. 10.1038/ncpendmet0638 (2007). Wang, Y., Su, B., Xie, J., Garcia-Rizo, C. & Prieto-Alhambra, D. Long-term risk of psychiatric disorder and psychotropic prescription after SARS-CoV-2 infection among UK general population. Nat. Hum. Behav. 8 , 1076–1087. 10.1038/s41562-024-01853-4 (2024). Stein, D. J. et al. Associations between mental disorders and subsequent onset of hypertension. Gen. Hosp. Psychiatry . 36 , 142–149 (2014). Gotanda, H. et al. Changes in Blood Pressure Outcomes Among Hypertensive Individuals During the COVID-19 Pandemic: A Time Series Analysis in Three US Healthcare Organizations. Hypertension 79 , 2733–2742. 10.1161/HYPERTENSIONAHA.122.19861 (2022). Nolde, J. M. et al. Trends in blood pressure changes and hypertension prevalence in Australian adults before and during the COVID-19 pandemic. J. Clin. Hypertens. (Greenwich) . 26 , 145–154. 10.1111/jch.14761 (2024). Trimarco, V. et al. Incidence of new-onset hypertension before, during, and after the COVID-19 pandemic: a 7-year longitudinal cohort study in a large population. BMC Med. 22 , 127. 10.1186/s12916-024-03328-9 (2024). Al Zaman, K. et al. Impact of COVID-19 Pandemic on Weight Change Among Adults in the UAE. Int. J. Gen. Med. 16 , 1661–1670. 10.2147/ijgm.S407934 (2023). Argabright, S. T. et al. COVID-19-related financial strain and adolescent mental health. Lancet Reg. Health Am. 16 , 100391. 10.1016/j.lana.2022.100391 (2022). Khubchandani, J., Price, J. H., Sharma, S., Wiblishauser, M. J. & Webb, F. J. COVID-19 pandemic and weight gain in American adults: A nationwide population-based study. Diabetes Metab. Syndr. 16 , 102392. 10.1016/j.dsx.2022.102392 (2022). Pujolar, G., Oliver-Anglès, A., Vargas, I. & Vázquez, M. L. Changes in Access to Health Services during the COVID-19 Pandemic: A Scoping Review. Int. J. Environ. Res. Public. Health . 19 10.3390/ijerph19031749 (2022). Rodrigues, M., Silva, R. & Franco, M. COVID-19: Financial Stress and Well-Being in Families. J. Fam Issues . 44 , 1254–1275. 10.1177/0192513x211057009 (2023). Additional Declarations No competing interests reported. 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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-6074295","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":424024084,"identity":"ba8f60c3-6c9e-4768-b6ce-3a99ac3fdd64","order_by":0,"name":"Montek S Boparai","email":"data:image/png;base64,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","orcid":"","institution":"Albert Einstein College of Medicine and Montefiore Medical Center","correspondingAuthor":true,"prefix":"","firstName":"Montek","middleName":"S","lastName":"Boparai","suffix":""},{"id":424024085,"identity":"dc3f0ccf-1a97-42bf-b4de-48343479919a","order_by":1,"name":"Jacob Gordon","email":"","orcid":"","institution":"Stony Brook University","correspondingAuthor":false,"prefix":"","firstName":"Jacob","middleName":"","lastName":"Gordon","suffix":""},{"id":424024086,"identity":"3b12e197-8f45-4217-99bd-068b657a77c1","order_by":2,"name":"Sandi Bajrami","email":"","orcid":"","institution":"Stony Brook University","correspondingAuthor":false,"prefix":"","firstName":"Sandi","middleName":"","lastName":"Bajrami","suffix":""},{"id":424024087,"identity":"7b690272-e555-486d-b687-61ef9b078067","order_by":3,"name":"Tharun Alamuri","email":"","orcid":"","institution":"Stony Brook University","correspondingAuthor":false,"prefix":"","firstName":"Tharun","middleName":"","lastName":"Alamuri","suffix":""},{"id":424024088,"identity":"c4c9b26a-9350-4e5f-b837-e4cf746ae29a","order_by":4,"name":"Ryan Lee","email":"","orcid":"","institution":"Stony Brook University","correspondingAuthor":false,"prefix":"","firstName":"Ryan","middleName":"","lastName":"Lee","suffix":""},{"id":424024089,"identity":"5990f33c-3094-4e80-8e1d-5131cd8ef891","order_by":5,"name":"Tim Q Duong","email":"","orcid":"","institution":"Albert Einstein College of Medicine and Montefiore Medical Center","correspondingAuthor":false,"prefix":"","firstName":"Tim","middleName":"Q","lastName":"Duong","suffix":""}],"badges":[],"createdAt":"2025-02-20 19:08:16","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6074295/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6074295/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41598-025-14617-5","type":"published","date":"2025-08-06T15:58:09+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":78249416,"identity":"5b232dd3-2177-4713-b7ec-7196c021fcfe","added_by":"auto","created_at":"2025-03-11 09:48:04","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":73134,"visible":true,"origin":"","legend":"\u003cp\u003eFlowchart of cohort selection.\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-6074295/v1/cb4ba2d88436b35577448227.png"},{"id":78249399,"identity":"04e0ad4d-c109-4e91-9b20-f5224b9ca35c","added_by":"auto","created_at":"2025-03-11 09:48:01","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":26211,"visible":true,"origin":"","legend":"\u003cp\u003eCumulative incidences curves from 1 month - 3 years after COVID-19 for a) Hospitalized COVID-positive patients compared to matched COVID-negative patients and b) Non-hospitalized COVID-positive patients compared to matched COVID-negative patients.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-6074295/v1/1bf3cb333e308cae9e691312.png"},{"id":88814285,"identity":"fa51504d-5275-460f-960d-8a69a1d878ac","added_by":"auto","created_at":"2025-08-11 16:09:30","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":812079,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6074295/v1/8784bde6-c3cf-40a5-bf2a-92871967eb2e.pdf"},{"id":78249406,"identity":"8594a328-da17-46a1-8dcd-91e75ef5c1be","added_by":"auto","created_at":"2025-03-11 09:48:01","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":97629,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryFigures.docx","url":"https://assets-eu.researchsquare.com/files/rs-6074295/v1/08a2572b954a4fc260ab713f.docx"},{"id":78249400,"identity":"12e634b0-d0d4-463d-adea-4f163f47c19c","added_by":"auto","created_at":"2025-03-11 09:48:01","extension":"docx","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":19101,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryTables.docx","url":"https://assets-eu.researchsquare.com/files/rs-6074295/v1/ed12193711601bc4ff3e4a72.docx"},{"id":78249402,"identity":"6bd4f67f-a841-464f-a7be-10c504c30c38","added_by":"auto","created_at":"2025-03-11 09:48:01","extension":"docx","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":18117,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryInformation.docx","url":"https://assets-eu.researchsquare.com/files/rs-6074295/v1/5862f80b84f48deec26c6bc9.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Incidence and Risk Factors of New-onset Hypertension Up To 3 years Post SARS-CoV-2 Infection","fulltext":[{"header":"Introduction","content":"\u003cp\u003eThe long-term health consequences of COVID-19 have garnered significant attention as multitude of persistent and systemic effects of the virus are uncovered, collectively referred to as post-acute sequelae of COVID-19 (PASC), or \u0026ldquo;long COVID \u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e.\u0026rdquo; While much focus has been placed on respiratory and neurological sequelae, emerging evidence highlights the potential for COVID-19 to contribute to the development of long-term cardiovascular conditions, including hypertension. Hypertension, a leading global cause of morbidity and mortality, often develops insidiously but carries significant implications for cardiovascular events such as myocardial infarction, stroke, and heart failure \u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eMechanistically, COVID-19 may cause hypertension by persistent systemic inflammation, endothelial dysfunction, and/or autonomic dysregulation. SARS-CoV-2 infection has been shown to directly impair endothelial function through downregulation of ACE2 receptors, promoting vasoconstriction, oxidative stress, and pro-inflammatory states. In addition, the virus may exacerbate pre-existing subclinical cardiovascular conditions, potentially unmasking hypertension in individuals with predisposing risk factors. Chronic dysregulation of the renin-angiotensin-aldosterone system (RAAS), a pathway critical to blood pressure regulation, may also play a central role in the long-term sequelae od COVID-19 .\u003c/p\u003e \u003cp\u003eThe association between COVID-19 and new-onset hypertension is poorly understood as only a handful of studies have reported on this \u003csup\u003e\u003cspan additionalcitationids=\"CR4 CR5 CR6 CR7 CR8\" citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e. Moreover, many of these studies have a small sample size, lack COVID-negative controls, do not adequately distinguish between new-onset and persistent hypertension, or do not provide an in-depth analysis of risk factors. Most studies are limited to at most to 6-months follow-up \u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e. As such, the long-term (\u0026gt;\u0026thinsp;1 year) effects of SARS-CoV-2 on developing hypertension has yet to be adequately analyzed.\u003c/p\u003e \u003cp\u003eThis study of over 64,000 COVID-positive patients investigates the long-term association between COVID-19 and new-onset hypertension at 3-year follow-up to the capture sustained effects of SARS-CoV-2. Moreover, we stratified the COVID-positive patients into hospitalized and non-hospitalized cohorts to compare the effect of COVID-19 severity on the development of new-onset hypertension. We also identified the major risk factors for developing new-onset hypertension. Understanding long-term risk of hypertension in patients with COVID-19 is essential for guiding post-COVID care, including targeted monitoring and early intervention strategies, to mitigate the broader cardiovascular burden associated with the pandemic.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy Design and Data\u003c/h2\u003e \u003cp\u003eThis is a retrospective cohort study conducted on the TriNetX research platform using de-identified Electronic Medical Record data from over 1.7\u0026nbsp;million patients from January 2020 to October 2024 in the Stony Brook University Healthcare Network. TriNetX is a global web-based platform that allows researchers to identify and characterize patient cohorts and analyze outcomes. Broadly, the data includes demographics, diagnoses (based on International Classification of Diseases, 10th Revision, Clinical Modification codes), procedures (based primarily on International Classification of Diseases, 10th Revision, Procedure Coding System, Current Procedural Terminology, Healthcare Common Procedure Coding System, and Systemized Nomenclature of Medicine codes), medications (based on Veteran Affairs and Anatomical Therapeutic Chemical codes), laboratory values (based on Logical Observation Identifiers, Names, and Codes or curated separately by TriNetX), and genomics data.\u003c/p\u003e \u003cp\u003eWith one of the largest global COVID-19 datasets, multiple studies have used TriNetX to study the outcomes of COVID-19 \u003csup\u003e10\u0026ndash;12\u003c/sup\u003e. Details regarding the data extraction, transformation, and validation performed by TriNetX have been published \u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e. Other external validation studies have also confirmed the reliability of TriNetX in analyzing large-scale data \u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003e Due to the retrospective nature of the study, the Stony Brook University Institutional Review Board waived the need of obtaining informed consent. The data reviewed is a secondary analysis of existing data, does not involve intervention or interaction with human subjects, and is de-identified per the de-identification standard defined in Section \u0026sect;\u0026nbsp;164.514(a) of the HIPAA Privacy Rule. The process by which the data is de-identified is attested to through a formal determination by a qualified expert as defined in Section \u0026sect;\u0026nbsp;164.514(b)(1) of the HIPAA Privacy Rule. This formal determination by a qualified expert refreshed on December 2020. All methods were carried out in accordance with the TriNetX guidelines and regulations. All experimental protocols were approved by Stony Brook University.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003ePatient Selection\u003c/h3\u003e\n\u003cp\u003eWe queried the Stony Brook TriNetX database from January 2020 to October 2024 for patients with COVID-19 and without COVID-19 who did not have a pre-existing diagnosis of hypertension (assessed on October 10, 2024). Details regarding the search query, identification codes, and inclusion/exclusion criteria can be found in the supplemental materials. Briefly, COVID-19 was defined as a positive SARS-CoV-2 PCR test. COVID-negative patients were defined as those with a negative SARS-CoV-2 PCR test who never had a subsequent positive SARS-COV-2 PCR test. Essential hypertension was defined using the ICD code I10. The COVID-positive cohort was then subdivided into those who were hospitalized during the time of their COVID infection and those who were not. These cohorts were then 1:1 propensity matched with the COVID-negative cohort before analyzing outcomes.\u003c/p\u003e\n\u003ch3\u003eFollow-Up and Outcomes\u003c/h3\u003e\n\u003cp\u003eThe follow-up period for this study was between 1-month to 3 years after COVID-19. The primary outcome of this study was a new diagnosis of hypertension based on ICD-10 code. Cumulative incidence was obtained by assessing the number of outcomes on a monthly basis. All outcomes in this study were categorical.\u003c/p\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis\u003c/h2\u003e \u003cp\u003eStatistical analyses were performed directly on the TriNetX platform which, for the purposes of this study, used R 4.0.2 software. All variables in this study were categorical and expressed a frequency or percentage of the total cohort with the exception of age which was expressed as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation. Patients who met the inclusion criteria were 1:1 propensity matched for age, race, sex, ethnicity, and comorbidities including heart failure, ischemic heart disease, diabetes, chronic kidney disease, asthma, chronic obstructive pulmonary disease, obesity, and tobacco use before analyzing outcomes. Matching was performed on the TriNetX platform by greedy nearest neighbor matching. Hazard ratios and confidence intervals were generated by the TriNetX platform for all outcomes. Multivariate odds ratios and their 95% confidence intervals (CI) were calculated using Microsoft Excel.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eFigure \u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e shows the cohort selection flowchart for this study. From January 2020 to October 2024, there were 64,250 patients who tested positive for COVID-19 and 225,980 patients who tested negative for COVID-19 and never had a positive test. There were 172,660 (76.40%) COVID-negative patients and 42,900 (66.77%) COVID-positive patients who had no past medical history of hypertension. The COVID-positive cohort was further divided into 5,500 (12.94%) hospitalized patients and 37,350 (87.06%) non-hospitalized patients. Prior to matching, the number of patients with new-onset hypertension at 3 years follow-up was 410 (9.93%), 1,650 (4.66%), and 12,030 (6.94%) for the hospitalized COVID-positive, non-hospitalized COVID-positive, and COVID-negative cohorts, respectively.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e shows the baseline patient demographics for the three cohorts. Hospitalized COVID-positive patients were more likely to be older (50.4\u0026thinsp;\u0026plusmn;\u0026thinsp;23.7 vs 35.9\u0026thinsp;\u0026plusmn;\u0026thinsp;23.8, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) white (63% vs 56%, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), male (54% vs 45%, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and had a higher prevalence of CAD, CHF, CKD, diabetes, obesity, COPD, and tobacco use (all p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), but not asthma (p\u0026thinsp;=\u0026thinsp;0.68), compared to COVID-negative patients.\u003c/p\u003e \u003cp\u003eHospitalized COVID-positive patients were more likely to be older (50.4\u0026thinsp;\u0026plusmn;\u0026thinsp;23.7 vs 36.5\u0026thinsp;\u0026plusmn;\u0026thinsp;22.4, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) white (63% vs 52%, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), male (54% vs 42%, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and had higher prevalence of CAD, CHF, CKD, diabetes, COPD, and tobacco use (all p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), but lower prevalence of asthma and obesity (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), compared to non-hospitalized COVID-positive patients.\u003c/p\u003e \u003cp\u003eNon-hospitalized COVID-positive patients were more likely to be older (36.5\u0026thinsp;\u0026plusmn;\u0026thinsp;22.4 vs 35.9\u0026thinsp;\u0026plusmn;\u0026thinsp;23.8, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), less likely to be white (52% vs 56%, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), less likely to be male (42% vs 45%, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and had higher prevalence of CAD, CHF, CKD, diabetes, obesity, COPD, asthma, and tobacco use (all p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) compared to COVID-negative patients.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePatient demographics. * p\u0026thinsp;\u0026lt;\u0026thinsp;0.05, ** p\u0026thinsp;\u0026lt;\u0026thinsp;0.01, and *** p\u0026thinsp;\u0026lt;\u0026thinsp;0.001 compared to COVID-19 negative patients. ^ p\u0026thinsp;\u0026lt;\u0026thinsp;0.05, ^^ p\u0026thinsp;\u0026lt;\u0026thinsp;0.01, and ^^^ p\u0026thinsp;\u0026lt;\u0026thinsp;0.001 between hospitalized and non-hospitalized COVID-19 patients.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDemographics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCOVID-Positive Hospitalized (5,550)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCOVID-Positive Non-Hospitalized\u003c/p\u003e \u003cp\u003e(N\u0026thinsp;=\u0026thinsp;37,350)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCOVID-Negative\u003c/p\u003e \u003cp\u003e(172,660)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e50.4\u0026thinsp;\u0026plusmn;\u0026thinsp;23.7\u003csup\u003e***^^^\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e36.5\u0026thinsp;\u0026plusmn;\u0026thinsp;22.4\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e35.9\u0026thinsp;\u0026plusmn;\u0026thinsp;23.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3000 (54%)\u003csup\u003e***^^^\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15,680 (42%)\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e72,810 (45%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWhite Race\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3,490 (63%)\u003csup\u003e***^^^\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19,510 (52%)\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e96,640 (56%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBlack Race\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e390 (7%)\u003csup\u003e^^^\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2,040 (5%)\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11,130 (6%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAsian Race\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e160 (3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1,280 (3%)\u003csup\u003e^\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5,890 (3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnknown Race\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,500 (27%)\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14,380 (39%)\u003csup\u003e***^^^\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e59,040 (34%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNon-Hispanic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3,720 (67%)\u003csup\u003e***^^^\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22,200 (59%)\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e111,260 (64%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHispanic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,130 (20%)\u003csup\u003e***^^^\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6,080 (16%)\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e30,250 (18%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnknown Ethnicity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e700 (13%)\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9,080 (24%)\u003csup\u003e***^^^\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e31,800 (18%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eComorbidities\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCAD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e300 (5%)\u003csup\u003e***^^^\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e990 (3%)\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3,190 (2%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCHF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e190 (3%)\u003csup\u003e***^^^\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e350 (1%)\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1,300 (1%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCKD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e150 (3%)\u003csup\u003e***^^^\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e360 (1%)\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1,100 (1%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiabetes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e340 (6%)\u003csup\u003e***^^^\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1520 (4%)\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4,660 (2%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCOPD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e200 (4%)\u003csup\u003e***^^^\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e460 (1%)\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1,780 (1%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAsthma\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e450 (8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4,510 (12%)\u003csup\u003e***^^^\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14,320 (9%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eObesity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e550 (10%)\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4,350 (12%)\u003csup\u003e***^^^\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13,510 (8%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTobacco Use\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e140 (3%)\u003csup\u003e***^^\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e720 (2%)\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2,700 (2%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eFigures 2\u003c/b\u003e shows the 3-year cumulative incidence curve for new-onset hypertension. At 3-year follow-up, hospitalized COVID-positive patients were at greater risk of developing new-onset hypertension compared to COVID-negative controls (HR\u0026thinsp;=\u0026thinsp;1.57, 95%CI [1.35\u0026ndash;1.81]). Non-hospitalized COVID-positive patients were not more likely to develop hypertension compared to COVID-negative controls (HR: 1.05 [0.98\u0026ndash;1.13]). Hospitalized COVID-positive patients were also at greater risk of developing new-onset hypertension compared to non-hospitalized COVID-positive patients (HR: 1.42, 95%CI [1.24\u0026ndash;1.63]).\u003c/p\u003e \u003cp\u003eFor the non-hospitalized COVID-positive cohort, the results were then separated into two distinct time periods: 1-month to 1.5-years after COVID, and 1.5-years to 3-years after COVID. Non-hospitalized patients were not more likely to develop hypertension in the 1-month to 1.5-year time period (HR: 1.00, 95% CI [0.92\u0026ndash;1.10]), but were more likely in the 1.5-3-year time period (HR: 1.14, 95% CI [1.01\u0026ndash;1.28]) compared to COVID-negative controls.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e shows the multivariate odds ratios for patients with new-onset hypertension at 3-years follow-up. COVID-19 patients were more likely to develop new-onset hypertension compared to COVID-19 negative controls (OR\u0026thinsp;=\u0026thinsp;1.76 [1.62\u0026ndash;1.92]). Confounders included male (OR\u0026thinsp;=\u0026thinsp;1.22 [1.15\u0026ndash;2.30]), older than 50 years old (OR\u0026thinsp;=\u0026thinsp;2.39 [2.24\u0026ndash;2.55]), Hispanic (OR\u0026thinsp;=\u0026thinsp;1.12 [1.01\u0026ndash;1.24]) and have greater comorbidities (ORs ranging from 1.12 to 3.07).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e\u003cb\u003eMultivariate\u003c/b\u003e odds ratios for new-onset hypertension between 1 month and 3 years follow up for all COVID-positive and COVID-negative patients.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOdds Ratio\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCOVID +\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.62\u0026ndash;1.92\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u0026thinsp;\u0026gt;\u0026thinsp;50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.24\u0026ndash;2.55\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.15\u0026ndash;1.30\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBlack\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.87\u0026ndash;1.13\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAsian\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.84\u0026ndash;1.22\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther Race\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.81\u0026ndash;0.93\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHispanic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.01\u0026ndash;1.24\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCAD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.54\u0026ndash;1.83\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.02\u0026ndash;1.26\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCKD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.23\u0026ndash;1.57\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiabetes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.38\u0026ndash;1.63\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eObesity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.86\u0026ndash;3.31\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAsthma\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.43\u0026ndash;1.72\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCOPD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.09\u0026ndash;1.40\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTobacco Use\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.67\u0026ndash;2.26\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAnxiety\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.30\u0026ndash;2.10\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDepression\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.36\u0026ndash;1.61\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInsomnia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.56\u0026ndash;2.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSubstance Use\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.23\u0026ndash;1.43\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study evaluated the risk of developing new-onset hypertension up to 3 years post SARS-CoV-2 infection on 1.7\u0026nbsp;million patients in the Stony Brook Medicine health system of multiple hospitals on Long Island. To our knowledge, this is the first study to report these findings at up to 3-years post infection follow-up. The main findings were: 1) 9.93% hospitalized patients and 4.66% non-hospitalized developed new-onset hypertension after COVID-19, 2) Hospitalized COVID-positive patients were more likely to develop new-onset hypertension compared to propensity matched COVID-negative patients (HR\u0026thinsp;=\u0026thinsp;1.57) and non-hospitalized COVID-positive patients (HR: 1.42). 3) COVID-19 was one of the five greatest risk factors for developing new-onset hypertension, along with obesity, age\u0026thinsp;\u0026gt;\u0026thinsp;50, tobacco use, and insomnia.\u003c/p\u003e\n\u003ch3\u003eIncidence of New-onset Hypertension\u003c/h3\u003e\n\u003cp\u003eA few studies have investigated new-onset hypertension after COVID-19. Zhang et al. analyzed 45,398 COVID-19 patients in the Montefiore Health System in the Bronx and reported the incidence of new-onset hypertension to be 20.6% and 10.85% in hospitalized and non-hospitalized patients, respectively, at 6 months follow-up \u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e. Hospitalized patients with COVID-19 were 2.23 ([95% CI, 1.48\u0026ndash;3.54]; P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) times and nonhospitalized patients with COVID-19 were 1.52 ([95% CI, 1.22\u0026ndash;1.90]; P\u0026thinsp;\u0026lt;\u0026thinsp;0.01) times more likely to develop new-onset hypertension than influenza counterparts with adjustment of confounders. Notably, the Montefiore cohort was predominantly Black and/or Hispanic patients and had a high prevalence of pre-existing comorbidities. Our cohort were predominantly Whites and was comparatively younger and had a lower prevalence of comorbidities. Despite these differences, we found similar risk factors for developing new-onset hypertension including age, male sex, and major preexisting comorbidities.\u003c/p\u003e \u003cp\u003eIn a study of 168 COVID-19 patients, Akpek et al. found the incidence of new-onset hypertension to be 12% at 30-day follow-up \u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e. Delacic et al. report an incidence of 16% in 199 COVID-19 patients at 3-month follow-up \u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e. Vyas et al. report an incidence of 32.3% in 248 COVID-19 patients at 1-year follow-up \u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e. In addition to small sample sizes, lack of risk factor analysis, and a relatively short follow-up period, these studies do not have COVID-negative controls nor statistical analyses for comparison. Azama et al. conducted a larger study of 5,355 COVID-19 patients and found an incidence of 17% at 1-year follow-up. This study was conducted at a cardiology clinic which may have inflated the incidence. This study also did not use COVID-negative controls for comparison, but they did identify risk factors associated with elevated blood pressure including increased age and comorbidities, which is consistent with our study. Lastly, Cohen et al. found COVID-19 patients\u0026thinsp;\u0026ge;\u0026thinsp;65 years old to be more likely to experience hypertension compared to propensity matched COVID-negative patients (risk difference 4.43, 2.27\u0026ndash;6.37) at 3-month follow-up \u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e. They did not report the percent incidence. Generally, the patients in these aforementioned studies were older and/or had a higher prevalence of comorbidities compared to our cohorts which may explain the elevated incidence rate in these studies. Differences in experimental design, patient profiles (i.e., age, race/ethnicity, and pre-existing comorbidities), comparison group, regional and temporal differences in the severity of COVID-19 cases, duration of study (observation time), and other factors could all have contributed to differences in findings. Studies of populations from more affected regions and studies consisting of the first few months of the pandemic, likely have a higher incidence of outcome.\u003c/p\u003e \u003cp\u003eBoth the magnitude and the rate cumulative incidence of new HTN in the hospitalized COVID-19 cohort were markedly higher than those of COVID-negative controls in the first year post infection. By contrast, the magnitude and the rate cumulative incidence of new HTN in the nonhospitalized COVID-19 cohort were similar to COVID-negative cohort. These observations suggest that non-hospitalized COVID-19 patients experience an initial indolent phase followed by a late onset of hypertension. Indeed, whereas a more severe course of COVID-19 may lead to a relatively immediate diagnosis of hypertension, a less severe course of COVID-19 may simply accelerate the progression of the hypertensive disease process in patients who may already be at risk of developing it down the line.\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eRisk Factors\u003c/h2\u003e \u003cp\u003eNot surprisingly, patients with age over 50, male sex, and major comorbidities (CAD, HF, CKD, DM, obesity, asthma, COPD, tobacco use) were found to be at higher risk of new-onset hypertension. Age is a well-known risk factor for developing hypertension and has also been shown to be an independent predictor of COVID-severity \u003csup\u003e \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e,\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e \u003c/sup\u003e. Sex differences in developing hypertension have been hypothesized to occur, in part, due to differences in the influence of sex hormones on activating the renin-angiotensin-aldosterone system (RAAS) \u003csup\u003e \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e \u003c/sup\u003e. Likewise, this differential activation of the RAAS in males, coupled with the dysregulation of the RAAS by SARS-CoV-2, may explain why males have a greater predisposition for increased COVID severity \u003csup\u003e \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e \u003c/sup\u003e. This increased severity may lead to greater rates of hypertension in males post-COVID. Obesity was the greatest risk factor for development of new-onset hypertension, which is unsurprising considering obesity is a known cause of hypertension \u003csup\u003e \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e \u003c/sup\u003e, is linked to worse COVID-19 outcomes by several studies \u003csup\u003e \u003cspan additionalcitationids=\"CR21\" citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e \u003c/sup\u003e and is associated with every other chronic comorbidity found to be a risk factor. Despite black race having a well-known association with developing hypertension \u003csup\u003e \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e \u003c/sup\u003e, we did not find black race to be a significant risk factor for developing hypertension, which may be due to having low proportions of black patients in our cohort. Moreover, the high socioeconomic status of the area around Stony Brook Hospital (Suffolk County has the third highest median income, \u003cspan\u003e$\u003c/span\u003e141,671, in New York State) may contribute to lower rates of hypertension in our cohort, regardless of race \u003csup\u003e \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e,\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e \u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eCOVID-19 status was the 5th greater risk factor for new-onset hypertension in the multivariate analysis, greater than even well-established risk factors such as CKD, and diabetes \u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e,\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e. This may be because very few patients in our study population had these pre-existing comorbidities, thereby leading to underestimation of their risk on developing hypertension. Indeed, the absence of comorbidities in younger and healthier patients may make COVID-19 a greater risk factor for new-onset hypertension in this population.\u003c/p\u003e \u003cp\u003eMental health during COVID-19 pandemic may also play an important role in the development of new-onset hypertension. Prior studies show increased levels of anxiety, mood, substance abuse, and sleep disorders among patients with COVID-19 compared to contemporary controls \u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e. These conditions have been associated with an increase in the subsequent diagnosis of new-onset hypertension \u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e. Likewise, we found anxiety, depression, insomnia, and substance use disorders to be independent risk factors for developing hypertension. Moreover, certain antidepressant and antipsychotic medications are linked to increased risk of hypertension. Dedicated studies analyzing the relationship between COVID-19, psychiatric conditions, psychiatric medications, and new-onset hypertension are necessary. Although we used COVID-19 negative contemporary controls who experienced similar pandemic effect, there could be differential pandemic effects in COVID-19 versus non-COVID-19 patients.\u003c/p\u003e \u003cp\u003eIn addition to effects of the SARS-CoV-2 infection, the social and economic stress imparted by the COVID-19 pandemic lockdown also contribute to the development of hypertension. The increase seen in hypertension diagnoses and mean systolic/diastolic blood pressures \u003csup\u003e\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e,\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e after the COVID-19 pandemic cannot be explained entirely by those infected by SARS-CoV-2 \u003csup\u003e32\u003c/sup\u003e. Instead, the increase in mental health stress, financial stress, weight gain, decrease in physical activity, and limited access to healthcare \u003csup\u003e\u003cspan additionalcitationids=\"CR34 CR35 CR36\" citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e likely also play a significant role in the development of hypertension post-pandemic.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eMechanism\u003c/h2\u003e \u003cp\u003eThe exact mechanism by which COVID-19 may cause new-onset hypertension is not known, though several possible mechanisms have been proposed. One mechanism is via disruption of the renin-angiotensin aldosterone system by the binding of SARS-CoV-2 to the ACE2 receptor, thus, preventing the conversion of angiotensin II (vasoconstrictor) to angiotensin [1\u0026ndash;7] (vasodilator). This imbalance results in excess angiotensin II and leads to sustained vasoconstriction and increased blood pressure. Another mechanism is the \u0026ldquo;cytokine storm\u0026rdquo; whereby COVID-19 triggers a systemic inflammatory response resulting in irreversible damage to the vascular endothelium by cytokines such as IL-6 and TNF-ɑ. This permanent damage to the blood vessels impairs their ability to relax, resulting in hypertension. Lastly, it is possible that during the acute phase of SARS-CoV-2 infection, sympathetic activation, which is typical of a viral illness, may persist beyond the acute phase of infection, or may even have some degree of delayed-onset. Despite the resolution of COVID-19 symptoms, it is possible that sympathetic tone could remain persistently elevated, resulting in new-onset hypertension in the post-acute setting. Regardless of its exact mechanism, we found COVID-19 to be an independent risk factor for developing new-onset hypertension, even after matching for other major comorbidities.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eClinical Implications\u003c/h2\u003e \u003cp\u003eDiagnosing post-COVID hypertension may pose a unique challenge to healthcare providers. The onset of hypertension can occur well beyond the acute COVID period and in relatively young and healthy patients, making it difficult to determine an etiology. We urge healthcare providers to not dismiss new-onset hypertension in COVID-19 patients as white coat hypertension, and to instead conduct a holistic workup with a particular emphasis on patients\u0026rsquo; mental and psychiatric health as well as new-onset comorbidities. This study also highlights the need for close long-term follow-up and blood pressure monitoring in COVID-19 patients. The implementation of post-COVID blood pressure screening programs may be beneficial especially in populations/communities with predisposing risk factors.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eLimitations\u003c/h2\u003e \u003cp\u003eThere are a few limitations to this study. First, this is a single health-center study although there were 1.7\u0026nbsp;million patients within the Stony Brook Healthcare System. Furthermore, our analysis was limited to patients who returned. We did not study outcomes with respective to COVID-19 vaccination status because many patients could receive vaccine elsewhere. Moreover, there may be patients in either cohort with white coat hypertension or, conversely, those with masked hypertension. Hospitalized patients may be screened sooner and more frequently after COVID-19 which might have contributed to an earlier and higher incidence of outcomes. As is the case with any retrospective cohort study, the outcomes of this study may be affected by confounders that were not accounted for.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusions","content":"\u003cp\u003eThis study reports an increased incidence of new-onset hypertension in both hospitalized and non-hospitalized COVID-19 patients compared to propensity matched COVID-negative contemporary controls up to 3 years post index date. COVID-19 was found to be a major independent risk factor for the development of new-onset hypertension, comparable to other known risk factors for hypertension. These findings highlight the need for close long-term follow-up, holistic workups, and vigilant blood pressure screening and/or monitoring for at-risk COVID-19 patients.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthor Contributions:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMB\u003c/strong\u003e contributed to the study conceptualization, study design, data collection, data analysis, manuscript drafting and editing. \u003cstrong\u003eJG, SB, TA, and RL\u003c/strong\u003e contributed to data analysis, manuscript drafting and editing. \u003cstrong\u003eTD\u003c/strong\u003e contributed to study conceptualization, study design, manuscript drafting and editing, and supervision.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interests:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used and/or analyzed during the current study are available from the corresponding author on request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics Declaration:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe TriNetX Network is compliant with the Health Insurance Portability and Accountability Act (HIPAA), a federal law protecting the confidentiality of health information. 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Fam Issues\u003c/em\u003e. \u003cstrong\u003e44\u003c/strong\u003e, 1254\u0026ndash;1275. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1177/0192513x211057009\u003c/span\u003e\u003c/span\u003e (2023).\u003c/span\u003e\u003c/li\u003e\n\u003c/ol\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":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"COVID-19, SARS-CoV-2, hypertension, long-COVID, PASC","lastPublishedDoi":"10.21203/rs.3.rs-6074295/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6074295/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eCOVID-19 can trigger new cardiovascular events, including hypertension, in the acute setting. However, few studies have reported sustained new-onset hypertension post-infection. Moreover, these studies have a small sample size, inadequate controls, and a short (\u0026lt;\u0026thinsp;1 year) follow-up time. This retrospective cohort study of 64,000 COVID-19 patients from the Stony Brook Health System assessed the incidence and risk factors for new-onset hypertension after COVID-19. Contemporary COVID-negative controls were obtained and propensity matched for age, race, sex, ethnicity, and major comorbidities before analyzing outcomes. The primary outcome was new-onset hypertension up to 3 years post index date.\u003c/p\u003e \u003cp\u003eAbout 9.93% hospitalized patients and 4.66% non-hospitalized developed new-onset hypertension after COVID-19. Hospitalized COVID-positive patients were more likely to develop hypertension compared to COVID-negative controls (HR\u0026thinsp;=\u0026thinsp;1.57, 95%CI [1.35\u0026ndash;1.81]) and non-hospitalized COVID-positive controls (HR: 1.42, 95%CI [1.24\u0026ndash;1.63]). Non-hospitalized COVID-positive patients were not more likely to develop hypertension compared to COVID-negative controls (HR: 1.05 [0.98\u0026ndash;1.13]). COVID-19 was one of the five greatest risk factors for developing hypertension.\u003c/p\u003e \u003cp\u003eThese findings underscore COVID-19 patients are at increased risk of developing hypertension well beyond the acute phase of the disease. Close long-term follow-up, holistic workups, and vigilant blood pressure screening and/or monitoring for COVID-19 patients is needed.\u003c/p\u003e","manuscriptTitle":"Incidence and Risk Factors of New-onset Hypertension Up To 3 years Post SARS-CoV-2 Infection","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-03-11 09:47:55","doi":"10.21203/rs.3.rs-6074295/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-05-21T05:12:30+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-05-20T08:21:41+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-05-06T03:26:14+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"302823440656017624328649908186147667098","date":"2025-04-21T03:49:41+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-04-21T03:19:43+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"60199455622508325987036723804908911192","date":"2025-04-21T02:43:36+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"257883007321916492609634467608302249455","date":"2025-04-21T02:40:39+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-04-21T02:17:41+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-03-07T17:01:49+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-03-04T13:56:29+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-03-04T06:28:41+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2025-02-20T19:02:15+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"bb27f704-6306-453e-abef-dceb17c98c5e","owner":[],"postedDate":"March 11th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":45185835,"name":"Health sciences/Cardiology"},{"id":45185836,"name":"Health sciences/Diseases/Infectious diseases"},{"id":45185837,"name":"Health sciences/Diseases/Cardiovascular diseases/Hypertension"}],"tags":[],"updatedAt":"2025-08-11T16:06:56+00:00","versionOfRecord":{"articleIdentity":"rs-6074295","link":"https://doi.org/10.1038/s41598-025-14617-5","journal":{"identity":"scientific-reports","isVorOnly":false,"title":"Scientific Reports"},"publishedOn":"2025-08-06 15:58:09","publishedOnDateReadable":"August 6th, 2025"},"versionCreatedAt":"2025-03-11 09:47:55","video":"","vorDoi":"10.1038/s41598-025-14617-5","vorDoiUrl":"https://doi.org/10.1038/s41598-025-14617-5","workflowStages":[]},"version":"v1","identity":"rs-6074295","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6074295","identity":"rs-6074295","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}