A Nonlinear Association of Serum Uric Acid with All-cause and Cardiovascular Mortality among Patients with Cardiovascular Disease: A Cohort Study from NHANES

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This study found a nonlinear, U-shaped association between serum uric acid levels and both all-cause and cardiovascular mortality in patients with cardiovascular disease.

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This cohort study examined the nonlinear association between serum uric acid (SUA) and all-cause mortality (ACM) and cardiovascular mortality (CVM) in 3,977 adults with cardiovascular disease (CVD) from NHANES (2005–2018), using weighted Cox regression, Kaplan–Meier curves, restricted cubic spline models, and threshold analyses with death determined via National Death Index linkage through December 31, 2019. Over a median follow-up of 68 months, 34.4% of participants died, and after multivariable adjustment, participants in the highest SUA quartile had higher risks of ACM (HR 1.38) and CVM (HR 1.40) than others. Modeling showed a nonlinear, U-shaped relationship between SUA and both ACM and CVM, including subgroup-specific nonlinear thresholds among CVD patients with chronic kidney disease. This paper does not explicitly discuss endometriosis or adenomyosis; it was included in the corpus via a keyword match in the upstream search index.

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Abstract Background The relationship between serum uric acid (SUA) and mortality in patients with cardiovascular disease (CVD) remains controversial. We aimed to explore the relationship between SUA and all-cause mortality (ACM) and cardiovascular mortality (CVM) in adult patients with CVD. Methods This cohort study included 3977 patients with CVD from the National Health and Nutrition Examination Survey (2005–2018). Death outcomes were determined by linking National Death Index (NDI) records through December 31, 2019. We explored the association of SUA with mortality using weighted Cox proportional hazards regression models, subgroup analysis, Kaplan-Meier survival curves, weighted restricted cubic spline (RCS) models, and weighted threshold effect analysis among patients with CVD. Results During a median follow-up of 68 months (interquartile range, 34–110 months), 1,369 (34.4%) of the 3,977 patients with cardiovascular disease died, of which 536 (13.5%) died of cardiovascular deaths and 833 (20.9%) died of non-cardiovascular deaths. In a multivariable-adjusted model (Model 3), the risk of ACM (HR 1.38, 95% CI 1.16–1.64, p < 0.001) and the risk of CVM (HR 1.40, 95% CI 1.06–1.10, p < 0.001) for participants in the SUA Q4 group were significantly higher. In patients with CVD, RCS regression analysis revealed a nonlinear association (p < 0.001 for all nonlinearities) between SUA, ACM, and CVM. Subgroup analysis showed a nonlinear association between ACM and CVM with SUA in patients with CVD combined with chronic kidney disease (CKD), with thresholds of 5.49 and 5.64, respectively. Time-dependent ROC curves indicated areas under the curve of 0.61, 0.60, 0.58, and 0.55 for 1-, 3-, 5-, and 10-year survival for ACM and 0.69, 0.61, 0.59, and 0.56 for CVM, respectively. Conclusions We demonstrate that SUA is an independent prognostic factor for the risk of ACM and CVM in patients with CVD, supporting a U-shaped association between SUA and mortality, with thresholds of 5.49 and 5.64, respectively. In patients with CVD combined with CKD, the association of the ACM and the CVM with SUA remains nonlinear.
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A Nonlinear Association of Serum Uric Acid with All-cause and Cardiovascular Mortality among Patients with Cardiovascular Disease: A Cohort Study from NHANES | 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 A Nonlinear Association of Serum Uric Acid with All-cause and Cardiovascular Mortality among Patients with Cardiovascular Disease: A Cohort Study from NHANES Yan-Lin LV, Yong-Ming LIU, Kai-Xuan DONG, Xiong-Bin MA, Lin QIAN This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4512214/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 04 Nov, 2024 Read the published version in Scientific Reports → Version 1 posted 14 You are reading this latest preprint version Abstract Background The relationship between serum uric acid (SUA) and mortality in patients with cardiovascular disease (CVD) remains controversial. We aimed to explore the relationship between SUA and all-cause mortality (ACM) and cardiovascular mortality (CVM) in adult patients with CVD. Methods This cohort study included 3977 patients with CVD from the National Health and Nutrition Examination Survey (2005–2018). Death outcomes were determined by linking National Death Index (NDI) records through December 31, 2019. We explored the association of SUA with mortality using weighted Cox proportional hazards regression models, subgroup analysis, Kaplan-Meier survival curves, weighted restricted cubic spline (RCS) models, and weighted threshold effect analysis among patients with CVD. Results During a median follow-up of 68 months (interquartile range, 34–110 months), 1,369 (34.4%) of the 3,977 patients with cardiovascular disease died, of which 536 (13.5%) died of cardiovascular deaths and 833 (20.9%) died of non-cardiovascular deaths. In a multivariable-adjusted model (Model 3), the risk of ACM (HR 1.38, 95% CI 1.16–1.64, p < 0.001) and the risk of CVM (HR 1.40, 95% CI 1.06–1.10, p < 0.001) for participants in the SUA Q4 group were significantly higher. In patients with CVD, RCS regression analysis revealed a nonlinear association (p < 0.001 for all nonlinearities) between SUA, ACM, and CVM. Subgroup analysis showed a nonlinear association between ACM and CVM with SUA in patients with CVD combined with chronic kidney disease (CKD), with thresholds of 5.49 and 5.64, respectively. Time-dependent ROC curves indicated areas under the curve of 0.61, 0.60, 0.58, and 0.55 for 1-, 3-, 5-, and 10-year survival for ACM and 0.69, 0.61, 0.59, and 0.56 for CVM, respectively. Conclusions We demonstrate that SUA is an independent prognostic factor for the risk of ACM and CVM in patients with CVD, supporting a U-shaped association between SUA and mortality, with thresholds of 5.49 and 5.64, respectively. In patients with CVD combined with CKD, the association of the ACM and the CVM with SUA remains nonlinear. Health sciences/Cardiology Health sciences/Diseases Serum uric acid Cardiovascular disease All-cause mortality Cardiovascular mortality Cohort study NHANES Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 04 Nov, 2024 Read the published version in Scientific Reports → Version 1 posted Editorial decision: Revision requested 18 Jul, 2024 Reviews received at journal 14 Jul, 2024 Reviews received at journal 08 Jul, 2024 Reviews received at journal 08 Jul, 2024 Reviewers agreed at journal 05 Jul, 2024 Reviewers agreed at journal 01 Jul, 2024 Reviews received at journal 30 Jun, 2024 Reviewers agreed at journal 20 Jun, 2024 Reviewers agreed at journal 15 Jun, 2024 Reviewers invited by journal 12 Jun, 2024 Editor assigned by journal 12 Jun, 2024 Editor invited by journal 07 Jun, 2024 Submission checks completed at journal 04 Jun, 2024 First submitted to journal 01 Jun, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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