Predictive Value of Combined Lipoprotein(a) and hs-CRP for Contrast-Induced Acute Kidney Injury After PCI in Elderly Patients With Acute Coronary Syndrome 

Predictive Value of Combined Lipoprotein(a) and hs-CRP for Contrast-Induced Acute Kidney Injury After PCI in Elderly Patients With Acute Coronary Syndrome | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Predictive Value of Combined Lipoprotein(a) and hs-CRP for Contrast-Induced Acute Kidney Injury After PCI in Elderly Patients With Acute Coronary Syndrome Xishen Zhang, Xuan Zhang, Jingkun Jin, Jiahui Ding, Shanshan Li, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9303281/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 7 You are reading this latest preprint version Abstract Background: Notwithstanding the evolution of safer contrast media and optimized hydration protocols, renal injury persists as a frequent sequela in the clinical management of acute coronary syndromes. This enduring risk stems inherently from the obligatory exposure to iodinated agents required to perform life-saving PCI. Objective: To evaluate whether pre-procedural high-sensitivity C-reactive protein (hs-CRP) combined with lipoprotein(a) [Lp(a)] improves prediction of CI-AKI after PCI in elderly patients with ACS. Methods: This retrospective study included 1,321 elderly ACS patients (age ≥60 years) treated with PCI from 2020 to 2024. The cohort was split into training and validation sets (7:3). Following the definition of CI-AKI based on established criteria, data collection encompassed baseline laboratory and clinical parameters obtained 24 hours pre-procedure. Candidate variables were identified via LASSO regression and subsequently entered into a multivariable logistic model. These analyses culminated in the development of a risk-prediction nomogram using R software. Performance evaluation involved plotting ROC curves and estimating AUC values. Crucially, the assessment prioritized verifying if the dual addition of Lp(a) and hs-CRP improved prognostic accuracy relative to their standalone counterparts. Results: Diuretic use, smoking, blood urea nitrogen (BUN), hemoglobin A1c (HbA1c), Lp(a), and hs-CRP were independently associated with CI-AKI after PCI. The combined biomarker model (hs-CRP + Lp(a)) achieved an AUC of 0.857 (95% CI 0.831–0.883), with 70.2% sensitivity and 77.2% specificity, outperforming either biomarker alone. Conclusion: Hs-CRP and Lp(a) were independent predictors of CI-AKI in elderly ACS patients undergoing PCI. Their combination improved risk discrimination and may aid pre-procedural risk stratification and targeted prevention. Lipoprotein(a) high-sensitivity C-Reactive Protein elderly patients acute coronary syndrome contrast-induced acute kidney injury Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Reviews received at journal 18 May, 2026 Reviewers agreed at journal 10 May, 2026 Reviewers invited by journal 30 Apr, 2026 Editor invited by journal 08 Apr, 2026 Editor assigned by journal 07 Apr, 2026 Submission checks completed at journal 07 Apr, 2026 First submitted to journal 02 Apr, 2026 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. 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-9303281","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":636144061,"identity":"70d1a87b-e2b7-4738-8ec9-fe86d15d12fc","order_by":0,"name":"Xishen Zhang","email":"","orcid":"","institution":"Institute of Cardiovascular Diseases, Xuzhou Medical University, Xuzhou, Jiangsu, People’s Republic of China","correspondingAuthor":false,"prefix":"","firstName":"Xishen","middleName":"","lastName":"Zhang","suffix":""},{"id":636144063,"identity":"70317817-1f2f-450f-800d-1e870f673dde","order_by":1,"name":"Xuan Zhang","email":"","orcid":"","institution":"Institute of Cardiovascular Diseases, Xuzhou Medical University, Xuzhou, Jiangsu, People’s Republic of China","correspondingAuthor":false,"prefix":"","firstName":"Xuan","middleName":"","lastName":"Zhang","suffix":""},{"id":636144064,"identity":"f8a08907-aabf-4d25-a240-1c4f8ee8d797","order_by":2,"name":"Jingkun Jin","email":"","orcid":"","institution":"Institute of Cardiovascular Diseases, Xuzhou Medical University, Xuzhou, Jiangsu, People’s Republic of China","correspondingAuthor":false,"prefix":"","firstName":"Jingkun","middleName":"","lastName":"Jin","suffix":""},{"id":636144066,"identity":"be9a8680-1e1a-4723-9119-2e3d98ac4bd6","order_by":3,"name":"Jiahui Ding","email":"","orcid":"","institution":"Institute of Cardiovascular Diseases, Xuzhou Medical University, Xuzhou, Jiangsu, People’s Republic of 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","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-cardiovascular-disorders","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bcar","sideBox":"Learn more about [BMC Cardiovascular Disorders](http://bmccardiovascdisord.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bcar/default.aspx","title":"BMC Cardiovascular Disorders","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC 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This enduring risk stems inherently from the obligatory exposure to iodinated agents required to perform life-saving PCI.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eObjective: \u003c/strong\u003eTo evaluate whether pre-procedural high-sensitivity C-reactive protein (hs-CRP) combined with lipoprotein(a) [Lp(a)] improves prediction of CI-AKI after PCI in elderly patients with ACS.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods: \u003c/strong\u003eThis retrospective study included 1,321 elderly ACS patients (age ≥60 years) treated with PCI from 2020 to 2024. The cohort was split into training and validation sets (7:3). Following the definition of CI-AKI based on established criteria, data collection encompassed baseline laboratory and clinical parameters obtained 24 hours pre-procedure. Candidate variables were identified via LASSO regression and subsequently entered into a multivariable logistic model. 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