Influencing factors and predictive models of recurrence after cryoballoon ablation for atrial fibrillation

Influencing factors and predictive models of recurrence after cryoballoon ablation for atrial fibrillation | 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 Influencing factors and predictive models of recurrence after cryoballoon ablation for atrial fibrillation Haitao Liu, Zhenghao Yu, Meijiao Lu, Chuanbin Liu This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9159360/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background : To construct and verify the influencing factors and early warning model of recurrence after cryoballoon ablation of atrial fibrillation. Methods: This study retrospectively enrolled 113 hospitalized patients with persistent atrial fibrillation (PAF) from the NHANES cohort between August 2019 and August 2022 as the modeling group for developing and validating the model. Additionally, 51 hospitalized PAF patients were recruited between August 2022 and August 2023 as an external validation group to assess the model's generalizability. Statistically analyze the recurrence of atrial fibrillation in patients after cryoballoon ablation. Univariate analysis and LASSO regression were used to screen for influencing factors. Logistic regression was used to analyze the factors influencing the recurrence of atrial fibrillation after cryoballoon ablation. A model was established and a nomogram was drawn. The area under the receiver operating characteristic (ROC) curve (AUC), calibration curve and decision curve (DCA) were used to evaluate the performance and applicability of the model. The incidences of MODS in the modeling group and the validation group were 27.43% (31/113) and 29.41% (15/51), respectively. Result The postoperative recurrence rates of the modeling group and the validation group were 27.43% (31/113) and 29.41% (15/51), respectively, respectively. The results of univariate analysis in the modeling group showed that the postoperative recurrence group and the postoperative non-recurrence group had diabetes, N-terminal pro-brain natriuretic peptide (NT-proBNP), left coronary artery (LAD), and left ventricular end-diastolic diameter. There were statistically significant differences in the comparisons of (LVDd), neutrophil-to-lymphocyte ratio (NLR), left ventricular ejection fraction (LVEF), B-type natriuretic peptide (BNP), and RIPV60s(all P <0.05). LASSO regression analysis screened out the variables: NT-proBNP, NLR, and RIPV60s. The results of Logistic regression analysis showed that NLR ( OR =4.987, 95%CI: 1.547-15.906), NT-proBNP ( OR =4.526, 95%CI: 1.723-11.485), and RIPV60s ( OR =3.419, 95%CI: 1.268-9.647 is a risk factor for recurrence after cryoballoon ablation of atrial fibrillation ( P <0.05). The correction curves of the modeling group and the verification group tend to approach the standard curve. The ROC curve results of the modeling group and the validation group showed that the AUC of the nomogram model for predicting the recurrence of atrial fibrillation after cryotherapy balloon ablation was 0.846 (95%CI: 0.768-0.924, P <0.001) and 0.802 (95%CI: 0.715-0.889, P <0.001), respectively. The DCA curve indicates that the modeling group has a greater net clinical benefit for patients within the threshold range of 0.05 to 0.89, while the validation group can achieve a greater net clinical benefit for patients within the threshold range of 0.04 to 0.91. Conclusion: NT-proBNP, NLR, and RIPV60s are closely related to the recurrence of atrial fibrillation after cryotherapy balloon ablation. The early warning model constructed based on this has good predictive value. Persistent atrial fibrillation Left ventricular ejection fraction Recurrence Early warning model Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted 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. 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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-9159360","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":611647101,"identity":"c7043712-3c74-468d-b4cf-7f23ab2c5299","order_by":0,"name":"Haitao Liu","email":"","orcid":"","institution":"Western Medical Branch of PLA General Hospital","correspondingAuthor":false,"prefix":"","firstName":"Haitao","middleName":"","lastName":"Liu","suffix":""},{"id":611647102,"identity":"82e90939-be2d-4b3d-a4ca-f6de4afa7d4f","order_by":1,"name":"Zhenghao Yu","email":"","orcid":"","institution":"Medical School of Chinese PLA","correspondingAuthor":false,"prefix":"","firstName":"Zhenghao","middleName":"","lastName":"Yu","suffix":""},{"id":611647103,"identity":"9c49940d-9f75-49d1-a036-09615b6fbad0","order_by":2,"name":"Meijiao Lu","email":"","orcid":"","institution":"Western Medical Branch of PLA General Hospital","correspondingAuthor":false,"prefix":"","firstName":"Meijiao","middleName":"","lastName":"Lu","suffix":""},{"id":611647104,"identity":"92d96fa7-8c33-48eb-9bb2-141d2abff65d","order_by":3,"name":"Chuanbin Liu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA/UlEQVRIiWNgGAWjYDCCAxBKho2BgQ3ESGBjYD5w4EMFXi2MDUCKB0kLW+LBGWeI0MIA0wJkGx/mbcGtg+948/MHH/cw8PBJJD97zFNzJ49PuufDAd4GBnl+sQNYtUieOWbYOOMZ0GESaebGPMeeFbPJnN1wQHIHg+HM2QlYtRjcyGFs5jkA0pLDJs3DdjixTSJ3wwHDMwwJBreJ0vIPpCXnwYHENmK18LaBtTAcOIhHC8gvM2eAtPA8M5Oc23e4GOgpg4MNZyRw+gUYYg8+fDjAICffnvxM4s23w3nyM5Iff/5TYSPPL41dCxT8xxCRwKd8FIyCUTAKRgEBAAADNWBITzXUaQAAAABJRU5ErkJggg==","orcid":"","institution":"the First Medical Center of PLA General Hospital","correspondingAuthor":true,"prefix":"","firstName":"Chuanbin","middleName":"","lastName":"Liu","suffix":""}],"badges":[],"createdAt":"2026-03-18 12:24:25","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9159360/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9159360/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":107986847,"identity":"20fc6650-fb86-474f-b280-61e8e9e8260b","added_by":"auto","created_at":"2026-04-28 09:27:04","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":403740,"visible":true,"origin":"","legend":"","description":"","filename":"Influencingfactorsandpredictivemodelsofrecurrenceaftercryoballoonablationforatrialfibrillation.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9159360/v1_covered_f3035e2a-27b3-4133-8a9c-bfa18d475d06.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Influencing factors and predictive models of recurrence after cryoballoon ablation for atrial fibrillation","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"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":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Persistent atrial fibrillation, Left ventricular ejection fraction, Recurrence, Early warning model","lastPublishedDoi":"10.21203/rs.3.rs-9159360/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9159360/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground\u003c/strong\u003e: To construct and verify the influencing factors and early warning model of recurrence after cryoballoon ablation of atrial fibrillation.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods: \u003c/strong\u003eThis study retrospectively enrolled 113 hospitalized patients with persistent atrial fibrillation (PAF) from the NHANES cohort between August 2019 and August 2022 as the modeling group for developing and validating the model. Additionally, 51 hospitalized PAF patients were recruited between August 2022 and August 2023 as an external validation group to assess the model's generalizability. Statistically analyze the recurrence of atrial fibrillation in patients after cryoballoon ablation. Univariate analysis and LASSO regression were used to screen for influencing factors. Logistic regression was used to analyze the factors influencing the recurrence of atrial fibrillation after cryoballoon ablation. A model was established and a nomogram was drawn. The area under the receiver operating characteristic (ROC) curve (AUC), calibration curve and decision curve (DCA) were used to evaluate the performance and applicability of the model. The incidences of MODS in the modeling group and the validation group were 27.43% (31/113) and 29.41% (15/51), respectively. \u003cstrong\u003eResult\u003c/strong\u003e The postoperative recurrence rates of the modeling group and the validation group were 27.43% (31/113) and 29.41% (15/51), respectively, respectively. The results of univariate analysis in the modeling group showed that the postoperative recurrence group and the postoperative non-recurrence group had diabetes, N-terminal pro-brain natriuretic peptide (NT-proBNP), left coronary artery (LAD), and left ventricular end-diastolic diameter. There were statistically significant differences in the comparisons of (LVDd), neutrophil-to-lymphocyte ratio (NLR), left ventricular ejection fraction (LVEF), B-type natriuretic peptide (BNP), and RIPV60s(all \u003cem\u003eP\u003c/em\u003e\u0026lt;0.05). LASSO regression analysis screened out the variables: NT-proBNP, NLR, and RIPV60s. The results of Logistic regression analysis showed that NLR (\u003cem\u003eOR\u003c/em\u003e=4.987, 95%CI: 1.547-15.906), NT-proBNP (\u003cem\u003eOR\u003c/em\u003e=4.526, 95%CI: 1.723-11.485), and RIPV60s (\u003cem\u003eOR\u003c/em\u003e=3.419, 95%CI: 1.268-9.647 is a risk factor for recurrence after cryoballoon ablation of atrial fibrillation (\u003cem\u003eP\u003c/em\u003e\u0026lt;0.05). The correction curves of the modeling group and the verification group tend to approach the standard curve. The ROC curve results of the modeling group and the validation group showed that the AUC of the nomogram model for predicting the recurrence of atrial fibrillation after cryotherapy balloon ablation was 0.846 (95%CI: 0.768-0.924, \u003cem\u003eP\u003c/em\u003e\u0026lt;0.001) and 0.802 (95%CI: 0.715-0.889, \u003cem\u003eP\u003c/em\u003e\u0026lt;0.001), respectively. The DCA curve indicates that the modeling group has a greater net clinical benefit for patients within the threshold range of 0.05 to 0.89, while the validation group can achieve a greater net clinical benefit for patients within the threshold range of 0.04 to 0.91.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion: \u003c/strong\u003eNT-proBNP, NLR, and RIPV60s are closely related to the recurrence of atrial fibrillation after cryotherapy balloon ablation. The early warning model constructed based on this has good predictive value.\u003c/p\u003e","manuscriptTitle":"Influencing factors and predictive models of recurrence after cryoballoon ablation for atrial fibrillation","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-03-26 23:24:41","doi":"10.21203/rs.3.rs-9159360/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"7b4c25d7-6744-4889-885a-39b93895dc02","owner":[],"postedDate":"March 26th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-04-28T09:26:34+00:00","versionOfRecord":[],"versionCreatedAt":"2026-03-26 23:24:41","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9159360","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9159360","identity":"rs-9159360","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}