Development and validation of a multivariable nomogram predictive of kidney function after cardiopulmonary resuscitation

Development and validation of a multivariable nomogram predictive of kidney function after cardiopulmonary resuscitation | 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 Development and validation of a multivariable nomogram predictive of kidney function after cardiopulmonary resuscitation Jinxiang Wang, Heng Jin, Yanfen Chai, Hongbao Guo, Guowu Xu, Jinxuan Liu, and 7 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7659182/v1 This work is licensed under a CC BY 4.0 License Status: Under Revision Version 1 posted 16 You are reading this latest preprint version Abstract Background Kidney injury is an important manifestation of post resuscitation syndrome (PRS) and a significant factor leading to high mortality rates after cardiopulmonary resuscitation (CPR).This study aimed to develop and validate a multivariable nomogram to predict estimated glomerular filtration rate (eGFR) after CPR to aassess the degree of kidney injury and provide protective strategies. Methods The clinical data of patients after CPR admitted to Tianjin Medical University General Hospital from January 2017 to June 2024 and Tianjin Medical University General Hospital Airport Hospital from January 2017 to December 2019 were retrospectively analyzed.The patients those who met the inclusion criteria were randomly divided into training and validation cohorts at a ratio of 7∶3.We obtained clinical data from January 2021 to June 2023 at First Affiliated Hospital of Hebei North University as external validation.Univariate and multivariate linear regression method were used to identify independent risk factors for 7d-eGFR after CPR,develope and validate (internal and external) a multivariate nomogram model.Calibration curve, Bland-Altman plot and Paired-T validation were used to validate the predictive performance of the model. Results We included 439 patients after CPR, of whom 307 were in training cohort and 132 were in validation cohort.And 105 patients were included as an external validation cohort.Multivariable linear analysis showed that age (Beta coefficient[β] 95% confidence interval [CI]:-0.344[-0.528, -0.160])、hypertension (-3.610[-5.968,-1.252])、diabetes mellitus (-2.992[-5.295,-0.689])、no flow time (-0.577[-0.996, -0.158])、baseline eGFR (0.349[0.269 ~ 0.429])、ACR (-0.042[-0.073, -0.011])、lactic acid (-0.650[-1.214,-0.086]) were the independent risk factors for eGFR after CPR.A composite nomogram predicted eGFR with good accuracy in training(97.07%), internal validation (95.45%) and external validation (91.08%) cohorts.The nomogram model has good predictive ability for AKI and CKD in training (AUC = 0.933 and 0.882), internal validation (AUC = 0.915 and 0.859) and external validation (AUC = 0.823 and 0.784) cohorts. Conclusion The developed nomogram could be used to predict 7d-eGFR after CPR, which helped to accurately quantify kidney function levels and early predict the probability of AKI and CKD progression, achieving early detection and intervention, thereby improving the prognosis of patients after CPR. Glomerular filtration rate Acute kidney injury Chronic kidney disease Nomogram prediction model Post-resuscitation syndrome Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Revision Version 1 posted Editorial decision: Revision requested 09 Jan, 2026 Reviewers agreed at journal 08 Jan, 2026 Reviews received at journal 08 Jan, 2026 Reviewers agreed at journal 06 Jan, 2026 Reviews received at journal 05 Jan, 2026 Reviewers agreed at journal 05 Jan, 2026 Reviews received at journal 20 Dec, 2025 Reviews received at journal 16 Dec, 2025 Reviewers agreed at journal 09 Dec, 2025 Reviewers agreed at journal 09 Dec, 2025 Reviewers agreed at journal 13 Oct, 2025 Reviewers invited by journal 05 Oct, 2025 Editor invited by journal 25 Sep, 2025 Editor assigned by journal 22 Sep, 2025 Submission checks completed at journal 22 Sep, 2025 First submitted to journal 19 Sep, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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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-7659182","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":529021564,"identity":"234250a6-67da-462f-b274-92aaba080665","order_by":0,"name":"Jinxiang 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resuscitation","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-nephrology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bnep","sideBox":"Learn more about [BMC Nephrology](http://bmcnephrol.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bnep/default.aspx","title":"BMC Nephrology","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Glomerular filtration rate, Acute kidney injury, Chronic kidney disease, Nomogram prediction model, Post-resuscitation syndrome","lastPublishedDoi":"10.21203/rs.3.rs-7659182/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7659182/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cb\u003eBackground\u003c/b\u003e Kidney injury is an important manifestation of post resuscitation syndrome (PRS) and a significant factor leading to high mortality rates after cardiopulmonary resuscitation (CPR).This study aimed to develop and validate a multivariable nomogram to predict estimated glomerular filtration rate (eGFR) after CPR to aassess the degree of kidney injury and provide protective strategies.\u003c/p\u003e\u003cp\u003e\u003cb\u003eMethods\u003c/b\u003e The clinical data of patients after CPR admitted to Tianjin Medical University General Hospital from January 2017 to June 2024 and Tianjin Medical University General Hospital Airport Hospital from January 2017 to December 2019 were retrospectively analyzed.The patients those who met the inclusion criteria were randomly divided into training and validation cohorts at a ratio of 7∶3.We obtained clinical data from January 2021 to June 2023 at First Affiliated Hospital of Hebei North University as external validation.Univariate and multivariate linear regression method were used to identify independent risk factors for 7d-eGFR after CPR,develope and validate (internal and external) a multivariate nomogram model.Calibration curve, Bland-Altman plot and Paired-T validation were used to validate the predictive performance of the model.\u003c/p\u003e\u003cp\u003e\u003cb\u003eResults\u003c/b\u003e We included 439 patients after CPR, of whom 307 were in training cohort and 132 were in validation cohort.And 105 patients were included as an external validation cohort.Multivariable linear analysis showed that age (Beta coefficient[β] 95% confidence interval [CI]:-0.344[-0.528, -0.160])、hypertension (-3.610[-5.968,-1.252])、diabetes mellitus (-2.992[-5.295,-0.689])、no flow time (-0.577[-0.996, -0.158])、baseline eGFR (0.349[0.269\u0026thinsp;~\u0026thinsp;0.429])、ACR (-0.042[-0.073, -0.011])、lactic acid (-0.650[-1.214,-0.086]) were the independent risk factors for eGFR after CPR.A composite nomogram predicted eGFR with good accuracy in training(97.07%), internal validation (95.45%) and external validation (91.08%) cohorts.The nomogram model has good predictive ability for AKI and CKD in training (AUC\u0026thinsp;=\u0026thinsp;0.933 and 0.882), internal validation (AUC\u0026thinsp;=\u0026thinsp;0.915 and 0.859) and external validation (AUC\u0026thinsp;=\u0026thinsp;0.823 and 0.784) cohorts.\u003c/p\u003e\u003cp\u003e\u003cb\u003eConclusion\u003c/b\u003e The developed nomogram could be used to predict 7d-eGFR after CPR, which helped to accurately quantify kidney function levels and early predict the probability of AKI and CKD progression, achieving early detection and intervention, thereby improving the prognosis of patients after CPR.\u003c/p\u003e","manuscriptTitle":"Development and validation of a multivariable nomogram predictive of kidney function after cardiopulmonary resuscitation","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-10-16 23:14:02","doi":"10.21203/rs.3.rs-7659182/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision 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