Independent Risk Factors and Predictive Modeling of Pulmonary Embolism in Patients with Acute Ischemic Stroke

Independent Risk Factors and Predictive Modeling of Pulmonary Embolism in Patients with Acute Ischemic Stroke | 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 Independent Risk Factors and Predictive Modeling of Pulmonary Embolism in Patients with Acute Ischemic Stroke Sangsang Chen, Shixin Wu, Jie Liu, Yanfang Liu, Yanlan Huang, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8494748/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 Objective: To investigate independent risk factors for pulmonary embolism (PE) in patients with acute ischemic stroke (AIS) and to develop a nomogram for PE risk prediction. Methods: We retrospectively analyzed clinical data from 214 AIS patients admitted between January 2017 and January 2025, including a training set (n = 150) and an independent validation set (n = 64). Demographic characteristics, medical history, cerebral infarction features, and laboratory parameters were collected. Independent risk factors for PE were identified using univariate and multivariate logistic regression analyses. A nomogram was constructed and internally validated using bootstrap resampling (1,000 iterations) and externally validated by temporal separation. Model performance was assessed using the concordance index (C-index), receiver operating characteristic (ROC) curve, calibration curve, and decision curve analysis (DCA). Results: Prolonged prothrombin time (PT), decreased serum albumin and globulin levels, elevated serum urea, and a history of cancer were identified as independent risk factors for PE in AIS patients (P < 0.01). The nomogram demonstrated excellent discrimination, with a C-index of 0.933 (95% CI: 0.893–0.974) in the training set and 0.902 (95% CI: 0.823–0.981) in the validation set. Calibration curves showed good agreement between predicted and observed outcomes, and DCA indicated meaningful clinical benefit. A total score ≥99 (predicted probability ≥50%) was defined as the high-risk threshold. Conclusions: Prolonged PT, hypoalbuminemia, hypoglobulinemia, elevated serum urea and history of cancer are independent risk factors for PE in AIS patients. The nomogram prediction model is helpful for early identification of patients with high risk of PE after AIS. Acute ischemic stroke Pulmonary embolism Risk factors Predictive models 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. 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-8494748","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":582201745,"identity":"f3401d0a-74c4-483e-a19a-b71c70d01f96","order_by":0,"name":"Sangsang Chen","email":"","orcid":"","institution":"Guangxi Medical University First Affiliated Hospital: The First Affiliated Hospital of Guangxi Medical University","correspondingAuthor":false,"prefix":"","firstName":"Sangsang","middleName":"","lastName":"Chen","suffix":""},{"id":582201746,"identity":"7bd7c547-d0cb-4ed9-8bd1-b7092ca4de27","order_by":1,"name":"Shixin 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11:08:24","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8494748/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8494748/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":105882759,"identity":"abb0b0b7-4fde-4f9c-bada-3dcc3c222d98","added_by":"auto","created_at":"2026-04-01 06:58:24","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":624333,"visible":true,"origin":"","legend":"","description":"","filename":"Manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8494748/v1_covered_408ba105-1e7f-4871-b517-005619de0b3f.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Independent Risk Factors and Predictive Modeling of Pulmonary Embolism in Patients with Acute Ischemic 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models","lastPublishedDoi":"10.21203/rs.3.rs-8494748/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8494748/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eObjective:\u003c/strong\u003e To investigate independent risk factors for pulmonary embolism (PE) in patients with acute ischemic stroke (AIS) and to develop a nomogram for PE risk prediction.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods: \u003c/strong\u003eWe retrospectively analyzed clinical data from 214 AIS patients admitted between January 2017 and January 2025, including a training set (n = 150) and an independent validation set (n = 64). Demographic characteristics, medical history, cerebral infarction features, and laboratory parameters were collected. Independent risk factors for PE were identified using univariate and multivariate logistic regression analyses. A nomogram was constructed and internally validated using bootstrap resampling (1,000 iterations) and externally validated by temporal separation. Model performance was assessed using the concordance index (C-index), receiver operating characteristic (ROC) curve, calibration curve, and decision curve analysis (DCA).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e Prolonged prothrombin time (PT), decreased serum albumin and globulin levels, elevated serum urea, and a history of cancer were identified as independent risk factors for PE in AIS patients (P \u0026lt; 0.01). The nomogram demonstrated excellent discrimination, with a C-index of 0.933 (95% CI: 0.893–0.974) in the training set and 0.902 (95% CI: 0.823–0.981) in the validation set. Calibration curves showed good agreement between predicted and observed outcomes, and DCA indicated meaningful clinical benefit. A total score ≥99 (predicted probability ≥50%) was defined as the high-risk threshold.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions:\u003c/strong\u003e Prolonged PT, hypoalbuminemia, hypoglobulinemia, elevated serum urea and history of cancer are independent risk factors for PE in AIS patients. The nomogram prediction model is helpful for early identification of patients with high risk of PE after AIS.\u003c/p\u003e","manuscriptTitle":"Independent Risk Factors and Predictive Modeling of Pulmonary Embolism in Patients with Acute Ischemic Stroke","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-01-30 10:49:43","doi":"10.21203/rs.3.rs-8494748/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":"5f622705-79f9-4ee1-b85d-a06913acbf3b","owner":[],"postedDate":"January 30th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-04-01T06:57:50+00:00","versionOfRecord":[],"versionCreatedAt":"2026-01-30 10:49:43","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8494748","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8494748","identity":"rs-8494748","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}