Geospatial Analysis of Out-of-Hospital Cardiac Arrest Incidence

Geospatial Analysis of Out-of-Hospital Cardiac Arrest Incidence | 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Article Geospatial Analysis of Out-of-Hospital Cardiac Arrest Incidence Atsushi Senda This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7736852/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 8 You are reading this latest preprint version Abstract Background In urban areas, abundant medical resources improve outcomes for patients with out-of-hospital cardiac arrest (OHCA). However, metropolitan environments present unique pre-hospital transportation challenges rarely observed in rural areas, such as complex transportation networks and high-rise buildings. Additionally, social factors, such as economic disparities within the same city, may affect prognostic outcomes. The aim of this study was to identify urban-specific factors affecting patient outcomes by analyzing prognostic differences among patients with OHCA transported to an emergency center in the heart of a major city. Methods In this retrospective observational study, data regarding patients transported to Tokyo Medical and Dental University Hospital between June 1, 2016 and May 30, 2022 were extracted from electronic records. Using Bayesian spatial modeling, the relationship between geographical factors and neurological outcomes was analyzed. The relationships between on-scene response time and transport time of emergency medical services were also examined. Results A correlation was observed between neurological outcomes and geographical factors, such as the distance from the OHCA scene to the emergency center. Population density, building floor level, and land prices were also associated with neurological outcomes. Conclusions The findings indicate that geographical factors in metropolitan areas affect patient outcomes. Furthermore, they highlight the importance of large-scale, multicenter studies in establishing more appropriate healthcare facilities in urban regions. Gaussian process Integrated nested Laplace approximation Out-of-hospital cardiac arrest Spatial modelling Stochastic partial differential equation Urban Figures Figure 1 Figure 2 Figure 3 Figure 4 Full Text Additional Declarations No competing interests reported. Supplementary Files Additionalfile1.docx Additional file 1. (.docx)The original Figure 1 without annotations. The map information in this figure is based on Google Maps, and its use complies with the License Agreements (https://cloud.google.com/mapsplatform/terms/). Additionalfile2.docx Additional file 2.(.docx) The original Figure 2 without annotations. The map information in this figure is based on Google Maps, and its use complies with the License Agreements (https://cloud.google.com/maps-platform/terms/). Cite Share Download PDF Status: Under Review Version 1 posted Reviews received at journal 10 Nov, 2025 Reviewers agreed at journal 07 Nov, 2025 Reviewers agreed at journal 31 Oct, 2025 Reviewers invited by journal 31 Oct, 2025 Editor invited by journal 03 Oct, 2025 Editor assigned by journal 02 Oct, 2025 Submission checks completed at journal 02 Oct, 2025 First submitted to journal 28 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. 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-7736852","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":542913261,"identity":"eefb45a6-7286-4388-85ad-faa500a770aa","order_by":0,"name":"Atsushi 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08:47:20","extension":"html","order_by":18,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":137197,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7736852/v1/fe2f7321678fb10edaea940d.html"},{"id":95806101,"identity":"389457e9-5c13-41f4-b455-084883009d6c","added_by":"auto","created_at":"2025-11-13 08:47:16","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":1764559,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eNeurological Outcomes of Patients with Shockable Rhythm Out-of-Hospital Cardiac Arrest in Relation to Geographical Factors\u003c/strong\u003e\u003cbr\u003e\nNeurological outcomes in relation to geographical factors before adjustment for the presence of a witness and bystander cardiopulmonary resuscitation (a), and after adjustment (b). Red circles indicate tertiary medical centers, while the red triangle marks the location of Tokyo Medical and Dental University. Map data are sourced from Google Maps and used in accordance with the License Agreements (https://cloud.google.com/maps-platform/terms/).\u003c/p\u003e\n\u003cp\u003eAbbreviation: CPC, Glasgow–Pittsburgh Cerebral Performance Category\u003c/p\u003e","description":"","filename":"fig1.png","url":"https://assets-eu.researchsquare.com/files/rs-7736852/v1/5a6eafb4a0e99a44480c8bff.png"},{"id":95806041,"identity":"b8358c64-5c9b-4a3f-8142-d7ca0d15a610","added_by":"auto","created_at":"2025-11-13 08:47:12","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":1064913,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eRelationship between Geographical and Temporal Factors\u003c/strong\u003e\u003cbr\u003e\nOn-scene response time (time from EMS arrival at the scene to departure) in relation to geographical factors (a). Transport time (time from scene departure to arrival at the emergency department) in relation to geographical factors (b). The red triangle marks Tokyo Medical and Dental University. Map data are sourced from Google Maps and comply with the License Agreements (https://cloud.google.com/maps-platform/terms/).\u003c/p\u003e","description":"","filename":"fig2.png","url":"https://assets-eu.researchsquare.com/files/rs-7736852/v1/678aa8caf5adcec601c1ce0e.png"},{"id":95805888,"identity":"76d0f62a-bb19-4aa0-aafb-87c885387db3","added_by":"auto","created_at":"2025-11-13 08:47:03","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":27464,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eRelationship between Temporal Factors and Neurological Outcomes\u003c/strong\u003e\u003cbr\u003e\nAssociation between on-scene response time (EMS arrival to departure) and neurological outcomes (a), and between transport time (scene departure to emergency department arrival) and neurological outcomes (b). Gray shading indicates the 95% confidence interval.\u003c/p\u003e\n\u003cp\u003eAbbreviations: CPC, Glasgow–Pittsburgh Cerebral Performance Category; EMS, emergency medical services\u003c/p\u003e","description":"","filename":"fig3.png","url":"https://assets-eu.researchsquare.com/files/rs-7736852/v1/4ea3b2855f3fe43f1db30a21.png"},{"id":95805826,"identity":"1c653d2c-1d33-48ba-a2e2-b9d8e02d9e9d","added_by":"auto","created_at":"2025-11-13 08:46:57","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":1104331,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eGeographical Factors Potentially Affecting Neurological Outcomes\u003c/strong\u003e\u003cbr\u003e\nNeurological outcomes relative to geographical factors after adjustment for witness presence, bystander CPR, on-scene response time, and transport time (a). Land prices (b) and floor area ratios (c) based on public data. Number of tertiary emergency medical facilities located before TMDU from each location (d). The red triangle marks Tokyo Medical and Dental University. Land price and floor area ratio data were obtained from the National Land Information Division, National Spatial Planning and Regional Policy Bureau, Ministry of Land, Infrastructure, Transport, and Tourism (https://nlftp.mlit.go.jp/). Map data are sourced from Google Maps and used in accordance with the License Agreements (https://cloud.google.com/maps-platform/terms/).\u003c/p\u003e\n\u003cp\u003eAbbreviations: CPC, Glasgow–Pittsburgh Cerebral Performance Category; JPY, Japanese Yen\u003c/p\u003e","description":"","filename":"fig4.png","url":"https://assets-eu.researchsquare.com/files/rs-7736852/v1/2780c2816fda5126e9330cba.png"},{"id":95810293,"identity":"84567b58-546c-45f3-bcfe-58d861a1d82a","added_by":"auto","created_at":"2025-11-13 08:52:17","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1175790,"visible":true,"origin":"","legend":"","description":"","filename":"manuscriptplain.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7736852/v1_covered_fa649aa0-407b-4113-85fb-7c6c8b972aec.pdf"},{"id":95805852,"identity":"14982039-0827-4e97-9cf0-3d3b595271b4","added_by":"auto","created_at":"2025-11-13 08:46:59","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":37993965,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAdditional file 1.\u003c/strong\u003e (.docx)The original Figure 1 without annotations.\u003c/p\u003e\n\u003cp\u003eThe map information in this figure is based on Google Maps, and its use complies with the License Agreements (https://cloud.google.com/mapsplatform/terms/).\u003c/p\u003e","description":"","filename":"Additionalfile1.docx","url":"https://assets-eu.researchsquare.com/files/rs-7736852/v1/80e20b6f9b40a33086c69600.docx"},{"id":95806195,"identity":"8448a348-2d06-4257-9b56-8c3b66de41d2","added_by":"auto","created_at":"2025-11-13 08:47:19","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":18481896,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAdditional file 2.\u003c/strong\u003e(.docx)\u003cstrong\u003e \u003c/strong\u003eThe original Figure 2 without annotations.\u003c/p\u003e\n\u003cp\u003eThe map information in this figure is based on Google Maps, and its use complies with the License Agreements (https://cloud.google.com/maps-platform/terms/).\u003c/p\u003e","description":"","filename":"Additionalfile2.docx","url":"https://assets-eu.researchsquare.com/files/rs-7736852/v1/745cb372f0f4e0982f351d47.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Geospatial Analysis of Out-of-Hospital Cardiac Arrest Incidence","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-public-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pubh","sideBox":"Learn more about [BMC Public Health](http://bmcpublichealth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pubh/default.aspx","title":"BMC Public Health","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Gaussian process, Integrated nested Laplace approximation, Out-of-hospital cardiac arrest, Spatial modelling, Stochastic partial differential equation, Urban","lastPublishedDoi":"10.21203/rs.3.rs-7736852/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7736852/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e\u003cp\u003eIn urban areas, abundant medical resources improve outcomes for patients with out-of-hospital cardiac arrest (OHCA). However, metropolitan environments present unique pre-hospital transportation challenges rarely observed in rural areas, such as complex transportation networks and high-rise buildings. Additionally, social factors, such as economic disparities within the same city, may affect prognostic outcomes. The aim of this study was to identify urban-specific factors affecting patient outcomes by analyzing prognostic differences among patients with OHCA transported to an emergency center in the heart of a major city.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003eIn this retrospective observational study, data regarding patients transported to Tokyo Medical and Dental University Hospital between June 1, 2016 and May 30, 2022 were extracted from electronic records. Using Bayesian spatial modeling, the relationship between geographical factors and neurological outcomes was analyzed. The relationships between on-scene response time and transport time of emergency medical services were also examined.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eA correlation was observed between neurological outcomes and geographical factors, such as the distance from the OHCA scene to the emergency center. Population density, building floor level, and land prices were also associated with neurological outcomes.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e\u003cp\u003eThe findings indicate that geographical factors in metropolitan areas affect patient outcomes. Furthermore, they highlight the importance of large-scale, multicenter studies in establishing more appropriate healthcare facilities in urban regions.\u003c/p\u003e","manuscriptTitle":"Geospatial Analysis of Out-of-Hospital Cardiac Arrest Incidence","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-11-13 07:46:50","doi":"10.21203/rs.3.rs-7736852/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"","date":"2025-11-10T20:15:26+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"306900508693539434631082358603410785716","date":"2025-11-07T19:27:36+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"269645242174209581049888296253148160117","date":"2025-10-31T14:46:42+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-10-31T11:09:46+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-10-03T13:01:23+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-10-02T13:05:38+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-10-02T13:04:51+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Public Health","date":"2025-09-29T01:01:11+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-public-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pubh","sideBox":"Learn more about [BMC Public Health](http://bmcpublichealth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pubh/default.aspx","title":"BMC Public Health","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"a3d03fc3-a23d-46c8-bcda-976061ec6021","owner":[],"postedDate":"November 13th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2025-11-13T07:46:51+00:00","versionOfRecord":[],"versionCreatedAt":"2025-11-13 07:46:50","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7736852","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7736852","identity":"rs-7736852","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}