Evaluation of a Rapid Immunoassay for Molecular Subphenotype Classification in Pediatric Acute Cardiorespiratory Failure

Evaluation of a Rapid Immunoassay for Molecular Subphenotype Classification in Pediatric Acute Cardiorespiratory Failure | 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 Short Report Evaluation of a Rapid Immunoassay for Molecular Subphenotype Classification in Pediatric Acute Cardiorespiratory Failure Colin J. Sallee, Clove S. Taylor, Matt S. Zinter, Daniela Markovic, and 7 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7596498/v2 This work is licensed under a CC BY 4.0 License Status: Posted Version 2 posted You are reading this latest preprint version Show more versions Abstract Objectives: Molecular subphenotypes, identified through latent class analysis (LCA) of biomarker profiles, have the potential to guide targeted therapeutics in critical care. We have previously published that intensive insulin management has subphenotype-specific beneficial effects among children with hyperglycemia accompanying cardiorespiratory failure. However, the real-time application of subphenotype-based strategies in clinical settings remains challenging due to the operational aspects of biomarker assays. Our study had three objectives: (1) compare biomarker measurements from rapid immunoassay and conventional multiplex platforms; (2) evaluate the cross-platform transportability of a conventional assay-based parsimonious classifier for LCA-derived subphenotypes and compare it to a classifier trained directly on rapid immunoassay data; and (3) assess the prognostic and predictive significance of rapid immunoassay-based subphenotypes. Design: Retrospective cohort study. Setting: Multicenter PICUs. Patients: 269 critically ill children with acute cardiorespiratory failure and hyperglycemia (2012-2016). Interventions: None. Measurements and Main Results: LCA was previously used to derive hyper-inflammatory and hypo-inflammatory classes using a conventional multiplex assay of 13 plasma biomarkers. A parsimonious classifier was fitted to LCA-derived subphenotypes and produced a model consisting of IL-6, IL-8, and sTNFR-1. We applied this classifier to rapid immunoassay biomarker measurements, yielding an AUROC of 0.90 (95% CI 0.85-0.95), though calibration was poor due to systematic underestimation of sTNFR-1 concentrations by the rapid platform. We then derived and internally validated via bootstrapping a de novo classifier using rapid immunoassay data, achieving an AUROC 0.90 (95% CI 0.86-0.95) and excellent calibration. The de novo classifier matched with LCA-derived classifications in 241 out of 269 cases (accuracy 89.6%). Rapid immunoassay-based subphenotypes demonstrated differences in morality (33.3% in hyper-inflammatory vs. 11.8% in hypo-inflammatory; P=0.009) and differential response to intensive insulin management (interaction P=0.024). Conclusions: Rapid biomarker testing paired with a parsimonious classifier has the potential to guide prospective identification of molecular subphenotypes and inform future clinical trial design. Molecular Subphenotyping Precision Medicine Rapid Immunoassay Biological Heterogeneity Clinical Trials Figures Figure 1 Figure 2 Full Text Additional Declarations The authors declare no competing interests. Supplementary Files EllaCCMSupplement1216.docx Supplement Cite Share Download PDF Status: Posted Version 2 posted You are reading this latest preprint version Show more versions 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-7596498","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Short Report","associatedPublications":[],"authors":[{"id":519217296,"identity":"9bce6a2c-95af-4d41-9f9c-00a98e3899af","order_by":0,"name":"Colin J. Sallee","email":"","orcid":"","institution":"University of California Los Angeles","correspondingAuthor":false,"prefix":"","firstName":"Colin","middleName":"J.","lastName":"Sallee","suffix":""},{"id":519217297,"identity":"296b7369-10f0-4f21-a2e8-2fe662dd8dfa","order_by":1,"name":"Clove S. Taylor","email":"","orcid":"","institution":"University of California Los Angeles","correspondingAuthor":false,"prefix":"","firstName":"Clove","middleName":"S.","lastName":"Taylor","suffix":""},{"id":519217298,"identity":"ce86e3f9-1f61-4603-81cb-8cccbd5dbbf6","order_by":2,"name":"Matt S. Zinter","email":"","orcid":"","institution":"University of California San Francisco","correspondingAuthor":false,"prefix":"","firstName":"Matt","middleName":"S.","lastName":"Zinter","suffix":""},{"id":519217299,"identity":"c332109e-06db-4506-84fa-a6c3293abcfd","order_by":3,"name":"Daniela Markovic","email":"","orcid":"","institution":"University of California Los Angeles","correspondingAuthor":false,"prefix":"","firstName":"Daniela","middleName":"","lastName":"Markovic","suffix":""},{"id":519217300,"identity":"834994e2-d038-4a55-aaed-507b5a6bb69d","order_by":4,"name":"Michelle J. 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A. \u003c/strong\u003eScatterplots of IL6 (orange), IL8 (green), and sTNFR-1 (purple) measured by Ella (x-axis) and Luminex (y-axis). Biomarker concentrations are in pg/mL. Deming regression lines are in blue with 95% bootstrapped confidence intervals (CIs). Dashed lines correspond to the identity line (x=y) for each biomarker.\u003cstrong\u003e \u003c/strong\u003eIL-6 was significantly correlated between platforms (ρ=0.93, P\u0026lt;0.0001) and no significant proportional bias was detected (slope 1.19, 95% 0.91, 1.48). IL-8 was significantly correlated between platforms (ρ=0.85, P\u0026lt;0.0001) without strong evidence of proportional bias (slope 1.38, 95% CI 0.65, 2.10). While sTNFR-1 values were significantly correlated between platforms (ρ=0.91, P\u0026lt;0.0001), there was significant proportional bias with Ella underestimating Luminex values (slope 11.98, 95% CI 6.79, 17.18). \u003cstrong\u003eB. \u003c/strong\u003eAgreement between the Ella and Luminex platforms assessed via Bland-Altman plots. For each biomarker, the difference between platforms (y-axis) is plotted against the platform average (x-axis). The solid line represents the mean bias, while the dashed lines indicate the 95% limits of agreement. IL6 = interleukin-6, IL8 = interleukin-8, sTNFR1 = soluble tumor necrosis factor 1.\u003c/p\u003e","description":"","filename":"Figure1CCM.png","url":"https://assets-eu.researchsquare.com/files/rs-7596498/v2/37ead80c3a296e018d88b8e0.png"},{"id":108048335,"identity":"67e8befc-0b4a-4e88-8af9-4fb65bd0ec7b","added_by":"auto","created_at":"2026-04-28 20:26:11","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":308892,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ePredictive Performance of the Rapid Immunoassay (Ella) Parsimonious Classifier. A. \u003c/strong\u003eArea under the receiver operating curves (AUROC) for discriminating latent class analysis (LCA)-derived molecular subphenotypes applying the \u003cem\u003ede novo\u003c/em\u003e rapid immunoassay-derived three-variable (IL-6, IL-8, sTNFR-1) classifier. \u003cstrong\u003eB. \u003c/strong\u003eCalibration plot illustrating observed event rate (for hyper-inflammatory class assignment; y-axis) versus predicted probabilities (x-axis). Dashed line corresponds to the identity line (y-intercept = 0; slope = 1). \u003cstrong\u003eC. \u003c/strong\u003ePrecision-recall curve (PR-AUC) plotting precision (positive predictive value, y-axis) against recall (sensitivity, x-axis) against LCA-derived hyperinflammatory class prevalence of 0.15. IL6 = interleukin-6, IL8 = interleukin-8, sTNFR1 = soluble tumor necrosis factor 1.\u003c/p\u003e","description":"","filename":"Figure2CCM.png","url":"https://assets-eu.researchsquare.com/files/rs-7596498/v2/ec2611f29bf4cc2541eb670a.png"},{"id":108803759,"identity":"a19481bc-f70b-420e-ad5e-99d104c183e1","added_by":"auto","created_at":"2026-05-08 15:05:57","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":996292,"visible":true,"origin":"","legend":"","description":"","filename":"EllaCCM1216Final.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7596498/v2_covered_33453e38-585b-441d-aa7b-98d185e39efa.pdf"},{"id":108181681,"identity":"0cc2bb3b-d02e-46ac-873a-a0f6489193b9","added_by":"auto","created_at":"2026-04-30 08:58:50","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":49651,"visible":true,"origin":"","legend":"\u003cp\u003eSupplement\u003c/p\u003e","description":"","filename":"EllaCCMSupplement1216.docx","url":"https://assets-eu.researchsquare.com/files/rs-7596498/v2/d40bf0aa9fa6add5081ee378.docx"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"Evaluation of a Rapid Immunoassay for Molecular Subphenotype Classification in Pediatric Acute Cardiorespiratory Failure","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"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":"Molecular Subphenotyping, Precision Medicine, Rapid Immunoassay, Biological Heterogeneity, Clinical Trials","lastPublishedDoi":"10.21203/rs.3.rs-7596498/v2","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7596498/v2","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eObjectives:\u003c/strong\u003e Molecular subphenotypes, identified through latent class analysis (LCA) of biomarker profiles, have the potential to guide targeted therapeutics in critical care. We have previously published that intensive insulin management has subphenotype-specific beneficial effects among children with hyperglycemia accompanying cardiorespiratory failure. However, the real-time application of subphenotype-based strategies in clinical settings remains challenging due to the operational aspects of biomarker assays. Our study had three objectives: (1) compare biomarker measurements from rapid immunoassay and conventional multiplex platforms; (2) evaluate the cross-platform transportability of a conventional assay-based parsimonious classifier for LCA-derived subphenotypes and compare it to a classifier trained directly on rapid immunoassay data; and (3) assess the prognostic and predictive significance of rapid immunoassay-based subphenotypes.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDesign: \u003c/strong\u003eRetrospective cohort study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSetting: \u003c/strong\u003eMulticenter PICUs.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePatients: \u003c/strong\u003e269 critically ill children with acute cardiorespiratory failure and hyperglycemia (2012-2016).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInterventions: \u003c/strong\u003eNone.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMeasurements and Main Results:\u003c/strong\u003eLCA was previously used to derive hyper-inflammatory and hypo-inflammatory classes using a conventional multiplex assay of 13 plasma biomarkers. A parsimonious classifier was fitted to LCA-derived subphenotypes and produced a model consisting of IL-6, IL-8, and sTNFR-1. We applied this classifier to rapid immunoassay biomarker measurements, yielding an AUROC of 0.90 (95% CI 0.85-0.95), though calibration was poor due to systematic underestimation of sTNFR-1 concentrations by the rapid platform. We then derived and internally validated via bootstrapping a \u003cem\u003ede novo\u003c/em\u003e classifier using rapid immunoassay data, achieving an AUROC 0.90 (95% CI 0.86-0.95) and excellent calibration. The \u003cem\u003ede novo\u003c/em\u003e classifier matched with LCA-derived classifications in 241 out of 269 cases (accuracy 89.6%). Rapid immunoassay-based subphenotypes demonstrated differences in morality (33.3% in hyper-inflammatory vs. 11.8% in hypo-inflammatory; P=0.009) and differential response to intensive insulin management (interaction P=0.024).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions: \u003c/strong\u003eRapid biomarker testing paired with a parsimonious classifier has the potential to guide prospective identification of molecular subphenotypes and inform future clinical trial design.\u003c/p\u003e","manuscriptTitle":"Evaluation of a Rapid Immunoassay for Molecular Subphenotype Classification in Pediatric Acute Cardiorespiratory Failure","msid":"","msnumber":"","nonDraftVersions":[{"code":2,"date":"2026-04-28 20:26:03","doi":"10.21203/rs.3.rs-7596498/v2","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}},{"code":1,"date":"2025-09-23 07:52:56","doi":"10.21203/rs.3.rs-7596498/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":"c1363951-c56e-4589-8056-e83939f0dd0e","owner":[],"postedDate":"April 28th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-09-30T13:08:14+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-28 20:26:03","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v2","identity":"rs-7596498","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7596498","identity":"rs-7596498","version":["v2"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}