From Model Performance to Screening Readiness: An Audit-Grade Evidence Mapping Study in Prediabetes

From Model Performance to Screening Readiness: An Audit-Grade Evidence Mapping Study in Prediabetes | 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 From Model Performance to Screening Readiness: An Audit-Grade Evidence Mapping Study in Prediabetes Mohammad Alshantti This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8568701/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: Prediabetes represents an intermediate metabolic state preceding type 2 diabetes, where delayed identification can postpone effective, low-cost preventive measures. Methods: We propose a taxonomy-first, audit-grade evidence mapping framework and score each model unit across validation maturity (V), reporting completeness (R), calibration/threshold readiness (C/T), and reproducibility (Re), using conservative coding and dual independent extraction. Results: In a pilot Run V0, we observed recurring gaps in calibration, threshold definition, and modality descriptions that limit decision readiness despite reported discrimination metrics. Conclusions: The framework and reproducible workflow provide a transparent method to quantify reporting and decision-readiness gaps and are designed to scale to a larger Run V1 under a frozen codebook. Prediabetes Medical informatics Evidence mapping Screening readiness Machine learning PRISMA 2020 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-8568701","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":584750882,"identity":"c6772250-7835-4fb8-b62f-493c3a40c48b","order_by":0,"name":"Mohammad 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