{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,6]],"date-time":"2026-10-06T17:55:13Z","timestamp":1791309313886,"version":"4.3.1"},"reference-count":126,"publisher":"Wiley","issue":"S29","license":[{"start":{"date-parts":[[2025,6,25]],"date-time":"2025-06-25T00:00:00Z","timestamp":1750809600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["J Clinic Periodontology"],"published-print":{"date-parts":[[2025,8]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Aim<\/jats:title>\n                    <jats:p>To evaluate different tools to screen for periodontal diseases and\/or evaluate the risk for disease progression in non\u2010dental clinical settings.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Materials and Methods<\/jats:title>\n                    <jats:p>The PRISMA Extension for Scoping Reviews (PRISMA\u2010ScR) guideline was followed. A systematic search was conducted on three databases. In order to provide a comprehensive picture of periodontal diseases (Population) screening and risk assessment tools (Concept) in non\u2010dental settings (Context), the available information was identified and presented in terms of the sources of data\/domains assessed and, eventually, how the tools\/algorithms were validated. The risk of bias was assessed using the QUADAS\u20102 tool.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>A total of 5313 articles were identified for abstract screening. Finally, 102 were included for data synthesis. The included studies were classified into domains\/clusters. Only two studies focused on risk assessment for disease progression. Algorithms designed to screen for gingivitis tended to present low sensitivity values, while the screening performance improved for periodontitis, particularly for severe periodontitis. Validated self\u2010reported questionnaires plus socio\u2010demographic determinants (e.g., age), certain biomarkers in saliva (e.g., activated matrix metalloproteinase\u20108, aMMP\u20108) and artificial intelligence (AI) algorithms based on orthopantomographs (OPGs) present the best screening capacity for periodontitis.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>Screening for periodontitis in non\u2010dental settings is feasible. Validated self\u2010reported questionnaires remain the gold standard for screening severe periodontitis in non\u2010dental settings, although AI algorithms based on biomarkers in saliva, or derived from OPGs, have shown promising results.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1111\/jcpe.14168","type":"journal-article","created":{"date-parts":[[2025,6,25]],"date-time":"2025-06-25T05:20:16Z","timestamp":1750828816000},"page":"246-291","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["Emerging Technologies and Algorithms for Periodontal Screening and Risk of Disease Progression in Non\u2010Dental Settings: A Scoping Review"],"prefix":"10.1111","volume":"52","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2525-8529","authenticated-orcid":false,"given":"Eduardo","family":"Montero","sequence":"first","affiliation":[{"name":"Section of Graduate Periodontology University Complutense of Madrid  Madrid 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