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Samples were collected and analyzed through ATR\u2010FTIR spectroscopy. Chemometric models were applied for cluster\/outlier identification and discrimination. Regression coefficient vectors of PLS\u2010DA models identified key spectral differences between groups.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      A total of 40 implants were analyzed; participants had a mean age of 62\u2009years, predominantly female (59%), non\u2010smokers (88%), and most received regular maintenance therapy (82%). PCA revealed subtle cluster formations without clear group separation. Comparing PICF from patients with and without PI, the most important wavenumbers for the PLS\u2010DA model were within 1700\u20131680\u2009cm\n                      <jats:sup>\u22121<\/jats:sup>\n                      , 1190\u20131130\u2009cm\n                      <jats:sup>\u22121<\/jats:sup>\n                      , and 1050\u2013980\u2009cm\n                      <jats:sup>\u22121<\/jats:sup>\n                      , associated with protein\u2010related signals and nucleic\u2010acid content. Comparing the GCF and PICF from PI patients, using a split\u2010mouth design, the most important wavenumbers were 3006\u2009cm\n                      <jats:sup>\u22121<\/jats:sup>\n                      , 2982\u2009cm\n                      <jats:sup>\u22121<\/jats:sup>\n                      , and 2900\u2009cm\n                      <jats:sup>\u22121<\/jats:sup>\n                      , related to lipid structures. In terms of accuracy, between\u2010participant assessment achieved 75%, whereas the split\u2010mouth assessment reached 83.4%.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>FTIR\u2010spectroscopy combined with chemometric modeling effectively discriminates peri\u2010implant health and PI in both inter\u2010 and intra\u2010subject comparisons. Higher within\u2010subject accuracy supports FTIR's potential as a site\u2010specific, non\u2010invasive diagnostic tool for peri\u2010implantitis.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1111\/clr.70091","type":"journal-article","created":{"date-parts":[[2026,1,23]],"date-time":"2026-01-23T04:00:20Z","timestamp":1769140820000},"page":"453-467","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Peri\u2010Implant Crevicular Fluid Analysis by Mid\u2010Infrared Spectroscopy in Peri\u2010Implantitis\u2014A Pilot Study"],"prefix":"10.1111","volume":"37","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1270-9597","authenticated-orcid":false,"given":"Francisco","family":"Maligno","sequence":"first","affiliation":[{"name":"Faculdade de Medicina Dent\u00e1ria Universidade do Porto  Porto Portugal"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ricardo N. M. 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