ArticleJournal of periodontal research2025
Accuracy of Metabolomics in Peri-Implant Crevicular Fluid for Diagnosis and Prognosis of Peri-Implantitis.
Article in Journal of periodontal research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
2 citing papers in PubMed.
- Untargeted Metabolomic and Lipidomic Profiles of Gingival Crevicular Fluid in the Context of Periodontitis.Journal of clinical periodontology · 2026Article
- Impact of OMICS Technologies in Our Understanding of the Pathogenesis of Peri-Implantitis.Clinical and experimental dental research · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
Abstract
aimsPoor accuracy of diagnostic and prognostic tools prevents the prediction of peri-implant disease stability or progression. We analyzed metabolites from peri-implant crevicular fluid (PICF) samples from healthy and diseased implants to identify those diagnostic of health and peri-implant disease and predictive of peri-implant bone loss over time.
methodsClinical, radiographic examinations and PICF samples were collected from 59 healthy implants, 33 implants with peri-implantitis, and 38 implants with peri-implant mucositis in 71 subjects. A subset of implants was evaluated at 6, 12, 18, and 24 months. Over time, all initially healthy implants remained stable (Group B, N = 28), whereas 6 initially diseased implants continued to lose bone and 8 did not (Group C). PICF metabolites were measured using proton-nuclear magnetic resonance (1H-NMR) 2-dimensional Total Correlation Spectroscopy. PCA and PLS-DA tested the cross-sectional clustering and importance of each metabolite, while the AUC summarized the accuracy of predicting radiographic bone changes ≥ 1 mm at 6-month intervals.
resultsAt baseline, the Cadaverine/Lysine and Putrescine/Lysine signatures diagnosed peri-implantitis (AUC = 0.76 and 0.70; p < 0.000) with good accuracy, while alpha-ketoglutarate diagnosed implant health (AUC = 0.706; p = 0.002). Combining metabolites increased diagnostic accuracy (AUC
conclusions
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Registered trials
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