Comparative analysis of gingival crevicular fluid and peri-implant crevicular fluid by mid-infrared spectroscopy: a split mouth study.

OBJECTIVES: This proof-of-concept study aimed to compare the biochemical composition of gingival crevicular fluid (GCF) and peri-implant crevicular fluid (PICF) under healthy conditions, through mid-infrared (MIR) spectroscopy. MATERIALS AND METHODS: Using a split-mouth design, GCF and PICF samples were collected from 12 participants and analyzed through MIR spectroscopy. Advanced chemometric models, including partial least squares-discriminant analysis, k-nearest neighbors, and support vector machine discriminant analysis, were applied to explore potential biochemical differences between the biofluids. RESULTS: No cluster formation was observed with PCA, indicating a high degree of similarity between groups. The PLS-DA model didn't effectively discriminate between GCF and PICF with prediction rates of 62.5% (10/16) for calibration, 37.5% (6/16) for cross-validation, and 50% (4/8) for validation. The k-NN model, using k = 3 neighbors showed 25% (4/16) correct classification rates during calibration and a validation set accuracy of 50%. SVM-DA analysis showed a correct prediction rate of 37.5% (6/16) for calibration and 50% for cross-validation 50% (8/16) and 50% (4/8) in the validation phase. Nonetheless, subtle spectral differences were observed in spectral regions R1 (3982-2652 cm(-)(1)) and R4 (1180-922 cm(-)(1)), suggesting a slightly increased lipidic content and the presence of ethers and glycosidic bonds linked to carbohydrates, in PICF. CONCLUSIONS: The lack of significant biochemical differences between GCF and PICF under healthy conditions, as determined by MIR spectroscopy, suggests that implant-related changes in PICF composition are negligible. CLINICAL RELEVANCE: The demonstrated biochemical similarity between GCF and PICF under healthy conditions reinforces the potential of PICF as a reliable biofluid for diagnostic applications, including monitoring oral and systemic health biomarkers, without significant influence from implant-related factors.