Retrospective 3D analysis of gingival recession and occlusal morphology based on digital intraoral scans: an exploratory study

OBJECTIVES: To characterize gingival recession (GR) in archived intraoral scans and to investigate associations with scan-visible occlusal and morphological features at patient and tooth levels. MATERIALS AND METHODS: This retrospective exploratory study included digital scans from adult patients without documented previous orthodontic treatment or relevant periodontal destruction. Mid-buccal GR was recorded as an ordinal score and as continuous depth. Wear-facet severity, a derived wear-facet involvement score, tooth type, alignment, and crown angulation were assessed. Patient-level associations were examined using logistic regression. Among recession-affected teeth, associations with recession severity were evaluated using cumulative link and gamma generalized linear mixed models accounting for clustering within patients. Exploratory random-forest modelling assessed predictive discrimination. RESULTS: Of 85 identified patients, 63 were included in patient-level analyses and 446 teeth in tooth-level analyses. GR was present in 74.6% of patients. Increasing age was associated with GR (odds ratio, 1.098; p < 0.01), whereas sex, smoking, and Angle Class were not. At tooth level, greater wear-facet involvement was associated with both higher recession scores and greater recession depth (both p < 0.0001), and age was also associated with both recession outcomes. The exploratory ML-based risk model showed moderate discrimination (AUC, 0.734 ± 0.061). CONCLUSIONS: Among recession-affected teeth, greater regional wear-facet involvement was associated with greater GR severity. CLINICAL RELEVANCE: The spatial distribution of wear facets may provide additional contextual information when assessing teeth with gingival recession, as greater regional involvement was associated with greater recession severity.