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.