ArticleClinical oral investigations2026
Retrospective 3D analysis of gingival recession and occlusal morphology based on digital intraoral scans: an exploratory study.
Article in Clinical oral investigations, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectivesTo 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
methodsThis 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.
resultsOf 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).
conclusionsAmong 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.
Indexed as
Identifiers
42853274What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.