ArticlePeerJ2025
Three-dimensional analysis of facial morphology in nine-year-old children with different unilateral orofacial clefts compared to normative data.
Article in PeerJ, 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
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
2 citing papers in PubMed.
- A longitudinal three-dimensional analysis of nasolabial morphology following primary cheiloplasty of unilateral cleft lip deformity.Frontiers in dental medicine · 2026Article
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Aim: To compare three-dimensional (3D) facial morphology of various unilateral cleft subphenotypes at 9-years of age to normative data using a general face template and automatic landmarking. The secondary objective is to compare facial morphology of 9-year-old children with unilateral fusion to differentiation defects. Methods: 3D facial stereophotogrammetric images of 9-year-old unilateral cleft patients were imported into 3DMedX® for processing. All images of patients with a right sided cleft were mirrored. A regionalized general facial template was used for standardization. This template was pre-aligned to each face using five automatically determined landmarks and fitted using MeshMonk. All cleft patients were compared to an age-and gender matched normative face using distance maps and inter-surface distances (mm). Average faces were created for five groups (unilateral cleft lip, alveolus, and/or palate (UCL/A/P), fusion and differentiation defects). The selected regions for the evaluation of facial morphology were: complete face, nose, upper lip, lower lip, chin, forehead, and cheeks. Results: A total of 86 consecutive 3D-stereophotogrammetry images were acquired for examination. No statistically significant differences were observed among the UCL, UCLA, and UCLP groups for the complete face, cheeks, chin, forehead, lower lip, and nose. However, in the upper lip region a significant difference was observed between the UCLP and UCL groups ( Conclusion: The findings demonstrate statistically significant differences in the upper lip region between children with UCL and those with UCLP, particularly with greater upper lip retrusion in the UCLP group. The use of color-coded distance maps revealed local variations and a trend of asymmetry in the nasal region, with increasing retrusion of the nose tip, upper lip, and cheeks correlating with the severity of the cleft. Although these trends were not statistically significant, they suggest a progressive facial retrusion pattern as cleft severity increases. For the secondary objective, no statistical differences were found between the facial morphology of children with fusion and differentiation defects, although a similar progression of maxillary retrusion was observed in the distance maps.
Indexed as
Identifiers
What 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.