Evidence map›Paper›PMID 32271782›Full record

ArticlePloS one2020

Morphometric approach to 3D soft-tissue craniofacial analysis and classification of ethnicity, sex, and age.

Olalekan Agbolade, Azree Nazri, Razali Yaakob, Abdul Azim Ghani, Yoke Kqueen Cheah

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
5.5field-weighted citation impact, top 4% of its field
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

13 citing papers in PubMed, 30 citations in OpenAlex.

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  8. Characterization of craniofacial-based clinical phenotypes in children with suspected obstructive sleep apnea.Journal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine · 2023
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors at 1 institution in 1 country.

Olalekan AgboladeDepartment of Computer Science, Faculty of Computer Science & IT, Universiti Putra Malaysia, Seri Kembangan, Selangor, Malaysia.ORCID 0000-0002-0985-8025
Azree NazriDepartment of Computer Science, Faculty of Computer Science & IT, Universiti Putra Malaysia, Seri Kembangan, Selangor, Malaysia.ORCID 0000-0001-6362-5006
Razali YaakobDepartment of Computer Science, Faculty of Computer Science & IT, Universiti Putra Malaysia, Seri Kembangan, Selangor, Malaysia.
Abdul Azim GhaniDepartment of Software Engineering, Faculty of Computer Science & IT, Universiti Putra Malaysia, Seri Kembangan, Selangor, Malaysia.
Yoke Kqueen CheahDepartment of Biomedical Science, Faculty of Medicine and Health Sciences, Universiti Putra Malaysia, Seri Kembangan, Selangor, Malaysia.
Universiti Putra Malaysia · MY

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe application of three-dimensional scan models offers a useful resource for studying craniofacial variation. The complex mathematical analysis for facial point acquisition in three-dimensional models has made many craniofacial assessments laborious.

methodThis study investigates three-dimensional (3D) soft-tissue craniofacial variation, with relation to ethnicity, sex and age variables in British and Irish white Europeans. This utilizes a geometric morphometric approach on a subsampled dataset comprising 292 scans, taken from a Liverpool-York Head Model database. Shape variation and analysis of each variable are tested using 20 anchor anatomical landmarks and 480 sliding semi-landmarks.

resultsSignificant ethnicity, sex, and age differences are observed for measurement covering major aspects of the craniofacial shape. The ethnicity shows subtle significant differences compared to sex and age; even though it presents the lowest classification accuracy. The magnitude of dimorphism in sex is revealed in the facial, nasal and crania measurement. Significant shape differences are also seen at each age group, with some distinct dimorphic features present in the age groups.

conclusionsThe patterns of shape variation show that white British individuals have a more rounded head shape, whereas white Irish individuals have a narrower head shape. White British persons also demonstrate higher classification accuracy. Regarding sex patterns, males are relatively larger than females, especially in the mouth and nasal regions. Females presented with higher classification accuracy than males. The differences in the chin, mouth, nose, crania, and forehead emerge from different growth rates between the groups. Classification accuracy is best for children and senior adult age groups.

Indexed as

CephalometryImaging, Three-DimensionalSex CharacteristicsAdolescentAdultAge FactorsAnalysis of VarianceAnatomic LandmarksDiscriminant AnalysisFaceFemaleHumansMiddle AgedPrincipal Component AnalysisSkullYoung Adult

Identifiers

PMID32271782
PMCPMC7145022
OpenAlexW3015693619

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.