Evidence map›Paper›PMID 23624552›Full record

ArticleInternational journal of legal medicine2014

Age determination of adult individuals by three-dimensional modelling of canines.

Delphine Tardivo, Julien Sastre, Jean-Hugues Catherine, Georges Leonetti, Pascal Adalian, Bruno Foti

Abstract read
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In one paragraph

Article in International journal of legal medicine, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed, 1 pooled it
–field-weighted citation impact
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

14 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. CT and MR imaging used in age estimation: a systematic review.The Journal of forensic odonto-stomatology · 2018
    Pooled it
  2. Article
  3. Age Estimation Using Maxillary Central Incisor Analysis on Cone Beam Computed Tomography Human Images.International journal of environmental research and public health · 2022
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  14. Age estimation from canine volumes.La Radiologia medica · 2015
    Article
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

6 authors.

Delphine TardivoUnité Mixte de Recherche 7268/CNRS-EFS-Aix Marseille Université, 51 Boulevard Pierre Dramard, 13916, Marseille Cedex 20, France, delphine.tardivo@gmail.com.
Julien Sastre
Jean-Hugues Catherine
Georges Leonetti
Pascal Adalian
Bruno Foti

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Accurate age determination is fundamental in both forensic medicine and anthropology. Many methods that relate dental characteristics to adult age have been proposed, but there is still no simple and reliable method that does not damage the study material. The aim of this work was to propose a relevant and practical technique for determining age in adults that could be used in both living and deceased individuals. The sample was composed of 210 CT scans from individuals aged from 15 to 85 years old, with four healthy canines present in the mouth. The 840 canines were modelled using Mimics® 10.01 software. The pulp volume/total volume ratio ×100 was determined for each tooth. Seven mathematical models, corresponding to all possible real situations, were determined by the weighted least squares method and ranked in order of relative performance. The adequacy of the seven models to the data was very high with the regressions proposed (0.915 < R (2) adjusted < 0.964). Ranked in order of performance, the maxillary model was the most powerful of the seven models for age determination, followed by the 4 canines model, the 13 model and the 23 model.

Indexed as

Models, DentalAdolescentAdultAgedAged, 80 and overAge Determination by TeethChildCuspidDental PulpFemaleHumansImaging, Three-DimensionalMaleMiddle AgedRadiography, DentalRegression Analysis

Identifiers

What OpenQuestion holds

Textmetadata
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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.