Evidence map›Paper›PMID 26312096›Full record

ArticleThe open dentistry journal2015

Dental Evidence in Forensic Identification - An Overview, Methodology and Present Status.

Kewal Krishan, Tanuj Kanchan, Arun K Garg

Abstract read
In one paragraph

Article in The open dentistry journal, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 56 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
56citing papers in PubMed, 2 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

56 citing papers in PubMed, 2 syntheses or guidelines pooled it.

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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

3 authors.

Kewal KrishanDepartment of Anthropology, Panjab University, Chandigarh, India.
Tanuj KanchanDepartment of Forensic Medicine, Kasturba Medical College, Mangalore (A Constituent Institute of Manipal University), India.
Arun K GargDepartment of Orthodontics, Dr. Harvansh Singh Judge Institute of Dental Sciences and Hospital, Panjab University, Chandigarh, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Forensic odontology is primarily concerned with the use of teeth and oral structures for identification in a legal context. Various forensic odontology techniques help in the identification of the human remains in incidents such as terrorists' attacks, airplane, train and road accidents, fires, mass murders, and natural disasters such as tsunamis, earth quakes and floods, etc. (Disaster Victim Identification-DVI). Dental structures are the hardest and well protected structures in the body. These structures resist decomposition and high temperatures and are among the last ones to disintegrate after death. The principal basis of the dental identification lies in the fact that no two oral cavities are alike and the teeth are unique to an individual. The dental evidence of the deceased recovered from the scene of crime/occurrence is compared with the ante-mortem records for identification. Dental features such as tooth morphology, variations in shape and size, restorations, pathologies, missing tooth, wear patterns, crowding of the teeth, colour and position of the tooth, rotations and other peculiar dental anomalies give every individual a unique identity. In absence of ante-mortem dental records for comparison, the teeth can help in the determination of age, sex, race/ethnicity, habits, occupations, etc. which can give further clues regarding the identity of the individuals. This piece of writing gives an overview of dental evidence, its use in forensic identification and its limitations.

Indexed as

Age estimationbite marksdental anomaliesforensic odontologysex and race determination from teethwrongful convictions

Identifiers

PMID26312096
PMCPMC4541412

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Registered trials

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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.