Evidence map›Paper›PMID 25037236›Full record

ArticleForensic science, medicine, and pathology2014

A minimum data set approach to post-mortem computed tomography reporting for anthropological biological profiling.

Alison L Brough, Bruno Morgan, Claire Robinson, Sue Black, Craig Cunningham, Catherine Adams, Guy N Rutty

Abstract readEvaluation Study
PubMed Publisher
In one paragraph

Article in Forensic science, medicine, and pathology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
–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

7 citing papers in PubMed.

  1. Article
  2. Review
  3. Evaluating artificial intelligence for comparative radiography.International journal of legal medicine · 2024
    Article
  4. Article
  5. Article
  6. Article
  7. Review
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

7 authors.

Alison L BroughEast Midlands Forensic Pathology Unit, Robert Kilpatrick Building, Level 3, Leicester Royal Infirmary, Leicester, LE2 7LX, UK, alb39@le.ac.uk.
Bruno Morgan
Claire Robinson
Sue Black
Craig Cunningham
Catherine Adams
Guy N Rutty

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Anthropological examination of bones is routinely undertaken in medico-legal investigations to establish an individual's biological profile, particularly their age. This often requires the removal of soft tissue from bone (de-fleshing), which, especially when dealing with the recently deceased, is a time consuming and invasive procedure. Recent advances in multi-detector computed tomography have made it practical to rapidly acquire high-resolution morphological skeletal information from images of "fleshed" remains. The aim of this study was to develop a short standard form, created from post-mortem computed tomography images, that contains the minimum image-set required to anthropologically assess an individual. The proposed standard forms were created for 31 juvenile forensic cases with known age-at-death, spanning the full age range of the developing human. Five observers independently used this form to estimate age-at-death. All observers estimated age in all cases, and all estimations were within the accepted ranges for traditional anthropological and odontological assessment. This study supports the implementation of this approach in forensic radiological practice.

Indexed as

Multidetector Computed TomographyRadiology Information SystemsRecordsAdolescentAdultAge Determination by SkeletonAge Determination by TeethAge FactorsAutopsyBone and BonesChildChild, PreschoolFemaleForensic AnthropologyHumansInfant

Identifiers

What OpenQuestion holds

Textmetadata
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.