Evidence map›Paper›PMID 28617981›Full record

ArticleJournal of anatomy2017

What is the variability in shoulder, axillae and waist position in a group of adolescents?

Adrian Gardner, Fiona Berryman, Paul Pynsent

Abstract read
In one paragraph

Article in Journal of anatomy, 2017. 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. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. 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

3 authors.

Adrian GardnerThe Royal Orthopaedic Hospital NHS Foundation Trust, Birmingham, UK.ORCID http://orcid.org/0000-0001-6532-7950
Fiona BerrymanThe Royal Orthopaedic Hospital NHS Foundation Trust, Birmingham, UK.
Paul PynsentDepartment of Anatomy, Institute of Clinical Science, University of Birmingham, Birmingham, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The clinical assessment of scoliosis is based on the recognition of asymmetry. It is not clear what the degree of asymmetry is in a population without scoliosis, which could make the differentiation between abnormal and normal uncertain. This study defines the range of normality in certain parameters of torso shape that are also associated with the clinical assessment of scoliosis. This was done by analysing the surface topography of a group of 195 children serially measured over a 5-year period. The analysis considered both the spinal curvature and the relative position of shoulders, axillae and waist on each side. The bivariate relationships were examined using 95% confidence interval data ellipses. Our results showed that a degree of spinal curvature was seen, either as a main thoracic or main thoracolumbar curve. The distribution of the data about a mean point is illustrated by 95% confidence interval (CI) data ellipses with shoulder, axilla and waist data plotted against spinal curvature. The mean values were close to zero (exact symmetry) for all of the measured parameters, with the ellipses showing little differences in the distributions. We conclude that mild asymmetry of the measured torso parameters is normal. These results define what is normal and beyond what point asymmetry becomes abnormal. This information is of use for those managing and counselling patients with scoliosis both before and after surgery.

Indexed as

Spinal CurvaturesAdolescentAxillaChildFemaleFourier AnalysisHumansMaleReference ValuesShoulderaxillaenormalscoliosisshoulderssurface topographywaist

Identifiers

PMID28617981
PMCPMC5522889

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.