Evidence map›Paper›PMID 25095743›Full record

ReviewCurrent osteoporosis reports2014

Imaging of the muscle-bone relationship.

Alex Ireland, José Luis Ferretti, Jörn Rittweger

Abstract readReview
PubMed Publisher
In one paragraph

Review in Current osteoporosis reports, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
0.8field-weighted citation impact, top 29% 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

6 citing papers in PubMed, 12 citations in OpenAlex.

  1. Trial
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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 at 3 institutions in 3 countries.

Alex IrelandCognitive Motor Function Research Group, Manchester Metropolitan University, Manchester, England.
José Luis Ferretti
Jörn Rittweger
Linde (Germany) · DEManchester Metropolitan University · GBNational University of Rosario · AR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Muscle can be assessed by imaging techniques according to its size (as thickness, area, volume, or alternatively, as a mass) and architecture (fiber length and pennation angle), with values used as an anthropometric measure or a surrogate for force production. Similarly, the size of the bone (as area or volume) can be imaged using MRI or pQCT, although typically bone mineral mass is reported. Bone imaging measures of mineral density, size, and geometry can also be combined to calculate bone's structural strength-measures being highly predictive of bone's failure load ex vivo. Imaging of muscle-bone relationships can, hence, be accomplished through a number of approaches by adoption and comparison of these different muscle and bone parameters, dependent on the research question under investigation. These approaches have revealed evidence of direct, mechanical muscle-bone interactions independent of allometric associations. They have led to important information on bone mechanoadaptation and the influence of muscular action on bone, in addition to influences of age, gender, exercise, and disuse on muscle-bone relationships. Such analyses have also produced promising diagnostic tools for clinical use, such as identification of primary, disuse-induced, and secondary osteoporosis and estimation of bone safety factors. Standardization of muscle-bone imaging methods is required to permit more reliable comparisons between studies and differing imaging modes, and in particular to aid adoption of these methods into widespread clinical practice.

Indexed as

Absorptiometry, PhotonBiomechanical PhenomenaBone and BonesBone DensityFemaleHumansMaleMuscle, SkeletalStress, PhysiologicalTomography, X-Ray Computed

Identifiers

PMID25095743
OpenAlexW1988890838

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.