Evidence mapPaperPMID 42374333Full record

ArticleBMC musculoskeletal disorders2026

Association of trabecular texture and paraspinal muscle characteristics with prevalent vertebral fractures - QCT results from a subcohort of the AGES population.

Tobias Stumpf, Oliver Chaudry, Jana Hummel, Sandra Freitag-Wolf, Eren Yilmaz, Stefan Bartenschlager, Sigurdur Sigurdsson, Vilmundur Gudnason, Nicolai R Krekiehn, Claus C Glüer and 1 more

Abstract read
In one paragraph

Article in BMC musculoskeletal disorders, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

11 authors.

Tobias StumpfInstitute of Radiology, Friedrich-Alexander-University Erlangen-Nürnberg and Universitätsklinikum Erlangen, Erlangen, Germany.
Oliver ChaudryInstitute of Radiology, Friedrich-Alexander-University Erlangen-Nürnberg and Universitätsklinikum Erlangen, Erlangen, Germany.
Jana HummelInstitute of Radiology, Friedrich-Alexander-University Erlangen-Nürnberg and Universitätsklinikum Erlangen, Erlangen, Germany.
Sandra Freitag-WolfInstitute of Medical Informatics and Statistics, Kiel University and University Hospital Schleswig-Holstein, Kiel, Germany.
Eren YilmazSection Biomedical Imaging, Department of Radiology and Neuroradiology, Kiel University and University Hospital Schleswig-Holstein, Kiel, Germany.
Stefan BartenschlagerDepartment of Medicine 3, Friedrich-Alexander-University Erlangen-Nürnberg and Universitätsklinikum Erlangen, Erlangen, Germany.
Sigurdur SigurdssonIcelandic Heart Association Research Institute, Kopavogur, Iceland.
Vilmundur GudnasonIcelandic Heart Association Research Institute, Kopavogur, Iceland.
Nicolai R KrekiehnSection Biomedical Imaging, Department of Radiology and Neuroradiology, Kiel University and University Hospital Schleswig-Holstein, Kiel, Germany.
Claus C GlüerSection Biomedical Imaging, Department of Radiology and Neuroradiology, Kiel University and University Hospital Schleswig-Holstein, Kiel, Germany.
Klaus EngelkeDepartment of Medicine 3, Friedrich-Alexander-University Erlangen-Nürnberg and Universitätsklinikum Erlangen, Erlangen, Germany. klaus.engelke@fau.de.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPrediction of osteoporotic fractures remains suboptimal, leaving many high-risk individuals untreated while others fracture without prior diagnosis. Muscle characteristics are not part of prediction algorithms although studies showed that paraspinal muscle size, density, and fat infiltration are associated with vertebral fractures (VF). However, an analysis of the prospective AGES-Reykjavik study did not show improved prediction of the first incident VF when combining muscle parameters with BMD.

objectiveTo determine whether paraspinal muscle characteristics are associated with prevalent fractures using the prospective AGES-Reykjavik study.

methodsIn the current study associations of muscle parameters with prevalent VF were analyzed in the same cohort of 486 women and 340 men with 96 and 78 prevalent VF, respectively. 50 parameters from CT scans of the L1 and L2 vertebrae, divided into a BMD, a trabecular texture and a muscle subset were used as discriminators. Each subset also included age and BMI. The number of parameters was reduced using stepwise logistic regression to create multivariable fracture discrimination models. Model accuracy was assessed using the likelihood ratio test (LRT) and the area under the curve (AUC). Bootstrap analyses were performed to assess stability of the model selection process.

results23 parameters significantly discriminated prevalent VFs univariately in women and 5 in men. In women multivariable bone and muscle models showed significantly better fracture discrimination (p < 0.01) than the combination of age and BMI. Compared to the BMD model, LRT showed a significantly improved VF discrimination of the combinations of BMD with texture or with muscle models (p < 0.001). In men the BMD model (AUC 0.64) did not significantly improve VF discrimination compared to age and BMI.

conclusionsIn older women, but not men, paraspinal muscle characteristics significantly enhance the discrimination of prevalent VFs beyond BMD alone. Muscle parameters were not predictive of incident VFs in prior analyses of the same cohort, suggesting that muscle deterioration may occur concurrently or follow vertebral fracture.

Indexed as

Cancellous BoneOsteoporotic FracturesParaspinal MusclesSpinal FracturesTomography, X-Ray ComputedAgedAged, 80 and overBone DensityFemaleHumansIcelandLumbar VertebraeMalePrevalenceProspective StudiesComputed tomography; BMDFracture predictionIncident and prevalent vertebral fractureParaspinal muscleTrabecular texture

Identifiers

PMID42374333
PMCPMC13321617

What Socratic holds

Textmetadata
LicenceCC BY
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 Socratic graph.