Evidence map›Paper›PMID 42510414›Full record

ArticleBioengineering (Basel, Switzerland)2026

A Viscoelastic Modeling for Failure Analysis of Human Vertebral Bone Undergoing Quasi-Static and Dynamic Compression.

Mahmood Allahyari, Mehran Fereydoonpour, Asghar Rezaei, Ghodrat Karami

Abstract read
In one paragraph

Article in Bioengineering (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0cells of the map it votes in
0citing papers in PubMed
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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

4 authors.

Mahmood AllahyariDepartment of Mechanical Engineering, North Dakota State University, Fargo, ND 58102, USA.
Mehran FereydoonpourDepartment of Mechanical Engineering, North Dakota State University, Fargo, ND 58102, USA.ORCID 0009-0004-0195-9843
Asghar RezaeiDepartment of Physiology and Biomedical Engineering, Mayo Clinic, Rochester, MN 55905, USA.ORCID 0000-0003-1129-7412
Ghodrat KaramiDepartment of Mechanical Engineering, North Dakota State University, Fargo, ND 58102, USA.ORCID 0000-0002-0815-0850

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Vertebral fractures are among the most common skeletal injuries and present significant clinical and biomechanical challenges, particularly in older adults and individuals with low bone density. Accurate prediction of vertebral mechanical response and failure under varying loading conditions is essential for improving understanding of spinal injury mechanisms. This study develops a density-dependent viscoelastic analytical model to predict the stiffness and fracture force of human vertebral specimens subjected to different compression rates. The vertebral body is represented as a composite structure consisting of a cortical shell and a trabecular core. Cortical bone is modeled as a linear elastic material, whereas trabecular bone is described using a Kelvin-Voigt viscoelastic formulation. Density-dependent constitutive relationships are incorporated for the elastic modulus and viscous coefficient of trabecular bone. Unknown material parameters are identified through optimization using the Nelder-Mead algorithm, based on experimental compression data from cadaveric vertebral specimens tested under quasi-static and dynamic loading conditions. The calibrated model reproduced the overall trend of specimen-to-specimen mechanical variation observed experimentally. Predicted stiffness values were in reasonable agreement with measured data. Fracture force predictions showed moderate agreement for dynamically tested specimens (R

Indexed as

bone densitystrain-rate dependencetrabecular bonevertebral biomechanicsviscoelasticity

Identifiers

PMID42510414
PMCPMC13405886

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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.