Evidence map›Paper›PMID 36657616›Full record

ArticleComputer methods in biomechanics and biomedical engineering

Modular incorporation of deformable spine and 3D neck musculature into a simplified human body finite element model.

Mitesh Lalwala, Bharath Koya, Karan Devane, F Scott Gayzik, Ashley A Weaver

Open access · greenAbstract read
In one paragraph

Article in Computer methods in biomechanics and biomedical engineering. 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
0.3field-weighted citation impact, top 41% 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

0 citing papers in PubMed, 1 citations in OpenAlex.

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

5 authors at 1 institution in 1 country.

Mitesh LalwalaDepartment of Biomedical Engineering, Wake Forest University School of Medicine, Winston-Salem, NC, USA.ORCID 0000-0002-4404-9071
Bharath KoyaDepartment of Biomedical Engineering, Wake Forest University School of Medicine, Winston-Salem, NC, USA.ORCID 0000-0003-3784-2706
Karan DevaneDepartment of Biomedical Engineering, Wake Forest University School of Medicine, Winston-Salem, NC, USA.ORCID 0000-0001-6891-2119
F Scott GayzikDepartment of Biomedical Engineering, Wake Forest University School of Medicine, Winston-Salem, NC, USA.ORCID 0000-0002-7443-5424
Ashley A WeaverDepartment of Biomedical Engineering, Wake Forest University School of Medicine, Winston-Salem, NC, USA.ORCID 0000-0002-4383-0106
Virginia Tech - Wake Forest University School of Biomedical Engineering & Sciences · US

Funding

Effect of protein supplementation during weight loss on older adult bone healthK25AG058804 · NIA · WAKE FOREST UNIVERSITY HEALTH SCIENCES · PI WEAVER, ASHLEY · 2019 to 2023
$672k
NIA NIH HHS K25 AG058804
6 · The paper itself

Abstract

Spinal injuries are a concern for automotive applications, requiring large parametric studies to understand spinal injury mechanisms under complex loading conditions. Finite element computational human body models (e.g. Global Human Body Models Consortium (GHBMC) models) can be used to identify spinal injury mechanisms. However, the existing GHBMC detailed models (with high computational time) or GHBMC simplified models (lacking vertebral fracture prediction capabilities) are not ideal for studying spinal injury mechanisms in large parametric studies. To overcome these limitations, a modular 50

Indexed as

Human BodySpinal FracturesAccidents, TrafficBiomechanical PhenomenaFinite Element AnalysisHumansMaleModels, Biologicalcomputational efficiencyinjury mechanismslumbarnecksimulationSpinal injuryvertebra

Identifiers

PMID36657616
PMCPMC10354211
OpenAlexW4317513987

What OpenQuestion holds

Textmetadata
LicenceTDM
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.