Evidence map›Paper›PMID 34352453›Full record

ArticleComputers in biology and medicine2021

Development and multi-level validation of a computational model to predict traumatic aortic injury.

Wei Zeng, Adrian Caudillo, Sayak Mukherjee, Sang-Hyun Lee, Matthew B Panzer

Abstract read
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In one paragraph

Article in Computers in biology and medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.8field-weighted citation impact, top 27% 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

2 citing papers in PubMed, 7 citations in OpenAlex.

  1. Article
  2. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

5 authors at 1 institution in 1 country.

Wei ZengCenter for Applied Biomechanics, University of Virginia, Charlottesville, VA, USA. Electronic address: zeng.work@gmail.com.
Adrian CaudilloCenter for Applied Biomechanics, University of Virginia, Charlottesville, VA, USA.
Sayak MukherjeeCenter for Applied Biomechanics, University of Virginia, Charlottesville, VA, USA.
Sang-Hyun LeeCenter for Applied Biomechanics, University of Virginia, Charlottesville, VA, USA.
Matthew B PanzerCenter for Applied Biomechanics, University of Virginia, Charlottesville, VA, USA. Electronic address: panzer@virginia.edu.
University of Virginia · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Traumatic aortic injury (TAI) is one of the leading causes of fatalities in blunt impact. However, there is no consensus on the injury mechanism of TAI in traffic accidents, mainly due to the complexity of occurrence scenarios and limited real-world crash data relevant to TAI. In this study, a computational model of the aorta with nonlinear mechanical characteristics and accurate morphology was developed and integrated within a thorax finite element model that included all major anatomical structures. To maximize the model's capability for predicting TAI, a multi-level process was presented to validate the model comprehensively. At the component level, the in vitro aortic pressurization testing was simulated to mimic the aortic burst pressure. Then, a sled test of a truncated cadaver was modeled to evaluate aorta response under posterior acceleration. The frontal chest pendulum impact was utilized to validate the performance of the aorta within full body model under direct chest compression. A parametric study was implemented to determine an injury tolerance for the aorta under these different loading conditions. The simulated peak pressure before aortic rupture was within the range of the experimental burst pressure. For the sled test, the simulated chest deflection and cross-sectional pressure of the aorta were correlated with the experimental measurement. No aorta injury was observed in simulated results of both sled test and chest pendulum impact, which matched the experimental findings. The present model will be a useful tool for understanding the TAI mechanisms, evaluating injury tolerance, and developing prevention strategies for aortic injuries.

Indexed as

Accidents, TrafficAortic RuptureAortaBiomechanical PhenomenaCross-Sectional StudiesHumansThoraxAorta modelBiofidelityFinite element methodHuman thoraxInjury biomechanicsTraumatic aortic injury (TAI)Validation

Identifiers

PMID34352453
OpenAlexW3190693220

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.