Data · dataset · 2015
Computational analysis of pediatric ventricular assist device implantation to decrease cerebral particulate embolization
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Stroke is the most devastating complication after ventricular assist device (VAD) implantation with a 19% incidence and 65% mortality in the pediatric population.
Description
Current pediatric VAD technology and anticoagulation strategies alone are suboptimal. VAD implantation assisted by computational methods (CFD) may contribute reducing the risk of cerebral embolization.
Representative three-dimensional aortic arch models of an infant and a child were generated. An 8 mm VAD outflow-graft (VAD-OG) anastomosed to the aorta was rendered and CFD was applied to study blood flow patterns. Particle tracks, originating in the VAD, were computed with a Lagrangian phase model and the percentage of particles entering the cerebral vessels was calculated.
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Eight implantation configurations (infant = 5 and child = 3) and 5 particle sizes (0.5, 1, 2, 3, and 4 mm) were considered. For the infant model, percentage of particles entering the cerebral vessels ranged from 15% for a VAD-OG anastomosed at 90° to the aorta, to 31% for 30° VAD-OG anastomosis (overall percentages: X 2 = 10,852, p 2 = 10,323, p
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- Repository landing page tandf.figshare.com/articles/dataset/Computational_analysis_of_pediatric_ventricul… ↗
landing page · from DataCite
- DOI doi.org/10.6084/m9.figshare.1494829 ↗
DOI / persistent id · from DataCite
Documentation and papers
- Creative Commons Attribution 4.0 International creativecommons.org/licenses/by/4.0/legalcode ↗
license · from DataCite
- IsSupplementTo 10.1080/10255842.2015.1062478 doi.org/10.1080/10255842.2015.1062478 ↗
publication · from DataCite
Catalogue records · 2
- DataCite API api.datacite.org/dois/10.6084/m9.figshare.1494829 ↗
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- DataCite Commons commons.datacite.org/doi.org/10.6084/m9.figshare.1494829 ↗
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Topics
- Stated by source
- Biological sciences · Mathematics
- From keywords
- Engineering · Life Sciences · Mathematics & Statistics · Medicine & Health
- Inferred from text
- Biomedical engineering 70%
Provenance · 1 source records, 15 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| DataCite | 10.6084/m9.figshare.1494829 | 14 d ago | JSON v1 |
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| concepts[field].anzsrc:group:4003 | enrichment · DataCite | taxonomy-embedding@1.1.0 | title+keywords+description (70%) |
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| concepts[field].fos:mathematics | source · DataCite | connector:datacite@1.0.0 | |
| concepts[field].local:field:engineering | mapping · DataCite | vocabulary-mapper@1.0.0 | keywords['Engineering'] |
| concepts[field].local:field:life-sciences | mapping · DataCite | vocabulary-mapper@1.0.0 | keywords['Biological Sciences'] |
| concepts[field].local:field:mathematics-statistics | mapping · DataCite | vocabulary-mapper@1.0.0 | keywords['Mathematics'] |
| concepts[field].local:field:medicine-health | mapping · DataCite | vocabulary-mapper@1.0.0 | keywords['Medicine'] |
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