Evidence map›Paper›PMID 29608016›Full record

ArticleArtificial organs2018

Cell Damage Index as Computational Indicator for Blood Cell Activation and Damage.

Markus Gusenbauer, Renáta Tóthová, Giulia Mazza, Martin Brandl, Thomas Schrefl, Iveta Jančigová, Ivan Cimrák

Abstract read
In one paragraph

Article in Artificial organs, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

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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

7 authors.

Markus GusenbauerDepartment for Integrated Sensor Systems, Danube University Krems, Krems an der Donau, Austria.ORCID http://orcid.org/0000-0002-3540-3964
Renáta TóthováDepartment of Software Technologies, University of Žilina, Žilina, Slovakia.
Giulia MazzaDepartment for Integrated Sensor Systems, Danube University Krems, Krems an der Donau, Austria.
Martin BrandlDepartment for Integrated Sensor Systems, Danube University Krems, Krems an der Donau, Austria.
Thomas SchreflDepartment for Integrated Sensor Systems, Danube University Krems, Krems an der Donau, Austria.
Iveta JančigováDepartment of Software Technologies, University of Žilina, Žilina, Slovakia.
Ivan CimrákDepartment of Software Technologies, University of Žilina, Žilina, Slovakia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Shear-induced hemolysis is a major concern in the design and optimization of blood-contacting devices. Even with a small amount of mechanical stress, inflammatory reactions can be triggered in the cells. Blood damage is typically estimated using continuum fluid dynamics simulations. In this study, we report a novel cell damage index (CDI) obtained by simulations on the single-cell level in a lattice Boltzmann fluid flow. The change of the cell surface area gives important information on mechanical stress of individual cells as well as for whole blood. We are using predefined basic channel designs to analyze and compare the newly developed CDI to the conventional blood damage calculations in very weak shear stress scenarios. The CDI can incorporate both volume fraction and channel geometry information into a single quantitative value for the characterization of flow in artificial chambers.

Indexed as

Computer SimulationMaterials TestingModels, BiologicalArtificial OrgansBlood CellsBlood Flow VelocityCell CommunicationEquipment DesignErythrocytesExtracorporeal CirculationHematocritHemodynamicsHemolysisHumansHydrodynamicsLab-On-A-Chip Devices-Blood cell dynamicsBlood damage index-Cell activation-Hemolysis-Immersed boundary method-Lattice Boltzmann method

Identifiers

PMID29608016
PMCPMC6099442

What OpenQuestion holds

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LicenceCC BY-NC
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Registered trials

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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.