Evidence map›Paper›PMID 37980307›Full record

ArticleMedical & biological engineering & computing2024

Insights from 3D modeling and fluid dynamics in COVID-19 pneumonia.

M Kürşat Gökcan, D Funda Kurtuluş, Adalet Aypak, Murathan Köksal, Sarper R Ökten

Open access · greenAbstract read
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In one paragraph

Article in Medical & biological engineering & computing, 2024. 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
0.8field-weighted citation impact, top 23% 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, 3 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 3 institutions in 1 country.

M Kürşat GökcanOtorhinolaryngology, Head and Neck Surgery Department, Ankara University Medical School, Ankara, Turkey. gokcan@medicine.ankara.edu.tr.ORCID http://orcid.org/0000-0002-4160-7349
D Funda KurtuluşDepartment of Aerospace Engineering, Faculty of Engineering, Middle East Technical University, Ankara, Turkey.ORCID https://orcid.org/0000-0002-0678-9474
Adalet AypakDepartment of Infectious Diseases and Clinical Microbiology, Ankara Bilkent City Hospital, Ankara, Turkey.ORCID https://orcid.org/0000-0001-8850-2475
Murathan KöksalDepartment of Radiology, Ankara Bilkent City Hospital, Ankara, Turkey.ORCID https://orcid.org/0000-0002-5936-2925
Sarper R ÖktenDepartment of Radiology, Ankara Bilkent City Hospital, Ankara, Turkey.ORCID https://orcid.org/0000-0002-4721-6357
Bilkent University · TRAnkara University · TRMiddle East Technical University · TR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We address the lack of research regarding aerodynamic events behind respiratory distress at COVID-19. The use of chest CT enables quantification of pneumonia extent; however, there is a paucity of data regarding the impact of airflow changes. We reviewed 31 COVID-19 patients who were admitted in March 2020 with varying severity of pulmonary disease. Lung volumes were segmented and measured on CT images and patient-specific models of the lungs were created. Incompressible, laminar, and three-dimensional Navier-Stokes equations were used for the fluid dynamics (CFD) analyses of ten patients (five mild, five pneumonia). Of 31 patients, 17 were female, 18 had pneumonia, and 2 were deceased. Effective lung volume decreased in the general group, but the involvement of the right lung was prominent in dyspnea patients. CFD analyses revealed that the mass flow distribution was significantly distorted in pneumonia cases with diminished flow rate towards the right lung. In addition, the distribution of flow parameters showed mild group had less airway resistance with higher velocity (1.228 m/s vs 1.572 m/s) and higher static pressure values at airway branches (1.5112 Pa vs 1.3024 Pa). Therefore, we conclude that airway resistance and mass flow rate distribution are as important as the radiological involvement degree in defining the disease severity.

Indexed as

COVID-19Imaging, Three-DimensionalComputer SimulationFemaleHumansHydrodynamicsLungMaleAirway resistance/physiologyComputer simulationCOVID-19HydrodynamicsRespiratory system/diagnostic imaging

Identifiers

PMID37980307
OpenAlexW4388792333

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.