Evidence map›Paper›PMID 37426382›Full record

ArticleAPL bioengineering2023

Hemodynamics of thrombus formation in intracranial aneurysms: An

Qiongyao Liu, Ali Sarrami-Foroushani, Yongxing Wang, Michael MacRaild, Christopher Kelly, Fengming Lin, Yan Xia, Shuang Song, Nishant Ravikumar, Tufail Patankar and 3 more

Open access · goldAbstract read
In one paragraph

Article in APL bioengineering, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
1.9field-weighted citation impact, top 14% 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

3 citing papers in PubMed, 9 citations in OpenAlex.

  1. Article
  2. Article
  3. Frontiers in neurology
    Article
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

13 authors at 3 institutions in 2 countries.

Christopher KellyCentre for Computational Imaging and Simulation Technologies in Biomedicine (CISTIB), School of Computing, University of Leeds, Leeds, United Kingdom.ORCID https://orcid.org/0000-0003-2401-0839
Nishant RavikumarCentre for Computational Imaging and Simulation Technologies in Biomedicine (CISTIB), School of Computing, University of Leeds, Leeds, United Kingdom.ORCID https://orcid.org/0000-0003-0134-107X
Tufail PatankarLeeds General Infirmary, Leeds, United Kingdom.ORCID https://orcid.org/0000-0003-3460-1528
Zeike A TaylorSchool of Mechanical Engineering, University of Leeds, Leeds, United Kingdom.ORCID https://orcid.org/0000-0002-0718-1663
Toni LassilaCentre for Computational Imaging and Simulation Technologies in Biomedicine (CISTIB), School of Computing, University of Leeds, Leeds, United Kingdom.ORCID https://orcid.org/0000-0001-8947-1447
University of Leeds · GBEngineering and Physical Sciences Research Council · GBLeeds General Infirmary · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

How prevalent is spontaneous thrombosis in a population containing all sizes of intracranial aneurysms? How can we calibrate computational models of thrombosis based on published data? How does spontaneous thrombosis differ in normo- and hypertensive subjects? We address the first question through a thorough analysis of published datasets that provide spontaneous thrombosis rates across different aneurysm characteristics. This analysis provides data for a subgroup of the general population of aneurysms, namely, those of large and giant size (>10 mm). Based on these observed spontaneous thrombosis rates, our computational modeling platform enables the first

Identifiers

PMID37426382
PMCPMC10329514
OpenAlexW4383500200

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.