Evidence map›Paper›PMID 38014682›Full record

SynthesisJournal of the American Heart Association2023

Imaging Biomarkers and Prevalence of Complex Aortic Plaque in Cryptogenic Stroke: A Systematic Review.

Yu Sakai, Quy Cao, Jeremy Rubin, Jens Witsch, Dan Cohen-Addad, Katyucia de Macedo Rodrigues, Maria Begoña Coco-Martin, Pouyan Pasyar, Jesús Juega, Zhaoyang Fan and 3 more

Open access · goldAbstract readSystematic Review
In one paragraph

Synthesis in Journal of the American Heart Association, 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
1.8field-weighted citation impact, top 13% 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, 7 citations in OpenAlex.

  1. Article
  2. Article
  3. Review
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 5 institutions in 2 countries.

Yu SakaiDepartment of Radiology University of Pennsylvania Philadelphia PA USA.
Quy CaoDepartment of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine University of Pennsylvania Philadelphia PA USA.ORCID 0000-0002-6204-1305
Jeremy RubinDepartment of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine University of Pennsylvania Philadelphia PA USA.ORCID 0000-0002-8288-6022
Jens WitschDepartment of Neurology University of Pennsylvania Philadelphia PA USA.ORCID 0000-0001-8924-851X
Dan Cohen-AddadDepartment of Radiology and Imaging Sciences Emory University Atlanta GA USA.ORCID 0000-0002-8303-9191
Katyucia de Macedo RodriguesGreensboro Radiology Greensboro NC USA.ORCID 0000-0002-3649-102X
Maria Begoña Coco-MartinDepartment of Neurology University of Valladolid Valladolid Spain.ORCID 0000-0001-9977-429X
Pouyan PasyarDepartment of Radiology University of Pennsylvania Philadelphia PA USA.
Jesús JuegaDepartment of Neurology Vall d'Hebron University Hospital Barcelona Spain.ORCID 0000-0003-1309-0730
Zhaoyang FanDepartments of Radiology, Biomedical Engineering, and Radiation Oncology University of Southern California Los Angeles CA USA.ORCID 0000-0002-2693-0260
Scott E KasnerDepartment of Neurology University of Pennsylvania Philadelphia PA USA.ORCID 0000-0003-0418-6917
Brett L CucchiaraDepartment of Neurology University of Pennsylvania Philadelphia PA USA.ORCID 0000-0002-5218-9015
Jae W SongDepartment of Radiology University of Pennsylvania Philadelphia PA USA.ORCID 0000-0002-3127-6427
University of Pennsylvania · USEmory University · USUniversidad de Valladolid · ESUniversity of Southern California · USVall d'Hebron Hospital Universitari · ES

Funding

Longitudinal and quantitative MR plaque imaging for prediction of response to medical management in symptomatic intracranial atherosclerosisR01HL147355 · NHLBI · UNIVERSITY OF SOUTHERN CALIFORNIA · PI FAN, ZHAOYANG · 2019 to 2023
$2.1M
NHLBI NIH HHS R01 HL147355
6 · The paper itself

Abstract

backgroundComplex aortic plaque (CAP) is a potential embolic source in patients with cryptogenic stroke (CS). We review CAP imaging criteria for transesophageal echocardiogram (TEE), computed tomography angiography (CTA), and magnetic resonance imaging and calculate CAP prevalence in patients with acute CS. METHODS AND

resultsPubMed and EMBASE databases were searched up to December 2022 in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guideline. Two independent reviewers extracted data on study design, imaging techniques, CAP criteria, and prevalence. The Cochrane Collaboration tool and Guideline for Reporting Reliability and Agreement Studies were used to assess risk of bias and reporting completeness, respectively. From 2293 studies, 45 were reviewed for CAP imaging biomarker criteria in patients with acute CS (N=37 TEE; N=9 CTA; N=6 magnetic resonance imaging). Most studies (74%) used ≥4 mm plaque thickness as the imaging criterion for CAP although ≥1 mm (N=1, CTA), ≥5 mm (N=5, TEE), and ≥6 mm (N=2, CTA) were also reported. Additional features included mobility, ulceration, thrombus, protrusions, and assessment of plaque composition. From 23 prospective studies, CAP was detected in 960 of 2778 patients with CS (0.32 [95% CI, 0.24-0.41],

conclusionsTEE was commonly used to assess CAP in patients with CS. The most common CAP imaging biomarker was ≥4 mm plaque thickness. CAP was observed in one-third of patients with acute CS. However, high study heterogeneity suggests a need for reproducible imaging methods.

Indexed as

Brain IschemiaIschemic StrokePlaque, AtheroscleroticStrokeBiomarkersHumansPrevalenceProspective StudiesReproducibility of ResultsBiomarkersaortaatherosclerosisbiomarkerimagingstroke

Identifiers

PMID38014682
PMCPMC10727354
OpenAlexW4389087311

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.