Evidence map›Paper›PMID 31728661›Full record

ReviewCurrent treatment options in cardiovascular medicine2019

Vessel Wall Imaging of Cerebrovascular Disorders.

Kyle C Kern, David S Liebeskind

Abstract readReview
PubMed Publisher
In one paragraph

Review in Current treatment options in cardiovascular medicine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
1.7field-weighted citation impact, top 16% 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

7 citing papers in PubMed, 17 citations in OpenAlex.

  1. Article
  2. Stroke in Asia.Cerebrovascular diseases extra · 2024
    Review
  3. Article
  4. Article
  5. Review
  6. Review
  7. 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

2 authors at 1 institution in 1 country.

Kyle C KernComprehensive Stroke Center, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, 710 Westwood Plaza, Los Angeles, CA, 90095, USA.ORCID http://orcid.org/0000-0002-2703-7669
David S LiebeskindNeurovascular Imaging Research Core, UCLA Comprehensive Stroke Center, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, 635 Charles E Young Dr. South, Suite 225, Los Angeles, CA, 90095, USA. dliebeskind@mednet.ucla.edu.
University of California, Los Angeles · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purpose of reviewHigh-resolution magnetic resonance vessel wall imaging (VWI) permits direct visualization of intracranial arterial wall pathology, providing diagnostic and prognostic information that is complementary to conventional imaging techniques. We highlight the most recent studies that have advanced the clinical application of VWI. RECENT

findingsVWI aids in distinguishing and diagnosing intracranial atherosclerotic disease (ICAD), intracranial dissections, central nervous system vasculitis, reversible cerebral vasoconstriction syndrome, and moyamoya disease. VWI may help predict recurrent stroke in ICAD, treatment effects in vasculitis, and disease progression in moyamoya. VWI also identifies ruptured intracranial aneurysms and may predict stability of unruptured aneurysms. Implementing VWI as an adjunctive imaging technique may permit earlier and noninvasive discrimination of rare vasculopathies. However the prognostic utility of VWI for more common cerebrovascular pathologies requires further validation.

Indexed as

Cerebrovascular disordersCNS vasculitisIntracranial aneurysmIntracranial atherosclerosisMagnetic resonance imagingMoyamoya disease

Identifiers

PMID31728661
OpenAlexW2988076216

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.