Evidence map›Paper›PMID 30380952›Full record

ReviewInterventional neuroradiology : journal of peritherapeutic neuroradiology, surgical procedures and related neurosciences2019

Treatment of direct carotid-cavernous fistulas with flow diversion - does it work?

Zeynep Hüseyinoglu, Marvin D Oppong, Andrew S Griffin, Erik Hauck

Abstract readCase ReportsReview
In one paragraph

Review in Interventional neuroradiology : journal of peritherapeutic neuroradiology, surgical procedures and related neurosciences, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed, 1 pooled it
0.8field-weighted citation impact, top 26% 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, 1 synthesis or guideline pooled it, 11 citations in OpenAlex.

  1. Treatment of carotid cavernous sinus fistulas with flow diverters. A case report and systematic review.Interventional neuroradiology : journal of peritherapeutic neuroradiology, surgical procedures and related neurosciences · 2022
    Pooled it
  2. Article
  3. 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

4 authors at 1 institution in 1 country.

Zeynep HüseyinogluDuke University Medical Center, Department of Neurosurgery, Durham, USA.
Marvin D OppongDuke University Medical Center, Department of Neurosurgery, Durham, USA.
Andrew S GriffinDuke University Medical Center, Department of Neurosurgery, Durham, USA.ORCID https://orcid.org/0000-0003-3266-1359
Erik HauckDuke University Medical Center, Department of Neurosurgery, Durham, USA.
Duke Medical Center · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Direct carotid-cavernous fistulas (CCFs) are high flow lesions that can be challenging to treat. A number of recent reports suggest that flow diversion may be a viable treatment option. We present a case of a post-traumatic CCF successfully treated with flow diversion and provide a review of the literature. Our results suggest that flow diversion is a potentially effective treatment option for CCFs and is most successful when used as an adjunctive therapy.

Indexed as

Accidental FallsAngiography, Digital SubtractionAnticoagulantsCarotid-Cavernous Sinus FistulaCerebral AngiographyComputed Tomography AngiographyDimethyl SulfoxideEmbolization, TherapeuticGlasgow Coma ScaleHematoma, SubduralHumansMalePolyvinylsTomography, X-Ray ComputedYoung AdultAnticoagulantsDimethyl SulfoxideOnyx copolymerPolyvinylsDirect carotid-cavernous fistulaflow diversionpipeline embolization device

Identifiers

PMID30380952
PMCPMC6448386
OpenAlexW2899183462

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.