Evidence map›Paper›PMID 29728873›Full record

ReviewNeurosurgical review2020

Modern radiosurgical and endovascular classification schemes for brain arteriovenous malformations.

Ali Tayebi Meybodi, Michael T Lawton

Abstract readReview
PubMed Publisher
In one paragraph

Review in Neurosurgical review, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed, 1 pooled it
–field-weighted citation impact
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

10 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
  4. Basic Knowledge and Overview of Brain AVMs.Journal of neuroendovascular therapy · 2025
    Review
  5. Observational
  6. Review
  7. Article
  8. Microsurgical Treatment of Deep and Eloquent AVMs.Advances and technical standards in neurosurgery · 2022
    Article
  9. Observational
  10. 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.

Ali Tayebi MeybodiDivision of Neurological Surgery, Barrow Neurological Institute, 350 West Thomas Road, Phoenix, AZ, 85013, USA.
Michael T LawtonDivision of Neurological Surgery, Barrow Neurological Institute, 350 West Thomas Road, Phoenix, AZ, 85013, USA. Michael.Lawton@BarrowBrainandSpine.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Stereotactic radiosurgery (SRS) and endovascular techniques are commonly used for treating brain arteriovenous malformations (bAVMs). They are usually used as ancillary techniques to microsurgery but may also be used as solitary treatment options. Careful patient selection requires a clear estimate of the treatment efficacy and complication rates for the individual patient. As such, classification schemes are an essential part of patient selection paradigm for each treatment modality. While the Spetzler-Martin grading system and its subsequent modifications are commonly used for microsurgical outcome prediction for bAVMs, the same system(s) may not be easily applicable to SRS and endovascular therapy. Several radiosurgical- and endovascular-based grading scales have been proposed for bAVMs. However, a comprehensive review of these systems including a discussion on their relative advantages and disadvantages is missing. This paper is dedicated to modern classification schemes designed for SRS and endovascular techniques.

Indexed as

Endovascular ProceduresHumansIntracranial Arteriovenous MalformationsMicrosurgeryNeurosurgical ProceduresPatient SelectionRadiosurgeryTreatment OutcomeEmbolizationGrading systemOutcome predictionPollock-FlickingerRadiosurgery

Identifiers

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.