Evidence map›Paper›PMID 40469353›Full record

ReviewSurgical neurology international2025

Cerebral arteriovenous malformations classification systems in comparison with Spetzler-Martin: A comparative review.

Mohamad M Assker, Ahmed M Youssef, Saeed A S Mohammed, Noor M Akar, Mohammed A Hashim, Narjis Kadhim, Noor Al-Saadi, Mostafa H Algabri, Mustafa J Shukur, Mustafa Ismail and 2 more

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In one paragraph

Review in Surgical neurology international, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

12 authors.

Mohamad M AsskerDepartment of Radiology, Sheikh Khalifa Medical City, Abu Dhabi, United Arab Emirates.
Ahmed M YoussefDepartment of Education, Al Qassimi Hospital, Sharjah, United Arab Emirates.
Saeed A S MohammedDepartment of Neurosurgery, Almana General Hospital, Al-Jubail City, Eastern Province, Saudi Arabia.
Noor M AkarDepartment of Neurosurgery, College of Medicine, Al-Nahrain University, Baghdad, Iraq.
Mohammed A HashimDepartment of Neurosurgery, College of Medicine, University of Baghdad, Baghdad, Iraq.
Narjis KadhimDepartment of Neurosurgery, College of Medicine, Al-Nahrain University, Baghdad, Iraq.
Noor Al-SaadiDepartment of Neurosurgery, College of Medicine, University of Babylon, Hilla, Iraq.
Mostafa H AlgabriDepartment of Neurosurgery, College of Medicine, University of Baghdad, Baghdad, Iraq.
Mustafa J ShukurDepartment of Public health, Boonshoft School of Medicine, Wright State University, Ohio, United States.
Mustafa IsmailDepartment of Surgery, Baghdad Teaching Hospital, Medical City Complex, Al Risafa, Iraq.
Ahmed MuthanaDepartment of Neurosurgery, University of Baghdad, Al-Karkh, Baghdad, Iraq.
Samer S HozDepartment of Neurosurgery, University of Cincinnati Medical Center, Cincinnati, Ohio, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Arteriovenous malformations (AVMs) are complex vascular anomalies requiring classification systems to guide treatment and predict outcomes. This review evaluates multiple AVM classification systems, including the widely used Spetzler-Martin Grading System (SMGS), emphasizing their importance in neurosurgery for improving clinical decision-making and communication. Methods: We conducted a literature search using Google Scholar, PubMed, and Scopus to gather information on AVM classification systems. Our inclusion criteria involved articles that referenced a well-established classification system with at least two components. Radiological, surgical, and clinical outcomes systematically categorized nine distinct AVM grading systems. The review focuses on comparing the advantages and limitations of different AVM classification systems to the SMGS. Results: A review of 33 articles highlights the evolution of AVM classification systems, with the SMGS as a foundation for surgical outcomes. Systems such as the Pollock-Flickinger and Pittsburgh AVM scale improve radiosurgery predictions, while Lawton-Young adds factors for surgical precision. Specialized scores refine grading for specific cases, and simplified systems like Spetzler-Ponce enhance usability in unique contexts. Conclusion: AVM classification systems, including Spetzler-Martin, Pollock-Flickinger, and Lawton-Young, provide critical insights into treatment and prognosis. While Spetzler-Martin effectively predicts surgical outcomes, systems like Lawton-Young enhance accuracy by incorporating additional factors but may face challenges in clinical application due to complexity. Continued refinement and validation are essential to improve predictive accuracy, optimize patient care, and connect research with clinical practice.

Indexed as

Arteriovenous malformationsBrainCerebral angiographyClassificationGrading systemOutcome predictionPollock-FlickingerRadiosurgeryScoringSpetzler-martin grading

Identifiers

PMID40469353
PMCPMC12134889

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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.