脑动静脉畸形分类系统与Spetzler-Martin的比较综述。

Surgical neurology international Pub Date : 2025-05-09 eCollection Date: 2025-01-01 DOI:10.25259/SNI_140_2025
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, Ahmed Muthana, Samer S Hoz
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引用次数: 0

摘要

背景:动静脉畸形(AVMs)是复杂的血管异常,需要分类系统来指导治疗和预测结果。本文评估了多种AVM分类系统,包括广泛使用的Spetzler-Martin分级系统(SMGS),强调了它们在神经外科中改善临床决策和沟通的重要性。方法:使用谷歌Scholar、PubMed和Scopus进行文献检索,收集AVM分类系统的相关信息。我们的纳入标准涉及的文章引用了一个完善的分类系统,至少有两个组成部分。放射学、外科和临床结果系统地分为九个不同的AVM分级系统。本文重点比较了不同的AVM分类系统与SMGS的优缺点。结果:回顾了33篇文章,重点介绍了AVM分类系统的发展,其中SMGS是手术结果的基础。波洛克-弗利金格量表和匹兹堡AVM量表等系统提高了放射外科手术的预测,而劳顿-杨则增加了手术精度的因素。专门的分数细化了特定情况下的评分,而简化的系统,如斯佩茨勒-庞塞提高了独特环境下的可用性。结论:AVM分类系统,包括Spetzler-Martin、Pollock-Flickinger和Lawton-Young,为治疗和预后提供了重要的见解。虽然Spetzler-Martin可以有效预测手术结果,但像Lawton-Young这样的系统通过纳入其他因素来提高准确性,但由于复杂性,在临床应用中可能面临挑战。持续改进和验证对于提高预测准确性、优化患者护理以及将研究与临床实践联系起来至关重要。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Cerebral arteriovenous malformations classification systems in comparison with Spetzler-Martin: A comparative review.

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.

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