识别和解决胸腰椎爆裂性骨折分类预后验证的挑战:一篇叙述性综述。

IF 1.7 4区 医学 Q3 CLINICAL NEUROLOGY
Clinical Spine Surgery Pub Date : 2025-07-01 Epub Date: 2025-03-24 DOI:10.1097/BSD.0000000000001764
Mohamed M Aly, Mohammad El-Sharkawi, Andrei F Joaquim, Javier Pizones, Xavier A Santander Espinoza, Eugen C Popescu, Abdulaziz Bin Shebree N, Paul Gerdhem, Cumhur F Öner
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引用次数: 0

摘要

目的:回顾胸腰椎爆裂性骨折(TLBFs)的历史分类,并讨论其临床验证可能存在的差距。背景资料摘要:尽管有多种分类方案,神经完整患者TLBFs的治疗决策仍然存在争议。目前的分类与其predictive验证之间存在差距。方法:文献综述。结果:建立当前tlbf分类预测价值的潜在障碍可能与验证研究的缺陷有关,例如未经验证的结果测量和随机化的挑战。这也可能与诊断A3/A4骨折时观察者之间有限的可靠性有关。最后,这可能归因于the无法纳入所有预后变量,如计算机断层扫描(CT)参数,患者相关因素和创伤性椎间盘损伤,可能导致验证失败。结论:AOSpine患者和临床报告结果脊柱创伤(PROST)和最近提出的自然实验观察性研究有望减轻方法学上的挑战。鉴别A3/A4骨折的结构化方法和PLC损伤的标准化CT标准对于提高可靠性至关重要。最后,结合所有潜在预后变量的治疗算法,独立于形态学分类,可以提高分类的预测价值。在这种情况下,机器学习技术可能会有所帮助。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Toward Identifying and Resolving the Challenges to the Prognostic Validation of the Classifications for Thoracolumbar Burst Fractures: A Narrative Review.

Objective: To review the historical thoracolumbar burst fractures (TLBFs) classifications and discuss the probable gaps for their clinical validation.

Summary of background data: Despite multiple classification schemes, the treatment decisions for TLBFs in neurologically intact patients remain controversial. There are gaps between the current classifications and their predictive validation.

Methods: A narrative literature review.

Results: The potential barriers to establishing the predictive value of the current classifications of TLBFs could be connected to validation studies' flaws such as nonvalidated outcome measures and challenges of randomization. It could also be related to limited interobserver reliability in diagnosing A3/A4 fractures. Finally, it might be attributed to the inability to incorporate all prognostic variables, such as computed tomography (CT) parameters, patient-related factors, and traumatic disc injury, may result in failed validation.

Conclusion: AOSpine Patient and Clinical Reported Outcome Spine Trauma (PROST) and a recently proposed natural experiment observational study hold promise for mitigating methodological challenges. A structured approach for distinguishing A3/A4 fractures and standardized CT criteria for PLC injury is critical to improving reliability. Finally, a treatment algorithm incorporating all potential prognostic variables, independent of the morphologic classification, may improve the predictive value of the classification. Machine learning techniques could be helpful in this context.

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来源期刊
Clinical Spine Surgery
Clinical Spine Surgery Medicine-Surgery
CiteScore
3.00
自引率
5.30%
发文量
236
期刊介绍: Clinical Spine Surgery is the ideal journal for the busy practicing spine surgeon or trainee, as it is the only journal necessary to keep up to date with new clinical research and surgical techniques. Readers get to watch leaders in the field debate controversial topics in a new controversies section, and gain access to evidence-based reviews of important pathologies in the systematic reviews section. The journal features a surgical technique complete with a video, and a tips and tricks section that allows surgeons to review the important steps prior to a complex procedure. Clinical Spine Surgery provides readers with primary research studies, specifically level 1, 2 and 3 studies, ensuring that articles that may actually change a surgeon’s practice will be read and published. Each issue includes a brief article that will help a surgeon better understand the business of healthcare, as well as an article that will help a surgeon understand how to interpret increasingly complex research methodology. Clinical Spine Surgery is your single source for up-to-date, evidence-based recommendations for spine care.
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