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一种基于磁共振成像的腰椎间盘突出症新分类及全内镜下椎间盘切除术的算法推荐

A Novel Classification of Migrated Lumbar Disk Herniation Based on Magnetic Resonance Imaging and Algorithm Recommendations for Full-Endoscopic Discectomy.

机构信息

Department of Orthopedics, The Second Hospital of Jilin University, Changchun, China.

Department of Orthopaedics, The First Affiliated Hospital of Xinxiang Medical University, Xinxiang, China.

出版信息

Orthop Surg. 2024 Nov;16(11):2781-2792. doi: 10.1111/os.14203. Epub 2024 Aug 26.

DOI:10.1111/os.14203
PMID:39187393
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11541130/
Abstract

STUDY DESIGN

Retrospective clinical study.

OBJECTIVE

The purpose of this study was to establish a novel classification of migrated lumbar disk herniation (LDH) based on magnetic resonance imaging and provide appropriate treatment strategies for each type through algorithms.

SUMMARY OF BACKGROUND DATA

Full-endoscopic lumbar discectomy is a surgical technique that has been developed rapidly in recent years. For migrated LDH, few surgeons currently classify it with multiplanar positioning, and there is no consensus on the choice of treatment strategy. Therefore, we established a new multiplanar classification criteria that can localize the lesions more accurately than previous studies.

METHODS

A total of 263 eligible patients from March 2017 to March 2022 were included. Protrusions for each patient were located based on our classification and the surgical approach was selected according to our algorithms. The clinical symptoms of all patients before surgery, and at 1 day, 1 month, 3 months, 6 months, and 12 months after surgery were collected. Evaluations were performed using visual analogue scale (VAS), Oswestry Disability Index (ODI) and modified MacNab criteria. We used the chi-squared test, one-way analysis of variance (ANOVA), and t-test to compare perioperative results and postoperative 3-month, 6-month, and 12-month follow-up results.

RESULTS

VAS (low back pain) scores were reduced from 5.33 ± 2.67 to 0.73 ± 0.77 (p < 0.001), and VAS (leg pain) scores were reduced from 7.44 ± 2.21 to 0.37 ± 0.51 (p < 0.001). ODI scores improved from 58.46 ± 8.04 to 12.57 ± 2.51 (p < 0.001). According to the modified MacNab criteria, the excellent and good rate reached 92.78% at the 12-month follow-up. Twenty-six patients developed complications, all of which improved after treatment. Recurrence occurred in 13 patients, and four of them underwent secondary surgery.

CONCLUSIONS

This is an innovative classification method using multi-plane positioning, and the algorithm used with it can help surgeons make appropriate choices when using endoscopic technology to treat migrated LDH. Statistical analysis of follow-up data confirmed that this is a safe and effective strategy.

摘要

研究设计

回顾性临床研究。

目的

本研究旨在基于磁共振成像建立一种新的腰椎间盘突出症(LDH)迁移分类,并通过算法为每种类型提供合适的治疗策略。

背景资料概要

全内镜腰椎间盘切除术是近年来发展迅速的一种手术技术。对于迁移性 LDH,目前很少有外科医生对其进行多平面定位分类,对于治疗策略的选择也没有共识。因此,我们建立了一种新的多平面分类标准,可以比以前的研究更准确地定位病变。

方法

共纳入 2017 年 3 月至 2022 年 3 月的 263 名符合条件的患者。根据我们的分类,对每位患者的突出物进行定位,并根据我们的算法选择手术方法。收集所有患者术前、术后 1 天、1 个月、3 个月、6 个月和 12 个月的临床症状。采用视觉模拟评分(VAS)、Oswestry 功能障碍指数(ODI)和改良 MacNab 标准进行评估。采用卡方检验、单因素方差分析(ANOVA)和 t 检验比较围手术期结果和术后 3 个月、6 个月和 12 个月随访结果。

结果

VAS(腰痛)评分从 5.33±2.67 降至 0.73±0.77(p<0.001),VAS(腿痛)评分从 7.44±2.21 降至 0.37±0.51(p<0.001)。ODI 评分从 58.46±8.04 改善至 12.57±2.51(p<0.001)。根据改良 MacNab 标准,12 个月随访时优良率达到 92.78%。26 例患者出现并发症,经治疗后均得到改善。13 例患者复发,其中 4 例患者再次手术。

结论

这是一种使用多平面定位的创新分类方法,与之相关的算法可以帮助外科医生在使用内镜技术治疗迁移性 LDH 时做出合适的选择。对随访数据的统计分析证实了这是一种安全有效的策略。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0398/11541130/52fb3bf59ba7/OS-16-2781-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0398/11541130/726c8290828f/OS-16-2781-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0398/11541130/43ea7debec47/OS-16-2781-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0398/11541130/71ee992e3c3c/OS-16-2781-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0398/11541130/0d4040e35577/OS-16-2781-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0398/11541130/52fb3bf59ba7/OS-16-2781-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0398/11541130/726c8290828f/OS-16-2781-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0398/11541130/43ea7debec47/OS-16-2781-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0398/11541130/71ee992e3c3c/OS-16-2781-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0398/11541130/0d4040e35577/OS-16-2781-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0398/11541130/52fb3bf59ba7/OS-16-2781-g006.jpg

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