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通过分层手术干预改善患者选择:奥胡斯脊柱转移瘤算法

Improved patient selection by stratified surgical intervention: Aarhus Spinal Metastases Algorithm.

作者信息

Wang Miao, Bünger Cody E, Li Haisheng, Sun Ming, Helmig Peter, Borhani-Khomani Gilava, Wu Chun S, Hansen Ebbe S, Choi David, Hoey Kristian

机构信息

Department of Orthopaedic E, Aarhus University Hospital (NBG), Noerrebrogade 44, Bldg 1A, DK-8000 Aarhus C, Denmark.

Department of Orthopaedic E, Aarhus University Hospital (NBG), Noerrebrogade 44, Bldg 1A, DK-8000 Aarhus C, Denmark.

出版信息

Spine J. 2015 Jul 1;15(7):1554-62. doi: 10.1016/j.spinee.2015.03.012. Epub 2015 Mar 13.

Abstract

BACKGROUND CONTEXT

Choosing the best surgical treatment for patients with spinal metastases remains a significant challenge for spine surgeons. There is currently no gold standard for surgical treatments. The Aarhus Spinal Metastases Algorithm (ASMA) was established to help surgeons choose the most appropriate surgical intervention for patients with spinal metastases.

PURPOSE

The purpose of this study was to evaluate the clinical outcome of stratified surgical interventions based on the ASMA, which combines life expectancy and the anatomical classification of patients with spinal metastases to inform surgical decision making.

STUDY DESIGN/SETTING: This is a retrospective study based on a prospective database.

PATIENT SAMPLE

A consecutive series of 515 spinal metastatic patients who underwent surgically treatment from December 1992 to June 2012 in Aarhus University Hospital were included prospectively and analyzed in detail retrospectively.

OUTCOME MEASURES

Survival time after surgery was determined for all patients. Neurological function was assessed using the Frankel score preoperatively and postoperatively (at the time of discharge). Complete outcome data were retrieved in 97.5% of this cohort.

METHODS

Patients with spinal metastases were identified from an institutional database that prospectively collected data since 1992. Survival status data were obtained from a national registry. Neurological function was determined from the same institutional database or local Electronic Patient Journal system. Surgeons evaluated and classified patients into five surgical groups preoperatively by using the revised Tokuhashi score (TS) and the Tomita anatomical classification (TC).

RESULTS

The overall median survival time of the cohort was 6.8 (95% confidence interval: 6.1-7.9) months. The median survival times in the five surgical groups determined by the ASMA were 2.1 (TS 0-4, TC 1-7), 5.1 (TS 5-8, TC 1-7), 12.1 (TS 9-11, TC 1-7 or TS 12-15, TC 7), 26.0 (TS 12-15, TC 4-6), and 36.0 (TS 12-15, TC 1-3) months. The 30-day mortality rate was 7.5%. Postoperative neurological function was maintained or improved in 469 patients (92.3%). Overall reoperation rate was 13.5%, commonly because of postoperative hematoma and new limb weakness.

CONCLUSIONS

The ASMA recommends at least two surgical options for a particular patient by determining the preoperative life expectancy and anatomical classification of the spinal metastases. This algorithm could help spine surgeons to discriminate the risks of surgeries. The ASMA provides a tool to guild surgeons to evaluate the spinal metastases patients, select potential optimal surgery, and avoid life-threatening risks.

摘要

背景

为脊柱转移瘤患者选择最佳手术治疗方案,对脊柱外科医生而言仍是一项重大挑战。目前手术治疗尚无金标准。奥胡斯脊柱转移瘤算法(ASMA)旨在帮助外科医生为脊柱转移瘤患者选择最合适的手术干预措施。

目的

本研究旨在评估基于ASMA的分层手术干预的临床效果,该算法结合了脊柱转移瘤患者的预期寿命和解剖学分类,以指导手术决策。

研究设计/地点:这是一项基于前瞻性数据库的回顾性研究。

患者样本

前瞻性纳入了1992年12月至2012年6月在奥胡斯大学医院接受手术治疗的515例连续性脊柱转移瘤患者,并进行了详细的回顾性分析。

观察指标

确定所有患者术后的生存时间。术前及术后(出院时)使用Frankel评分评估神经功能。该队列中97.5%的患者获得了完整的结局数据。

方法

从自1992年起前瞻性收集数据的机构数据库中识别出脊柱转移瘤患者。生存状态数据来自国家登记处。神经功能由同一机构数据库或当地电子病历系统确定。外科医生术前使用修订的Tokuhashi评分(TS)和Tomita解剖学分类(TC)将患者评估并分为五个手术组。

结果

该队列的总体中位生存时间为6.8(95%置信区间:6.1 - 7.9)个月。ASMA确定的五个手术组的中位生存时间分别为2.1(TS 0 - 4,TC 1 - 7)、5.1(TS 5 - 8,TC 1 - 7)、12.1(TS 9 - 11,TC 1 - 7或TS 12 - 15,TC 7)、26.0(TS 12 - 15,TC 4 - 6)和36.0(TS 12 - 15,TC 1 - 3)个月。30天死亡率为7.5%。469例患者(92.3%)术后神经功能得以维持或改善。总体再手术率为13.5%,常见原因是术后血肿和新出现的肢体无力。

结论

ASMA通过确定脊柱转移瘤患者术前的预期寿命和解剖学分类,为特定患者推荐至少两种手术方案。该算法有助于脊柱外科医生辨别手术风险。ASMA为外科医生评估脊柱转移瘤患者、选择潜在的最佳手术方案并避免危及生命的风险提供了一种工具。

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