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成人择期腰椎融合术后疼痛减轻预测工具的开发和验证:一项多中心队列研究。

Development and validation of a prediction tool for pain reduction in adult patients undergoing elective lumbar spinal fusion: a multicentre cohort study.

机构信息

Department of Orthopaedics and Research School Caphri, Maastricht University Medical Centre+, P. Debyelaan 25, 6229 HX, Maastricht, The Netherlands.

NUTRIM School for Nutrition and Translational Research in Metabolism, Maastricht University, Maastricht, The Netherlands.

出版信息

Eur Spine J. 2020 Aug;29(8):1909-1916. doi: 10.1007/s00586-020-06473-w. Epub 2020 May 29.

DOI:10.1007/s00586-020-06473-w
PMID:32472345
Abstract

PURPOSE

On average, 56% of patients report a clinically relevant reduction in pain after lumbar spinal fusion (LSF). Preoperatively identifying which patient will benefit from LSF is paramount to improve clinical decision making, expectation management and treatment selection. Therefore, this multicentre study aimed to develop and validate a clinical prediction tool for a clinically relevant reduction in pain 1 to 2 years after elective LSF.

METHODS

The outcomes were defined as a clinically relevant reduction in predominant (worst reported pain in back or legs) pain 1 to 2 years after LSF. Patient-reported outcome measures and patient characteristics from 202 patients were used to develop a prediction model by logistic regression. Data from 251 patients were used to validate the model.

RESULTS

Nonsmokers (odds ratio = 0.41 [95% confidence interval = 0.19-0.87]), with lower Body Mass Index (0.93 [0.85-1.01]), shorter pain duration (0.49 [0.20-1.19]), lower American Society of Anaesthesiologists score (4.82 [1.35-17.25]), higher Visual Analogue Scale score for predominant pain (1.05 [1.02-1.08]), lower Oswestry Disability Index (0.96 [0.93-1.00]) and higher RAND-36 mental component score (1.03 [0.10-1.06]) preoperatively had a higher chance of a clinically relevant reduction in predominant pain. The area under the curve of the externally validated model yielded 0.68. A nomogram was developed to aid clinical decision making.

CONCLUSIONS

Using the developed nomogram surgeons can estimate the probability of achieving a clinically relevant pain reduction 1 to 2 years after LSF and consequently inform patients on expected outcomes when considering treatment.

摘要

目的

平均有 56%的患者在接受腰椎脊柱融合术(LSF)后报告疼痛有临床显著缓解。术前识别哪些患者将从 LSF 中受益对于改善临床决策、期望管理和治疗选择至关重要。因此,这项多中心研究旨在开发和验证一种用于预测 LSF 后 1 至 2 年时疼痛有临床显著缓解的临床预测工具。

方法

结局定义为 LSF 后 1 至 2 年时主要(背部或腿部报告的最严重疼痛)疼痛有临床显著缓解。使用逻辑回归从 202 名患者的患者报告结局测量和患者特征数据中开发预测模型。使用 251 名患者的数据验证模型。

结果

不吸烟者(优势比=0.41 [95%置信区间=0.19-0.87])、较低的体重指数(0.93 [0.85-1.01])、较短的疼痛持续时间(0.49 [0.20-1.19])、较低的美国麻醉医师协会评分(4.82 [1.35-17.25])、较高的主要疼痛视觉模拟评分(1.05 [1.02-1.08])、较低的 Oswestry 残疾指数(0.96 [0.93-1.00])和较高的 RAND-36 心理成分评分(1.03 [0.10-1.06])术前更有可能出现主要疼痛的临床显著缓解。外部验证模型的曲线下面积为 0.68。开发了一个列线图来帮助临床决策。

结论

使用开发的列线图,外科医生可以估计在 LSF 后 1 至 2 年时实现临床显著疼痛缓解的概率,从而在考虑治疗时告知患者预期结果。

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