中国骨质疏松性椎体压缩骨折椎体强化术后残余痛风险预测模型的meta分析

常梦静; 崔琳; 郑雪梅; 盛珺; 刘达; 廖冬发

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武警医学 ›› 2026, Vol. 37 ›› Issue (2) : 123-131.

论著

中国骨质疏松性椎体压缩骨折椎体强化术后残余痛风险预测模型的meta分析

常梦静^1,2, 崔琳^1,3, 郑雪梅^2,4, 盛珺², 刘达², 廖冬发²

作者信息 +

Meta-analysis of the risk prediction model of residual pain after vertebroplasty for osteoporotic vertebral compression fractures in China

CHANG Mengjing^1,2, CUI Lin^1,3, ZHENG Xuemei^2,4, SHENG Jun², LIU Da², LIAO Dongfa²

Author information +

文章历史 +

摘要

目的系统评价中国骨质疏松性椎体压缩骨折椎体强化术后残余痛风险预测模型,为临床提供参考依据。方法检索中国知网、万方、中国生物医学文献、维普、PubMed、Web of Science、Cochrane Library和EMbase等中英文数据库,检索时限为建库至2025-05-31,由2名研究者独立进行文献的筛选和资料的提取,采用预测模型偏倚风险评估工具(PROBAST)对文献进行质量评价,并使用RevMan 5.4软件对高频预测因子进行Meta分析。结果共纳入24篇文献,包括33个预测模型,样本量为45~610例,纳入模型的C-index为0.774~0.94,受试者操作特征曲线下面积为0.70~0.94。 PROBAST结果显示,纳入的风险预测模型整体适用性较好,但偏倚风险较高,与研究对象的数据来源、结局评估的盲法控制、缺失数据的处理及模型性能评估不完善等有关。结论筋膜损伤、椎体内真空裂隙、骨水泥分布、骨密度为共同的高频预测因子,临床工作者应重点关注。我国骨质疏松性椎体压缩骨折椎体强化术后残余痛风险预测模型尚存在不足,未来应进一步提高相关模型研究的质量并加强模型的外部验证与临床适用性研究。

Abstract

Objective To systematically evaluate the risk prediction models of residual pain after vertebroplasty for osteoporotic vertebral compression fractures in China, and to provide references for clinical practice. Methods Relevant studies were retrieved from databases including CNKI, Wanfang Data, Chinese Biomedical Literature Database, VIP Database, PubMed, Web of Science, Cochrane Library, and EMbase. The search period was from the establishment of the database to May 31, 2025. Two researchers independently screened the literature and extracted the data. The quality of the literature was evaluated using the Prediction Model Risk of Bias Assessment Tool (PROBAST), and a meta-analysis of the high-frequency predictors was conducted using RevMan 5.4 software. Results A total of 24 articles were included, including 33 prediction models. The total sample size ranged from 45 to 610 cases. The C-index of the included models was 0.774-0.94, and the area under the receiver operating characteristic curve ranged from 0.70-0.94. The results of the PROBAST showed that the overall applicability of the included risk prediction models was good, but the risk of bias was high, which was related to the data source of the study subjects, the blind control of outcome assessment, the handling of missing data, and the imperfect evaluation of model performance. Conclusions Fascial injury, intravertebral vacuum fissure, bone cement distribution, and bone density are common high-frequency predictors. Clinicians should pay special attention to these factors. The risk prediction models for residual pain after vertebral augmentation surgery for osteoporotic vertebral compression fractures in China still have deficiencies. In the future, the quality of related model research should be further improved, and the external validation and clinical applicability research of the model should be strengthened.

导出引用

常梦静, 崔琳, 郑雪梅, 盛珺, 刘达, 廖冬发. 中国骨质疏松性椎体压缩骨折椎体强化术后残余痛风险预测模型的meta分析[J]. 武警医学. 2026, 37(2): 123-131

CHANG Mengjing, CUI Lin, ZHENG Xuemei, SHENG Jun, LIU Da, LIAO Dongfa. Meta-analysis of the risk prediction model of residual pain after vertebroplasty for osteoporotic vertebral compression fractures in China[J]. Medical Journal of the Chinese People Armed Police Forces. 2026, 37(2): 123-131

中图分类号： R681

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