Prognostic prediction model for chronic postsurgical pain among adult patients: a systematic review and meta-analysis

Yanjie Dong, Huolin Zeng, Lei Yang, Huan Song, Qian Li
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Abstract

Purpose

Chronic postsurgical pain (CPSP) presents a significant impact in the postoperative recovery, affecting patients’ outcomes and quality of life. Numerous prognostic prediction models have been developed to predict the risk of CPSP, however, the clinical utility remains variable. This systematic review and meta-analysis aimed to critically assessed and synthesize the existing CPSP prognostic prediction models in adult patients.

Methods

A comprehensive literature search was conducted in PubMed, Embase, and the Cochrane library up to August 2024. A total of 22 models were included in the systematic review, with 19 models subsequently integrated into the meta-analysis.

Results

The overall pooled C-index of the models was 0.79 (95% confidence interval [CI]: 0.75, 0.83; I2 = 88.6%). For studies evaluating CPSP at 3 months postoperatively, the pooled C-index was 0.80 (95% CI: 0.73, 0.87; I2 = 82.1%). At 4 months, the pooled C-index was 0.75 (95% CI: 0.62, 0.87; I2 = 82.8%), while studies considered CPSP at 6 months showed a pooled C-index of 0.81 (95% CI: 0.73, 0.89; I2 = 93.8%). For 12 months post-surgery, the C-index was 0.77 (95% CI: 0.74, 0.79; I2 = 0%). Among models with external validation, the C-index was 0.76 (95% CI: 0.70, 0.82; I2 = 68.2%). For orthopedic surgery, the C-index was 0.82 (95% CI: 0.74, 0.91; I2 = 92.7%). For breast surgery, the C-index was 0.78 (95% CI: 0.75, 0.81; I2 = 0%). For studies reported C-index, the C-index was 0.70 (95% CI: 0.66, 0.73; I2 = 0%) while the C-index was 0.81 (95% CI: 0.77, 0.85; I2 = 88%) for studies reported area under receiver operating characteristic curve.

Conclusions

While prognostic prediction models demonstrated promising discriminative performance, the high overall risk of bias raises concerns about their quality and generalizability. These findings underscore the urgent need for rigorously designed and externally validated models to improve CPSP risk prediction in clinical practice.

成年患者慢性术后疼痛的预后预测模型:系统回顾和荟萃分析
目的慢性术后疼痛(CPSP)对术后恢复有重要影响,影响患者的预后和生活质量。许多预后预测模型已经被开发来预测CPSP的风险,然而,临床效用仍然是可变的。本系统综述和荟萃分析旨在批判性地评估和综合现有的成人患者CPSP预后预测模型。方法对截至2024年8月的PubMed、Embase和Cochrane图书馆进行综合文献检索。总共有22个模型被纳入系统评价,随后有19个模型被纳入元分析。结果各模型的综合c指数为0.79(95%置信区间[CI]: 0.75, 0.83;i2 = 88.6%)。对于术后3个月评估CPSP的研究,合并c指数为0.80 (95% CI: 0.73, 0.87;i2 = 82.1%)。4个月时,合并c指数为0.75 (95% CI: 0.62, 0.87;I2 = 82.8%),而考虑6个月时CPSP的研究显示合并c指数为0.81 (95% CI: 0.73, 0.89;i2 = 93.8%)。术后12个月,c指数为0.77 (95% CI: 0.74, 0.79;i2 = 0%)。在经外部验证的模型中,c指数为0.76 (95% CI: 0.70, 0.82;i2 = 68.2%)。骨科手术的c指数为0.82 (95% CI: 0.74, 0.91;i2 = 92.7%)。对于乳房手术,c指数为0.78 (95% CI: 0.75, 0.81;i2 = 0%)。研究报告的c -指数为0.70 (95% CI: 0.66, 0.73;I2 = 0%), c指数为0.81 (95% CI: 0.77, 0.85;I2 = 88%)为研究报告的受试者工作特征曲线下面积。结论:虽然预后预测模型具有良好的判别性能,但较高的总体偏倚风险引起了对其质量和可推广性的担忧。这些发现强调迫切需要严格设计和外部验证的模型来改善临床实践中的CPSP风险预测。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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