基于前瞻性队列建立与验证骨科术后慢性疼痛的预测模型

Development and validation of a prediction model for chronic post-surgical pain after orthopedic surgery based on a prospective cohort

摘要:

目的：基于前瞻性设计，开发与验证适用于不同骨科术式的慢性术后疼痛(Chronic post-surgical pain, CPSP)预测模型。方法：研究设计为前瞻性研究，选取2023年7月至2024年5月在广州医科大学附属第五医院行择期骨科手术的成年患者。采用多因素logistic回归建立CPSP预测模型，通过自举法与验证集进行模型的内外部验证。结果：共298名患者纳入正式分析，训练集（n=200）和验证集(n=98)中有104例（52%）和50例（51%）发生CPSP。所得CPSP预测模型的ROC曲线下面积为0.769（95%CI : 0.705-0.834），外部验证结果为0.822（95%CI : 0.739-0.905）。校准曲线在内外部验证中均接近对角线，决策曲线高于极端曲线。模型包含5个预测因子，分别为术前DN4评分（OR 1.28，95% CI 0.98-1.67），术后首日疼痛的最严重程度（OR 1.24，95% CI 1.09-1.41），术后首日的DN4评分（OR 1.34，95% CI 1.00-1.79），术后住院天数（OR 1.08，95% CI 1.00-1.16），围术期使用科博肽（OR 1.81，95% CI 0.86-3.83）。结论：本研究建立并验证了适用于不同骨科术式的CPSP预测模型，可用于早期识别CPSP的风险患者。研究首次发现围术期使用科博肽为CPSP的风险因素之一，其与CPSP的关系有待进一步研究。

Abstract:

Objective: Based on prospective design, a predictive model for chronic post-surgical pain (CPSP) was developed and verified for different orthopedic surgery types. Methods: The study design was a prospective study, and the subjects were selected from adult patients who underwent elective orthopedic surgery in the Fifth Affiliated Hospital of Guangzhou Medical University from July 2023 to May 2024. Multivariate logistic regression was used to establish a CPSP prediction model, and the model was internally and externally validated by bootstrapping and validation sets. Results: A total of 298 patients were included in the formal analysis, and 104 (52%) and 50 (51%) patients in the training set (n=200) and validation set (n=98) developed CPSP. The area under the ROC curve of the obtained CPSP prediction model was 0.769 (95% CI: 0.705-0.834), and the external verification result was 0.822(95% CI: 0.739-0.905). The calibration curve is close to diagonal in internal and external verification, and the decision curve is higher than the extreme curve. The model contains 5 predictors, including Preoperative DN4 score (OR 1.28, 95% CI 0.98-1.67), Worst pain on POD1 (OR 1.24, 95% CI 1.09-1.41), DN4 score on POD1 (OR 1.34, 95% CI 1.00-1.79), Postoperative hospital stay (OR 1.08, 95% CI 1.00-1.16), Perioperative Cobratide (OR 1.81, 95% CI 0.86-3.83). Conclusions: This study established and verified a CPSP prediction model suitable for different orthopedic surgery procedures, which can be used to identify patients at risk of CPSP early. For the first time, the study found that perioperative use of Cobratide is one of the risk factors for CPSP, and its relationship with CPSP needs further study.