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膝关节盘状半月板损伤患者关节镜术后疼痛的列线图预测模型构建
引用本文:柴晟,蒋杰,屈宗斌,邓章荣,吕青,曾伟清. 膝关节盘状半月板损伤患者关节镜术后疼痛的列线图预测模型构建[J]. 广东医学, 2023, 44(3): 357-361. DOI: 10.13820/j.cnki.gdyx.20222787
作者姓名:柴晟  蒋杰  屈宗斌  邓章荣  吕青  曾伟清
作者单位:桂林市中医医院骨一科(广西桂林 541002)
摘    要:目的 分析膝关节盘状半月板(DLM)损伤患者关节镜术后疼痛的危险因素,并构建列线图预测模型。方法 收集2017年1月至2021年12月行关节镜手术治疗的217例DLM损伤患者临床资料。依照NRS数字分级法评估术侧膝关节及髌周疼痛情况,将患者分为疼痛组(≤4分,n=26)和非疼痛组(≥4分,n=191)。采用受试者工作特征(ROC)曲线分析获取有统计学意义的连续性变量的最佳截断值。采用多因素logistic回归模型分析DLM损伤患者关节镜术后疼痛的危险因素。构建预测DLM损伤患者关节镜术后疼痛的列线图预测模型,采用校正曲线对列线图预测模型进行内部验证和性能评价,决策曲线对列线图预测模型的预测效能进行临床净收益评估。结果 疼痛组患者年龄、关节软骨损伤比例、术后无冷敷比例均高于非疼痛组(P<0.05),术后负重时间早于非疼痛组(P<0.05)。ROC曲线分析显示:年龄、术后负重时间的AUC分别为0.767、0.774;最佳截断值分别为54岁、7 d。年龄(>54岁)、关节软骨损伤(有)、术后负重时间(≤7 d)是DLM损伤患者关节镜术后疼痛的独立危险因素,术后冷敷(有)是D...

关 键 词:盘状半月板  损伤  关节镜  术后疼痛  列线图

Construction of nomograph model for predicting pain in patients with discoid meniscus injury after arthroscopy
CHAI Sheng,JIANG Jie,QU Zong-bin,Deng Zhang-rong,LV Qing,ZENG Wei-qing. Construction of nomograph model for predicting pain in patients with discoid meniscus injury after arthroscopy[J]. Guangdong Medical Journal, 2023, 44(3): 357-361. DOI: 10.13820/j.cnki.gdyx.20222787
Authors:CHAI Sheng  JIANG Jie  QU Zong-bin  Deng Zhang-rong  LV Qing  ZENG Wei-qing
Affiliation:Department of Orthopedics, Guilin Hospital of Traditional Chinese Medicine, Guilin 541002, Guangxi, China
Abstract:Objective To analyze the risk factors of pain after arthroscopy in patients with discoid meniscus injury, and to construct a nomograph predicting model. Methods The clinical data of 217 patients with discoid meniscus injury received arthroscopic surgery from January 2017 to December 2021 were collected. ROC curve analysis was used to obtain the best cut-off value of statistically significant continuous variables. Multivariate logistic regression model was used to analyze the risk factors of pain in patients with discoid meniscus injury after arthroscopy. The nomograph prediction model for predicting the pain of patients with discoid meniscus injury after arthroscopy was constructed. The calibration curve was used to internally verify and evaluate the performance of the nomograph prediction model. The decision curve was used to evaluate the clinical net benefit of the prediction efficiency of the nomograph prediction model. Results The age, the proportion of articular cartilage injury and the proportion of no cold compress after operation in the pain group were higher than those in the non-pain group (P<0.05), and the postoperative weight-bearing time was earlier than that in the non-pain group (P<0.05). ROC curve analysis showed that the AUCs of age and postoperative weight-bearing time were 0.767 and 0.774, respectively; with the best cutoff values of 54 years old and 7 days, respectively. Age (>54 years old), articular cartilage injury (with) and postoperative weight-bearing time (≤7 days) were independent risk factors for arthroscopic pain in patients with discoid meniscus injury. Postoperative cold compress (with) was the protective factor for arthroscopic pain in patients with discoid meniscus. The internal validation results showed that the C-index of the nomogram model for predicting the pain of patients with discoid meniscus injury after arthroscopy was 0.758 (95%CI: 0.657-0.949). The calibration curve shows a good consistency between the observed value and the predicted value. The threshold of pain after arthroscopy in patients with discoid meniscus injury predicted by nomograph model was >0.12, and the nomograph prediction model provided clinical net income. In addition, the clinical net benefit of nomogram prediction model was higher than that of age, articular cartilage injury, postoperative weight-bearing time and postoperative cold compress. Conclusion Based on age, articular cartilage injury, postoperative weight-bearing time and postoperative cold compress, a nomograph model for predicting arthroscopic postoperative pain in patients with discoid meniscus injury of the knee was constructed. The model has good predictive value for arthroscopic postoperative pain in patients with discoid meniscus injury of the knee, and can be used to identify high-risk patients with postoperative pain.
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