随机森林算法对膝骨性关节炎关节镜术后老年病人急性疼痛的风险预测

    Study on the random forest algorithm for predicting the risk of acute pain in elderly patients with knee osteoarthritis after arthroscopy

    • 摘要:
      目的 探究随机森林算法在老年膝骨性关节炎膝关节镜治疗后早期急性疼痛风险中的预测价值。
      方法 前瞻性选取拟行膝关节镜治疗的老年膝骨性关节炎病人200例作为研究对象。术前1 d收集病人一般资料, 术后3 d统计病人病情资料, 通过单因素、多因素分析老年膝骨性关节炎病人术后早期急性疼痛的保护和危险因素。采用随机森林算法对各变量重要性进行排序, 建立术后早期急性疼痛的预测模型。
      结果 老年膝骨性关节炎病人术后早期急性疼痛发生率为61.42%(121/197);2组在术前关节软骨损伤程度、术后股四头肌功能练习、术后PCIA、加用镇痛药物、年龄、术前活动时疼痛程度、术前膝关节功能(KSS)评分、恐惧视觉模拟评分法(FAVS)、疼痛灾难化量表(PCS)、综合医院焦虑抑郁量表(HADS)总分方面比较, 差异均有统计学意义(P < 0.05~P < 0.01);术后股四头肌功能练习(OR=0.357, P < 0.01)、术后PCIA(OR=0.261, P < 0.01)、加用镇痛药物(OR=0.430, P < 0.01)是老年膝骨性关节炎病人术后早期急性疼痛的保护因素, 术前关节软骨损伤程度(OR=5.607, P < 0.01)、年龄(OR=4.555, P < 0.01)、FAVS(OR=5.214, P < 0.01)、PCS(OR=4.138, P < 0.01)、HADS总分(OR=6.798, P < 0.01)是其危险因素;基于logistic回归分析构建随机森林模型预测老年膝骨性关节炎病人术后早期急性疼痛发生风险AUC为0.892, 灵敏度为77.27%, 特异度为88.89%。
      结论 术后股四头肌功能练习、术后PCIA、加用镇痛药物、术前关节软骨损伤程度、年龄、FAVS、PCS、HADS总分是老年膝骨性关节炎病人术后早期急性疼痛的影响因素, 构建预测模型进行预测和重要性分析, 有利于指导临床精准实施防控措施。

       

      Abstract:
      Objective To explore the predictive value of random forest algorithm in the early acute pain risk of elderly patients with knee osteoarthritis after knee arthroscopy.
      Methods The elderly patients with knee osteoarthritis scheduled by knee arthroscopy were prospectively analyzed, and 200 patients who met the inclusion and exclusion criteria were selected as the research subjects.The general information of patients was collected before 1 day of surgery, and the condition of patients was statistically analyzed after 3 days of surgery.The protective and risk factors of early postoperative acute pain in elderly patients with knee osteoarthritis were analyzed through univariate and multivariate analysis.The importance of each variable was ranked using the random forest algorithm to establish a predictive model for early postoperative acute pain.
      Results The incidence rate of acute pain in elderly patients with knee osteoarthritis after surgery was 61.42%(121/197).The differences of the degree of preoperative articular cartilage injury, postoperative quadriceps function exercises, postoperative PCIA, addition of analgesic drugs, age, preoperative pain level during activity, preoperative knee function(KSS) score, fearful visual analog scale(FAVS), pain catastrophizing scale(PCS), and total score of the hospital anxiety and depression scale(HADS) were statistically significant between two groups(P < 0.05 to P < 0.01).The postoperative quadriceps function exercise(OR=0.357, P < 0.01), postoperative PCIA(OR=0.261, P < 0.01) and addition of analgesic drugs(OR=0.430, P < 0.01) were the protective factors for early postoperative acute pain in elderly patients with knee osteoarthritis.The preoperative joint cartilage injury severity(OR=5.607, P < 0.01), age(OR=4.555, P < 0.01), FAVS(OR=5.214, P < 0.01), PCS(OR=4.138, P < 0.01) and total HADS score(OR=6.798, P < 0.01) were the risk factors for acute pain.Based on logistic regression analysis, a random forest model was constructed to predict the risk of early postoperative acute pain in elderly patients with knee osteoarthritis.The area under the ROC curve was 0.892, the sensitivity was 77.27%, and the specificity was 88.89%.
      Conclusions The postoperative quadriceps function exercises, postoperative PCIA, addition of analgesic drugs, degree of preoperative articular cartilage injury, age, FAVS, PCS, and HADS total score are the influencing factors of early postoperative acute pain in elderly patients with knee osteoarthritis.Constructing a predictive model for prediction and importance analysis is beneficial for guiding the precise implementation of prevention and control measures in clinical practice.

       

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