谈俊, 李睿. 基于中医因素参与的肛周脓肿术后创面愈合质量的风险预测模型的构建[J]. 蚌埠医科大学学报, 2023, 48(9): 1325-1329. DOI: 10.13898/j.cnki.issn.1000-2200.2023.033
    引用本文: 谈俊, 李睿. 基于中医因素参与的肛周脓肿术后创面愈合质量的风险预测模型的构建[J]. 蚌埠医科大学学报, 2023, 48(9): 1325-1329. DOI: 10.13898/j.cnki.issn.1000-2200.2023.033
    TAN Jun, LI Rui. Construction of a risk prediction model for postoperative wound healing quality of perianal abscess based on Chinese medicine factors[J]. Journal of Bengbu Medical University, 2023, 48(9): 1325-1329. DOI: 10.13898/j.cnki.issn.1000-2200.2023.033
    Citation: TAN Jun, LI Rui. Construction of a risk prediction model for postoperative wound healing quality of perianal abscess based on Chinese medicine factors[J]. Journal of Bengbu Medical University, 2023, 48(9): 1325-1329. DOI: 10.13898/j.cnki.issn.1000-2200.2023.033

    基于中医因素参与的肛周脓肿术后创面愈合质量的风险预测模型的构建

    Construction of a risk prediction model for postoperative wound healing quality of perianal abscess based on Chinese medicine factors

    • 摘要:
      目的探讨肛周脓肿术后创面愈合不良的危险因素,并构建肛周脓肿术后创面愈合不良的列线图模型。
      方法选取行手术治疗的300例肛周脓肿病人作为研究对象。运用单因素分析初步筛选肛周脓肿术后创面愈合不良的影响因素,运用lasso分析筛选肛周脓肿术后创面愈合不良的预测因子,运用logistic回归分析筛选肛周脓肿术后创面愈合不良的危险因素,并建立肛周脓肿术后创面愈合不良的列线图模型。
      结果300例肛周脓肿病人中有71例病人术后创面愈合不良,创面愈合不良的发生率为23.67%(71/300)。愈合不良组和愈合良好组年龄、性别、居住地、受教育程度、饮酒、手术方式、手术切口、手术时间、日均坐浴时间、恢复正常活动时间、高血脂、高血压、热毒蕴结型及火毒炽盛型等差异均无统计学意义(P>0.05),而吸烟、创面引流不畅、糖尿病、体质量指数(BMI)、术后便秘、术后感染及阴虚毒恋型等差异均有统计学意义(P<0.01)。lasso回归分析结果显示,吸烟、创面引流不畅、糖尿病、BMI、术后便秘、术后感染及中医证型等是系数不为零的预测因素。logistic回归分析结果显示,吸烟、创面引流不畅、糖尿病、BMI<18.5 kg/m2、术后便秘、术后感染及阴虚毒恋型肛周脓肿等是肛周脓肿术后创面愈合不良的危险因素(P<0.05~P<0.01)。列线图模型结果显示,模型一致性指数为0.746(95%CI:0.711~0.781);校正曲线与理想曲线拟合度比较良好;受试者工作特征曲线下面积为0.728,灵敏度为81.25%,特异度为79.83%;决策曲线显示阈值概率在10%~81%范围内时,采用该列线图预测肛周脓肿术后创面愈合不良具有较高的净获益值。
      结论列线图模型可有效预测肛周脓肿术后创面愈合不良的发生,可对创面愈合不良高风险病人的筛查和相关防治措施的制定起到积极的帮助作用。

       

      Abstract:
      ObjectiveTo investigate the risk factors of poor wound healing after perianal abscess surgery, and construct a nomogram model of poor wound healing after perianal abscess surgery.
      MethodsThree hundred patients with perianal abscess were selected as the study subjects.The single factor analysis was used to preliminarily screen the influencing factors of poor wound healing, the lasso analysis was used to screen the predictive factors of poor wound healing, and the logistic regression analysis was used to screen the risk factors of poor wound healing after perianal abscess surgery.The nomograph model of poor wound healing after perianal abscess surgery was established.
      ResultsAmong 300 patients with perianal abscess, the poor wound healing in 71 patients after surgery were found.The incidence rate of poor wound healing was 23.67%(71/300).There was no statistical significances in the age, sex, residence, education level, alcohol consumption, operation method, surgical incision, operation time, average daily sitting bath time, recovery time of normal activities, hyperlipidemia, hypertension, heat poison accumulation type and fire poison incandescent type(P>0.05), but there were statistically significant in smoking, poor wound drainage, diabetes, body mass index (BMI), postoperative constipation, postoperative infection, and Yin-deficiency and poison love type between poor healing group and good healing group (P<0.01).The results of lasso regression analysis showed that the smoking, poor wound drainage, diabetes, BMI, postoperative constipation, postoperative infection and TCM syndrome types were the predictors of non-zero coefficients.The results of logistic regression analysis showed that the smoking, poor wound drainage, diabetes, BMI less than 18.5 kg/m2, postoperative constipation, postoperative infection and perianal abscess of Yin-deficiency and toxin love type were the risk factors of poor wound healing after perianal abscess surgery (P<0.05 to P<0.01).The results of the nomograph model show that the model consistency index was 0.746 (95%CI: 0.711-0.781).The fitting degree between the correction curve and ideal curve was good.The area under the reciever operating characteristic curve was 0.728, the sensitivity was 81.25%, and the specificity was 79.83%.When the decision curve showed that the threshold probability was within the range of 10%-81%, the nomograph had a higher net benefit value in predicting the poor wound healing after perianal abscess surgery.
      ConclusionsThe nomogram model can effectively predict the occurrence of poor wound healing after perianal abscess surgery, and can play a positive role in screening high-risk patients with poor wound healing and formulating relevant prevention and treatment measures.

       

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