营养状况联合临床资料构建的预测模型在胃癌根治术后感染性并发症中的应用价值

Application value of constructing a prediction model based on nutritional status combined with clinical data for infectious complications after radical gastrectomy for gastric cancer

  • 摘要: 目的 探讨营养状况联合临床资料构建预测模型在胃癌根治术后感染性并发症的应用价值。方法 回顾性收集2017年1月—2024年7月在苏州大学附属苏州九院行胃癌根治术的394例胃癌患者的临床资料。依据患者术后是否发生感染将患者分为感染组(n=73)和非感染组(n=321)。采用最小绝对收缩和选择算子(LASSO)法获取与胃癌根治术后感染性并发症的最佳相关特征,采用多因素Logistic回归分析筛选胃癌根治术后感染性并发症的危险因素。采用R软件随机抽取70%的数据作为训练集(建立列线图模型), 30%的数据作为测试集。采用受试者工作特征(ROC)曲线的曲线下面积(AUC)、Bootstrap法抽样验证、决策分析曲线(DCA)评估预测模型的价值。结果 394例胃癌患者中, 73例术后发生感染性并发症,其中肺部感染患者占比为53.42%, 腹腔感染患者占比17.81%, 泌尿系统感染患者占比16.44%, 切口感染患者占比12.33%。年龄、合并糖尿病、术前有营养风险、术前PIV高、联合脏器切除、手术时间长均是胃癌根治术后感染性并发症的危险因素(P<0.05)。训练集中, 列线图模型的AUC为0.898, 测试集验证得到AUC为0.891。经Bootstrap法通过1 000次抽样验证表明,模型在训练集和测试集中的预测概率与实际值的平均误差分别为0.019、0.024。DCA结果表明,模型具有临床实用价值。结论 胃癌术后感染性并发症发生率高,基于营养评估联合临床资料构建的预测模型在预测胃癌术后感染性并发症风险方面有较高的价值。

     

    Abstract: Objective To explore the application value of predictive model based on nutritional status combined with clinical data in infectious complications after radical gastrectomy for gastric cancer. Methods The clinical data on 394 gastric cancer patients who underwent radical gastrectomy at Suzhou Ninth Hospital Affiliated to Soochow University from January 2017 to July 2024 were retrospectively collected. According to whether the patients developed infection after surgery, they were divided into infection group (n=73) and non-infection group (n=321) based on whether they developed postoperative infections or not. The least absolute shrinkage and selection operator (LASSO) method was used to obtain the optimal related features associated with infectious complications after radical gastrectomy for gastric cancer. Multivariate Logistic regression analysis was conducted to screen for risk factors of infectious complications after radical gastrectomy. R software was used to randomly select 70% of data as training set (for establishing the nomogram model) and 30% of data as test set. The area under the curve (AUC) of the receiver operating characteristic (ROC) curve, Bootstrap sampling validation, and decision curve analysis (DCA) were used to assess the value of the predictive model. Results of the 394 gastric cancer patients, 73 developed postoperative infectious complications, including 53.42% with lung infections, 17.81% with intra-abdominal infections, 16.44% with urinary tract infections, and 12.33% with wound infections. Age, diabetes mellitus, preoperative nutritional risk, high preoperative PIV, combined organ resection, and prolonged operation time were identified as risk factors for infectious complications after radical gastrectomy (P<0.05). In the training set, the AUC of the nomogram model was 0.898, and the AUC validated in the test set was 0.891. Bootstrap sampling validation with 1, 000 iterations showed that the average errors between the predicted probabilities and actual values in the training and test sets were 0.019 and 0.024, respectively. DCA results indicated that the model had clinical utility. Conclusion Infectious complications after gastrectomy for gastric cancer are common, and the predictive model based on nutritional assessment combined with clinical data has high value in predicting the risk of infectious complications after gastrectomy.

     

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