PDF(Pubmed)
Abstract：
BACKGROUND: Incarceration occurred in approximately 5% to 15% of inguinal hernia patients, with around 15% of incarcerated cases progressing to intestinal necrosis, necessitating bowel resection surgery. Patients with intestinal necrosis had significantly higher mortality and complication rates compared to those without necrosis.The primary objective of this study was to design and validate a diagnostic model capable of predicting intestinal necrosis in patients with incarcerated groin hernias.
METHODS: We screened the clinical records of patients who underwent emergency surgery for incarcerated inguinal hernia between January 1, 2015, and December 31, 2022. To ensure balanced representation, the enrolled patients were randomly divided into a training set (n = 180) and a validation set (n = 76) using a 2:1 ratio. Logistic regression analysis was conducted using the rms package in R software, incorporating selected features from the LASSO regression model, to construct a predictive model.
RESULTS: Based on the results of the LASSO regression analysis, a multivariate logistic regression model was developed to establish the predictive model. The predictors included in the model were Abdominal effusion, Hernia Sac Effusion, and Procalcitonin. The area under the receiver operating characteristic (ROC) curve for the nomogram graph in the training set was 0.977 (95% CI = 0.957-0.992). In the validation set, the AUC for the nomogram graph was 0.970. Calibration curve and decision curve analysis (DCA) verified the accuracy and practicability of the nomogram graph in our study.
CONCLUSIONS: Bowel necrosis in patients with incarcerated inguinal hernia was influenced by multiple factors. The nomogram predictive model constructed in this study could be utilized to predict and differentiate whether incarcerated inguinal hernia patients were at risk of developing bowel necrosis.
METHODS: We screened the clinical records of patients who underwent emergency surgery for incarcerated inguinal hernia between January 1, 2015, and December 31, 2022. To ensure balanced representation, the enrolled patients were randomly divided into a training set (n = 180) and a validation set (n = 76) using a 2:1 ratio. Logistic regression analysis was conducted using the rms package in R software, incorporating selected features from the LASSO regression model, to construct a predictive model.
RESULTS: Based on the results of the LASSO regression analysis, a multivariate logistic regression model was developed to establish the predictive model. The predictors included in the model were Abdominal effusion, Hernia Sac Effusion, and Procalcitonin. The area under the receiver operating characteristic (ROC) curve for the nomogram graph in the training set was 0.977 (95% CI = 0.957-0.992). In the validation set, the AUC for the nomogram graph was 0.970. Calibration curve and decision curve analysis (DCA) verified the accuracy and practicability of the nomogram graph in our study.
CONCLUSIONS: Bowel necrosis in patients with incarcerated inguinal hernia was influenced by multiple factors. The nomogram predictive model constructed in this study could be utilized to predict and differentiate whether incarcerated inguinal hernia patients were at risk of developing bowel necrosis.
摘要：
背景：大约5％至15％的腹股沟疝患者发生嵌顿，大约15%的嵌顿病例进展为肠坏死，需要肠切除手术。肠坏死患者的死亡率和并发症发生率明显高于无坏死患者。这项研究的主要目的是设计和验证能够预测腹股沟嵌顿疝患者肠坏死的诊断模型。
方法：我们筛选了2015年1月1日至2022年12月31日期间因腹股沟嵌顿疝接受急诊手术的患者的临床记录。为了确保均衡的代表性，将纳入的患者按照2:1的比例随机分为训练集(n=180)和验证集(n=76).使用R软件中的均方根软件包进行Logistic回归分析，结合LASSO回归模型中的选定特征，构建预测模型。
结果：根据LASSO回归分析的结果，建立多变量逻辑回归模型，建立预测模型。模型中包括的预测因素是腹腔积液，疝囊积液,和降钙素原.训练集中列线图的受试者工作特征（ROC）曲线下面积为0.977（95％CI=0.957-0.992）。在验证集中，列线图的AUC为0.970.校准曲线和决策曲线分析（DCA）验证了列线图在我们研究中的准确性和实用性。
结论：嵌顿性腹股沟疝患者肠坏死受多种因素影响。本研究建立的列线图预测模型可用于预测和区分嵌顿腹股沟疝患者是否有发生肠坏死的风险。
方法：我们筛选了2015年1月1日至2022年12月31日期间因腹股沟嵌顿疝接受急诊手术的患者的临床记录。为了确保均衡的代表性，将纳入的患者按照2:1的比例随机分为训练集(n=180)和验证集(n=76).使用R软件中的均方根软件包进行Logistic回归分析，结合LASSO回归模型中的选定特征，构建预测模型。
结果：根据LASSO回归分析的结果，建立多变量逻辑回归模型，建立预测模型。模型中包括的预测因素是腹腔积液，疝囊积液,和降钙素原.训练集中列线图的受试者工作特征（ROC）曲线下面积为0.977（95％CI=0.957-0.992）。在验证集中，列线图的AUC为0.970.校准曲线和决策曲线分析（DCA）验证了列线图在我们研究中的准确性和实用性。
结论：嵌顿性腹股沟疝患者肠坏死受多种因素影响。本研究建立的列线图预测模型可用于预测和区分嵌顿腹股沟疝患者是否有发生肠坏死的风险。
