背景:内镜逆行胰胆管造影术(ERCP)前胃潴留影响因素研究背景:随着ERCP的广泛应用,术前胃潴留的风险影响手术的顺利进行。研究发现,女性,胆胰腺恶性肿瘤,消化道梗阻等因素与胃潴留密切相关,因此,建立预测模型对降低运营风险至关重要。
目的:分析ERCP术前胃潴留的影响因素并建立预测模型。
方法:对2020年1月至2024年2月我院收治的190例ERCP准备患者进行回顾性分析。使用电子病历系统收集患者基线临床数据。患者以1:4的比例与同期190名患者的数据进行随机匹配,以建立验证组(n=38)和建模组(n=152)。根据术前是否发生胃潴留,将模型组患者分为胃潴留组(52例)和非胃潴留组(100例)。比较验证组和模型组患者的一般资料。进行单因素和多因素logistic回归分析,以确定影响ERCP患者术前胃潴留的因素。建立ERCP患者术前胃潴留的预测模型,和校准曲线用于验证。分析受试者工作特征(ROC)曲线以评估模型的预测值。
结果:我们发现验证组和模型组的一般数据无统计学差异(P>0.05)。年龄的比较,身体质量指数,高血压,两组间比较差异无统计学意义(P>0.05)。然而,我们注意到性别的统计学差异,原发疾病,黄疸,阿片类药物的使用,两组间胃肠道梗阻情况比较(P<0.05)。多因素logistic回归分析显示,性别,原发疾病,黄疸,阿片类药物的使用,胃肠道梗阻是影响ERCP患者术前胃潴留的独立因素(P<0.05)。Logistic回归分析结果显示,性别、原发疾病,黄疸,阿片类药物的使用,和胃肠道梗阻被纳入ERCP患者术前胃潴留的预测模型。训练集和验证集中的校准曲线显示接近1的斜率,表明预测风险和实际风险之间具有良好的一致性。ROC分析结果显示,训练集中ERCP患者术前胃潴留预测模型的曲线下面积(AUC)为0.901,标准误差为0.023(95CI:0.8264-0.9567),最佳截断值为0.71,敏感性为87.5,特异性为84.2。在验证集中,预测模型的AUC为0.842,标准误差为0.013(95CI:0.8061-0.9216),最佳截断值为0.56,敏感性为56.2,特异性为100.0。
结论:性别,原发疾病,黄疸,阿片类药物的使用,胃肠道梗阻是影响ERCP患者术前胃潴留的因素。基于这些因素建立的预测模型具有较高的预测价值。
BACKGROUND: Study on influencing factors of gastric retention before endoscopic retrograde cholangiopancreatography (ERCP) background: With the wide application of ERCP, the risk of preoperative gastric retention affects the smooth progress of the operation. The study found that female, biliary and pancreatic malignant tumor, digestive tract obstruction and other factors are closely related to gastric retention, so the establishment of predictive model is very important to reduce the risk of operation.
OBJECTIVE: To analyze the factors influencing preoperative gastric retention in ERCP and establish a predictive model.
METHODS: A retrospective analysis was conducted on 190 patients admitted to our hospital for ERCP preparation between January 2020 and February 2024. Patient baseline clinical data were collected using an electronic medical record system. Patients were randomly matched in a 1:4 ratio with data from 190 patients during the same period to establish a validation group (n = 38) and a modeling group (n = 152). Patients in the modeling group were divided into the gastric retention group (n = 52) and non-gastric retention group (n = 100) based on whether gastric retention occurred preoperatively. General data of patients in the validation group and modeling group were compared. Univariate and multivariate logistic regression analyses were performed to identify factors influencing preoperative gastric retention in ERCP patients. A predictive model for preoperative gastric retention in ERCP patients was constructed, and calibration curves were used for validation. The receiver operating characteristic (ROC) curve was analyzed to evaluate the predictive value of the model.
RESULTS: We found no statistically significant difference in general data between the validation group and modeling group (P > 0.05). The comparison of age, body mass index, hypertension, and diabetes between the two groups showed no statistically significant difference (P > 0.05). However, we noted statistically significant differences in gender, primary disease, jaundice, opioid use, and gastrointestinal obstruction between the two groups (P < 0.05). Multivariate logistic regression analysis showed that gender, primary disease, jaundice, opioid use, and gastrointestinal obstruction were independent factors influencing preoperative gastric retention in ERCP patients (P < 0.05). The results of logistic regression analysis revealed that gender, primary disease, jaundice, opioid use, and gastrointestinal obstruction were included in the predictive model for preoperative gastric retention in ERCP patients. The calibration curves in the training set and validation set showed a slope close to 1, indicating good consistency between the predicted risk and actual risk. The ROC analysis results showed that the area under the curve (AUC) of the predictive model for preoperative gastric retention in ERCP patients in the training set was 0.901 with a standard error of 0.023 (95%CI: 0.8264-0.9567), and the optimal cutoff value was 0.71, with a sensitivity of 87.5 and specificity of 84.2. In the validation set, the AUC of the predictive model was 0.842 with a standard error of 0.013 (95%CI: 0.8061-0.9216), and the optimal cutoff value was 0.56, with a sensitivity of 56.2 and specificity of 100.0.
CONCLUSIONS: Gender, primary disease, jaundice, opioid use, and gastrointestinal obstruction are factors influencing preoperative gastric retention in ERCP patients. A predictive model established based on these factors has high predictive value.