建立内镜逆行胰胆管造影术术前胃潴留的预测模型和决定因素。

IF 1.8 4区 医学 Q3 GASTROENTEROLOGY & HEPATOLOGY
Ying Jia, Hao-Jun Wu, Tang Li, Jia-Bin Liu, Ling Fang, Zi-Ming Liu
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引用次数: 0

摘要

背景:研究内镜逆行胰胆管造影术(ERCP)术前胃潴留的影响因素背景:随着ERCP的广泛应用,术前胃潴留的风险影响着手术的顺利进行。研究发现,女性、胆道及胰腺恶性肿瘤、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手术风险十分重要:方法:对2020年1月至2024年2月期间我院收治的190例ERCP准备患者进行回顾性分析。通过电子病历系统收集患者的基线临床数据。以 1:4 的比例随机匹配同期 190 名患者的数据,建立验证组(38 人)和建模组(152 人)。根据术前是否发生胃潴留,将模型组患者分为胃潴留组(n = 52)和非胃潴留组(n = 100)。比较验证组和建模组患者的一般数据。进行单变量和多变量逻辑回归分析,以确定ERCP患者术前胃潴留的影响因素。构建了ERCP患者术前胃潴留的预测模型,并使用校准曲线进行验证。通过分析接收者操作特征曲线(ROC)来评估模型的预测价值:我们发现验证组与建模组的一般数据差异无统计学意义(P>0.05)。两组之间年龄、体重指数、高血压和糖尿病的比较也没有发现明显的统计学差异(P>0.05)。不过,我们注意到两组患者在性别、原发病、黄疸、阿片类药物使用和胃肠道梗阻方面存在显著统计学差异(P 0.05)。多变量逻辑回归分析显示,性别、原发疾病、黄疸、阿片类药物使用和胃肠道梗阻是影响 ERCP 患者术前胃潴留的独立因素(P 0.05)。逻辑回归分析结果显示,性别、原发疾病、黄疸、阿片类药物使用和胃肠道梗阻被纳入 ERCP 患者术前胃潴留的预测模型。训练集和验证集的校准曲线显示斜率接近于1,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,在训练集中,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(95%CI:0.8264-0.9567),最佳临界值为 0.71,灵敏度为 87.5,特异度为 84.2。在验证组中,预测模型的 AUC 为 0.842,标准误差为 0.013(95%CI:0.8061-0.9216),最佳临界值为 0.56,灵敏度为 56.2,特异性为 100.0:性别、原发疾病、黄疸、阿片类药物使用和胃肠道梗阻是ERCP患者术前胃潴留的影响因素。根据这些因素建立的预测模型具有很高的预测价值。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Establishment of predictive models and determinants of preoperative gastric retention in endoscopic retrograde cholangiopancreatography.

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.

Aim: 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.

Conclusion: 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.

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