Lu Yi, Zhuo Xianhua, Zhong Qinghua, Sun Jiachen, Li Chujun, Zhi Min
Department of Gastrointestinal Endoscopy, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.
Guangdong Provincial Key Laboratory of Colorectal and Pelvic Floor Diseases, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.
Ultrasonography. 2023 Jan;42(1):78-88. doi: 10.14366/usg.21265. Epub 2022 Jul 17.
Models for predicting perforation during endoscopic resection (ER) of gastric submucosal tumors (SMTs) originating from the muscularis propria (MP) are rare. Therefore, this study was conducted to determine important parameters in endoscopic ultrasonography (EUS) images to predict perforation and to build predictive models.
Consecutive patients with gastric SMTs originating from the MP who received ER from May 1, 2013 to January 15, 2021 were retrospectively reviewed. They were classified into case and control groups based on the presence of perforation. Logistic multivariate analysis was used to identify potential variables and build predictive models (models 1 and 2: with and without information on tumor pathology, respectively).
In total, 199 EUS procedures (194 patients) were finally chosen, with 99 procedures in the case group and 100 in the control group. The ratio of the inner distance to the outer distance (I/O ratio) was significantly larger in the case group than in the control group (median ratio, 2.20 vs. 1.53; P<0.001). Multivariate analysis showed that age (odds ratio [OR], 1.036 in model 1; OR, 1.046 in model 2), the I/O ratio (OR, 2.731 in model 1; OR, 2.372 in model 2), and the pathology of the tumors (OR, 10.977 for gastrointestinal stromal tumors; OR, 15.051 for others in model 1) were risk factors for perforation. The two models to predict perforation had areas under the curve of 0.836 (model 1) and 0.755 (model 2).
EUS was useful in predicting perforation in ER for gastric SMTs originating from the MP. Two predictive models were developed.
源自固有肌层（MP）的胃黏膜下肿瘤（SMT）内镜切除（ER）术中预测穿孔的模型少见。因此，本研究旨在确定内镜超声（EUS）图像中预测穿孔的重要参数并建立预测模型。
回顾性分析2013年5月1日至2021年1月15日期间接受ER治疗的连续的源自MP的胃SMT患者。根据是否发生穿孔将患者分为病例组和对照组。采用多因素logistic分析确定潜在变量并建立预测模型（模型1和模型2：分别包含和不包含肿瘤病理信息）。
最终纳入199例EUS手术（194例患者），其中病例组99例，对照组100例。病例组内距与外距之比（I/O比）显著高于对照组（中位数比，2.20对1.53；P<0.001）。多因素分析显示，年龄（模型1中比值比[OR]为1.036；模型2中OR为1.046）、I/O比（模型1中OR为2.731；模型2中OR为2.372）和肿瘤病理（模型1中胃肠道间质瘤的OR为10.977；其他肿瘤的OR为15.051）是穿孔的危险因素。预测穿孔的两个模型的曲线下面积分别为0.836（模型1）和0.755（模型2）。
EUS有助于预测源自MP的胃SMT的ER术中穿孔。建立了两个预测模型。
