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Background <p>Post-endoscopic submucosal dissection electrocoagulation syndrome (PEECS) is one of the postoperative adverse events of endoscopic resection, but the incidence and risk factors of PEECS after endoscopic full-thickness resection (EFTR) are still unclear. The purpose of this study was to identify risk factors and develop a predictive nomogram for PEECS after gastric EFTR.</p> Materials and methods <p>Multivariate logistic regression was used to analyze the risk factors of electrocoagulation syndrome after gastric EFTR. A prediction nomogram was developed based on the above results, and bootstrap was employed for internal validation of the model.</p> Results <p>507 patients who underwent gastric EFTR were included, and the incidence of PEECS was 9.9%. Multivariate analysis showed that tumor size ≥ 10 mm, hot biopsy forceps for hemostasis, and operation time were independent risk factors of PEECS. A nomogram based on these risk factors showed good predictive ability, and the area under the ROC curve (AUC) was 0.769 (95% CI: 0.700–0.838). The calibration curve of the predictive model also demonstrated a good fit.</p> Conclusion <p>This study developed a predictive nomogram based on tumor size, hemostasis method, and operation time, which was used to identify high-risk patients with electrocoagulation syndrome after gastric EFTR.</p>

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Development and validation of a model for predicting electrocoagulation syndrome after endoscopic full-thickness resection of gastric tumors

  • 期刊论文

  • 发表日期：

    2025年3月28日

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  • Foqiang Liao,
  • Jie Liang,
  • Yunfeng Huang,
  • Jianfang Rong,
  • Zhenhua Zhu,
  • Xiaolin Pan,
  • Chong Wang,
  • Shunhua Long,
  • Xiaojiang Zhou,
  • Guohua Li,
  • Yin Zhu,
  • Youxiang Chen,
  • Xu Shu

摘要

Background

Post-endoscopic submucosal dissection electrocoagulation syndrome (PEECS) is one of the postoperative adverse events of endoscopic resection, but the incidence and risk factors of PEECS after endoscopic full-thickness resection (EFTR) are still unclear. The purpose of this study was to identify risk factors and develop a predictive nomogram for PEECS after gastric EFTR.

Materials and methods

Multivariate logistic regression was used to analyze the risk factors of electrocoagulation syndrome after gastric EFTR. A prediction nomogram was developed based on the above results, and bootstrap was employed for internal validation of the model.

Results

507 patients who underwent gastric EFTR were included, and the incidence of PEECS was 9.9%. Multivariate analysis showed that tumor size ≥ 10 mm, hot biopsy forceps for hemostasis, and operation time were independent risk factors of PEECS. A nomogram based on these risk factors showed good predictive ability, and the area under the ROC curve (AUC) was 0.769 (95% CI: 0.700–0.838). The calibration curve of the predictive model also demonstrated a good fit.

Conclusion

This study developed a predictive nomogram based on tumor size, hemostasis method, and operation time, which was used to identify high-risk patients with electrocoagulation syndrome after gastric EFTR.