Validation of a Model for Predicting Duodenal Stump Leakage After Gastrectomy

Gastrectomy is an essential procedure in radical surgery for gastric cancer. Duodenal stump leakage (DSL) is one of the critical short-term complications after distal and total gastrectomy in gastric cancer patients. Identifying patients with high-risk of DSL will assist the surgeons' decision making to give efficient previous intervention, such as a more rigorous operation, placing dual-lumen flushable drainage catheter and decompression tube in afferent loop. Investigators have developed a high-performance machine learning model based on 4070 gastric cancer patients, which showed good discrimination of DSL. Hence, this multi-center prospective study will validate the reliability of this model for predicting DSL in gastric cancer patients who receive laparoscopic distal or total gastrectomy.

Inclusion criteria

• Aged older than 18 years and younger than 85 years
• Primary gastric carcinoma confirmed by preoperative pathology result
• Expected curative resection via laparoscopic distal or total gastrectomy and reconstruction via Billroth-II or Roux-en-Y anastomosis
• American Society of Anesthesiologists (ASA) class I, II, or III
• With full documents of preoperative examinations such as blood test and abdominal CT scanning
• Written informed consent

Exclusion criteria

• Pregnant or breastfeeding women.
• Severe mental disorder or language communication disorder.
• Other surgical procedures of gastrectomy is performed.
• Interrupted of surgery for more than 30 minutes due to any cause.
• Malignant tumors with other organs
• Performed gastrectomy in the past