This study aims to validate a machine learning model for predicting duodenal stump leakage after laparoscopic radical gastrectomy for gastric cancer.
Eligibility
Sex
ALL
Min age
18 Years
Max age
85 Years
Healthy volunteers
No
Inclusion Criteria:
1. Aged older than 18 years and younger than 85 years
2. Primary gastric carcinoma confirmed by preoperative pathology result
3. Expected curative resection via laparoscopic distal or total gastrectomy and reconstruction via Billroth-II or Roux-en-Y anastomosis
4. American Society of Anesthesiologists (ASA) class I, II, or III
5. With full documents of preoperative examinations such as blood test and abdominal CT scanning
6. Written informed consent
Exclusion Criteria:
1. Pregnant or breastfeeding women.
2. Severe mental disorder or language communication disorder.
3. Other surgical procedures of gastrectomy is performed.
4. Interrupted of surgery for more than 30 minutes due to any cause.
5. Malignant tumors with other organs
6. Performed gastrectomy in the past
Primary outcome measure(s)
Incidence of duodenal stump leakage — Within 30 days after operation
Trial sites (1)
Facility
City
Region
Status
Department of Gastrointestinal Surgery, The First Affiliated Hospital, Zhejiang University School of Medicine
This page summarises publicly available registry data for informational purposes — not medical advice. Eligibility is determined by each study team; patients should discuss participation with their clinician.
We use cookies to analyse site traffic and improve your experience. With your consent, we may also use cookies for advertising. You can change your choice at any time on our Cookie Policy page. See also our Privacy Policy.