Gastric Cancer Clinical Trial
Official title:
Validation of a Machine Learning Model for Predicting Anastomotic Leakage of Esophagogastrostomy and Esophagojejunostomy: A Multicenter Prospective Study
This study will validate a machine learning model for predicting anastomotic leakage of esophagogastrostomy and esophagojejunostomy.
Status | Recruiting |
Enrollment | 880 |
Est. completion date | April 6, 2024 |
Est. primary completion date | January 6, 2024 |
Accepts healthy volunteers | No |
Gender | All |
Age group | 18 Years to 85 Years |
Eligibility | Inclusion Criteria: Inclusion Criteria: 1. Aged older than 18 years and younger than 85 years. 2. Primary gastric adenocarcinoma confirmed by preoperative pathology. 3. Expected curative resection via total or proximal gastrectomy. 4. American Society of Anesthesiologists (ASA) class I, II, or III. 5. 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 |
Country | Name | City | State |
---|---|---|---|
China | Tongji Hospital, Tongji Medical College, Huazhong University of Science & Technology | Wuhan | Hubei |
Lead Sponsor | Collaborator |
---|---|
Jichao Qin |
China,
Type | Measure | Description | Time frame | Safety issue |
---|---|---|---|---|
Primary | Incidence of anastomotic leakage | Within 30 days after operation |
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