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Trial Title:
Validation of a Model for Predicting Anastomotic Leakage
NCT ID:
NCT05646290
Condition:
Gastric Cancer
Conditions: Official terms:
Anastomotic Leak
Conditions: Keywords:
machine learning
anastomotic leakage
total and proximal gastrectomy
Study type:
Observational
Overall status:
Recruiting
Study design:
Time perspective:
Prospective
Summary:
This study will validate a machine learning model for predicting anastomotic leakage of
esophagogastrostomy and esophagojejunostomy.
Detailed description:
Anastomotic leakage is a fatal complication after total and proximal gastrectomy in
gastric cancer patients. Identifying patients with high-risk of AL is important for
guiding the surgeons' decision making, such as a more rigorous anastomotic operation，
placing a jejunal feeding tube and dual-lumen flushable drainage catheter. We have
developed a high-performance machine learning model based on 1660 gastric cancer
patients, which showed good discrimination of anastomotic leakage. Hence, this
multi-center prospective study will validiate the usability of the model for predicting
anastomotic leakage in gastric cancer patients who receive total and proximal
gastrectomy.
Criteria for eligibility:
Study pop:
Gastric cancer patients undergoing total or proximal gastrectomy in five medical centers
(Tongji Hospital, Wuhan No. 1 Hospital, Xianning Central Hospital, Huanggang Central
Hospital and Jingzhou Central Hospital) are included in this perspective study.
Sampling method:
Non-Probability Sample
Criteria:
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
Gender:
All
Minimum age:
18 Years
Maximum age:
85 Years
Healthy volunteers:
No
Locations:
Facility:
Name:
Tongji Hospital, Tongji Medical College, Huazhong University of Science & Technology
Address:
City:
Wuhan
Zip:
430030
Country:
China
Status:
Recruiting
Contact:
Last name:
Jichao Qin, M.D./Ph.D
Phone:
+86-27-83665316
Email:
jcqin@tjh.tjmu.edu.cn
Start date:
January 6, 2022
Completion date:
April 6, 2024
Lead sponsor:
Agency:
Jichao Qin
Agency class:
Other
Source:
Tongji Hospital
Record processing date:
ClinicalTrials.gov processed this data on November 12, 2024
Source: ClinicalTrials.gov page:
https://clinicaltrials.gov/ct2/show/NCT05646290
