Validation of a Model for Predicting Duodenal Stump Leakage After Gastrectomy

NCT ID: NCT06807372

Last Updated: 2025-02-06

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

Get a concise snapshot of the trial, including recruitment status, study phase, enrollment targets, and key timeline milestones.

Recruitment Status

ACTIVE_NOT_RECRUITING

Total Enrollment

1200 participants

Study Classification

OBSERVATIONAL

Study Start Date

2024-09-11

Study Completion Date

2026-12-31

Brief Summary

Review the sponsor-provided synopsis that highlights what the study is about and why it is being conducted.

This study aims to validate a machine learning model for predicting duodenal stump leakage after laparoscopic radical gastrectomy for gastric cancer.

Detailed Description

Dive into the extended narrative that explains the scientific background, objectives, and procedures in greater depth.

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.

Conditions

See the medical conditions and disease areas that this research is targeting or investigating.

Gastric Cancers

Study Design

Understand how the trial is structured, including allocation methods, masking strategies, primary purpose, and other design elements.

Observational Model Type

COHORT

Study Time Perspective

PROSPECTIVE

Eligibility Criteria

Check the participation requirements, including inclusion and exclusion rules, age limits, and whether healthy volunteers are accepted.

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
Minimum Eligible Age

18 Years

Maximum Eligible Age

85 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

No

Sponsors

Meet the organizations funding or collaborating on the study and learn about their roles.

Second Affiliated Hospital, School of Medicine, Zhejiang University

OTHER

Sponsor Role collaborator

Jinhua Central Hospital

OTHER

Sponsor Role collaborator

Jichao Qin

OTHER

Sponsor Role lead

Responsible Party

Identify the individual or organization who holds primary responsibility for the study information submitted to regulators.

Jichao Qin

Professor

Responsibility Role SPONSOR_INVESTIGATOR

Locations

Explore where the study is taking place and check the recruitment status at each participating site.

Department of Gastrointestinal Surgery, The First Affiliated Hospital, Zhejiang University School of Medicine

Hangzhou, Zhejiang, China

Site Status

Countries

Review the countries where the study has at least one active or historical site.

China

Other Identifiers

Review additional registry numbers or institutional identifiers associated with this trial.

2024-0856

Identifier Type: -

Identifier Source: org_study_id

More Related Trials

Additional clinical trials that may be relevant based on similarity analysis.