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Development and Validation of a Machine Learning Model for Predicting Laparotomy Time and Blood Loss During Radical Gastrectomy for Gastric Cancer

Development and Validation of a Machine Learning Model for Predicting Dissection Time and Blood Loss During Laparoscopic Radical Gastrectomy for Gastric Cancer

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2600124117
Enrollment
Unknown
Registered
2026-05-07
Start date
2026-05-07
Completion date
Unknown
Last updated
2026-05-11

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Gastric cancer

Interventions

Observation group:None

Sponsors

The first affiliated hostipal of nanchang university
Lead Sponsor

Eligibility

Sex/Gender
All
Age
18 Years to 80 Years

Inclusion criteria

Inclusion criteria: 1. Patients must have a pathologically confirmed diagnosis of gastric cancer and have undergone elective laparoscopic radical gastrectomy. 2. Complete data: Preoperative clinical data (general information, tumor markers, imaging reports) and intraoperative records (time to tumor dissection, blood loss) must be available in full. 3. The study includes adult patients (aged 18-80 years) to cover the typical surgical population.

Exclusion criteria

Exclusion criteria: 1. Patients with severe cardiac, pulmonary, hepatic, or renal dysfunction, or coagulation disorders, which may significantly interfere with surgical outcomes. 2. Patients undergoing emergency or transfer laparotomy. 3. Missing or abnormal data, such as missing key variables (e.g., free time, blood loss). 4. Concurrent multiple primary cancers or malignant tumors in other sites, which may affect the focus of the surgery or the assessment of prognosis.

Design outcomes

Primary

MeasureTime frame
Operative time;

Secondary

MeasureTime frame
Intraoperative blood loss;Accuracy;Precision;

Countries

China

Contacts

Public ContactWu Ahao

The first affiliated hostipal of nanchang university

15770736779@163.com+86 791 8631 9546

Outcome results

None listed

Source: ChiCTR (via WHO ICTRP) · Data processed: May 16, 2026