Prediction of anastomotic leakage and hospitalization with machine learning after Robotic-assisted minimally invasive esophagectomy
- Conditions
- C15Malignant neoplasm of oesophagus
- Registration Number
- DRKS00029165
- Lead Sponsor
- niversitätsklinikum Münster (UKM)Klinik für Allgemein-, Viszeral- und Transplantationschirurgie
- Brief Summary
Not available
- Detailed Description
Not available
Recruitment & Eligibility
- Status
- Complete
- Sex
- All
- Target Recruitment
- 131
Inclusion Criteria
Patients who have undergone robotic minimally invasive Ivor Lewis esophagectomy (RAMIE) for esophageal cancer.
Exclusion Criteria
patients with evidence of COVID-19 infection and two-stage operations
Study & Design
- Study Type
- observational
- Study Design
- Not specified
- Primary Outcome Measures
Name Time Method Anastomotic Leakage, length of postoperative hospital stay (at least 30-days postoperative)
- Secondary Outcome Measures
Name Time Method