Prediction of anastomotic leakage and hospitalization with machine learning after Robotic-assisted minimally invasive esophagectomy

Status

Active, not recruiting

Phases

Unknown

Study type

Observational

Source

DRKS

Registry ID

DRKS00029165

Enrollment

147

Registered

2022-06-13

Start date

2022-03-12

Completion date

Unknown

Last updated

2025-04-07

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

Conditions

C15

Interventions

Group 1: Robotically-assisted minimally invasive

Eligibility

Sex/Gender

All

Age

18 Years to No maximum

Inclusion criteria

Inclusion criteria: Patients who have undergone robotic minimally invasive Ivor Lewis esophagectomy (RAMIE) for esophageal cancer.

Exclusion criteria

Exclusion criteria: patients with evidence of COVID-19 infection and two-stage operations

Design outcomes

Primary

Measure	Time frame
Anastomotic Leakage, length of postoperative hospital stay (at least 30-days postoperative)	—

Countries

Germany

Contacts

Public ContactJens Hölzen

Universitätsklinikum Münster (UKM)Klinik für Allgemein-, Viszeral- und Transplantationschirurgie

Jenspeter.Hoelzen@ukmuenster.de+49 251 8351493

Outcome results

None listed

Source: DRKS (via WHO ICTRP) · Data processed: Feb 4, 2026