External validation of machine learning models for perioperative risk prediction

Status

Recruiting

Phases

Unknown

Study type

Observational

Source

DRKS

Registry ID

DRKS00036102

Enrollment

200000

Registered

2025-02-07

Start date

2025-09-20

Completion date

Unknown

Last updated

2025-10-06

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

Conditions

perioperative Complications

Interventions

Group 1: Post-operative patients at the Klinikum rechts der Isar Munich: Retrospective analysis of routine data of patients who underwent surgery under anaesthesia at the hospital between 2014 and 202

Eligibility

Sex/Gender

All

Inclusion criteria

Inclusion criteria: surgery with anesthesia

Exclusion criteria

Exclusion criteria: No electronic data capture

Design outcomes

Primary

Measure	Time frame
Hospital mortality as target of model prediction, defined as reason for discharge/transfer 079 according to §21 KhEntgG	—

Secondary

Measure	Time frame
Hospital length of stay recorded as the difference between discharge and admission date in accordance with §21 KhEntgG	—

Countries

Germany

Contacts

Public ContactSimone Kagerbauer

Klinikum rechts der Isar der Technischen Universität München

simone.kagerbauer@tum.de8941406275

Outcome results

None listed

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