Model-driven survival prediction after congenital heart surgery

Model-driven survival prediction after congenital heart surgery - SACHS24 - Survival Assessment of Congenital Heart Surgery after 24 hours

Status

Active, not recruiting

Phases

Unknown

Study type

Observational

Source

DRKS

Registry ID

DRKS00028551

Enrollment

1500

Registered

2022-05-04

Start date

2021-12-13

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

Q24.9

Interventions

Group 1: Established risk parameters for dismal outcome after congenital heart surgery (age, STAT mortality score, aortic crossclamp time, serum lactate level) will be used to train and test a machine

Eligibility

Sex/Gender

All

Age

1 Days to 17 Years

Inclusion criteria

Inclusion criteria: Congenital heart surgery with cardiopulmonary bypass and postoperative stay in the intensive care unit for more than 24 hours.

Exclusion criteria

Exclusion criteria: No congenital heart surgery with cardiopulmonary bypass and postoperative stay in the intensive care unit for more than 24 hours.

Design outcomes

Primary

Measure	Time frame
The primary endpoint is the identification of rapidly available perioperative risk indicators on the basis of which a machine learning model for individual postoperative survival assessment can be trained.	—

Secondary

Measure	Time frame
Secondary endpoint is to test the generalizability of the model through a test data set.	—

Countries

Germany

Contacts

Public ContactChristoph Zürn

Department of Congenital Heart Defects and Pediatric Cardiology, University Heart CenterFreiburg - Bad Krozingen

christoph.zuern@uniklinik-freiburg.de+4976127043230

Outcome results

None listed

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