Heidelberg Perioperative Deep Data Study – a prospective cohort study

Heidelberg Perioperative Deep Data Study – a prospective cohort study - HeiPoDD

Status

Active, not recruiting

Phases

Unknown

Study type

Observational

Source

DRKS

Registry ID

DRKS00024625

Enrollment

1040

Registered

2021-12-07

Start date

2022-01-17

Completion date

Unknown

Last updated

2026-08-03

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

Conditions

Elective high risk surgery according to the definition of the European Society of Anaesthesiology

Interventions

Group 1: Patients scheduled for elective high-risk, non-cardiac surgery for any indication. The HeiPoDD study is a prospective single-center exploratory cohort study. Surgical procedures and perioper

Eligibility

Sex/Gender

All

Age

18 Years to No maximum

Inclusion criteria

Inclusion criteria: 1. Planned elective high-risk, non-cardiac surgery for any indication 2. Age = 18 years 3. Ability of subject to understand character and individual consequences of the clinical study 4. Written informed consent 5. Inclusion into HeiPoDD-Registry after written informed consent

Exclusion criteria

Exclusion criteria: 1. Expected lack of compliance or language barriers 2. ASA classification = 5 3. Jehovah's Witness

Design outcomes

Primary

Measure	Time frame
No confirmatory trial; multiple complications see secondary endpoints. There is no primary endpoint in this study. The objective of this study is to explore postoperative complications using data-driven, personalized risk prediction from a large-scale clinical data-set, supplemented by patient-specific proteome analysis. Adding the data into the HeiPoDD-Registry (DRKS00025924) will facilitate combining the study data with the clinical routine data-set stored in the HeiPoDD-Registry allowing to start a prospective data collection to gather the necessary volume of data to perform more in-depth analyses through machine learning methods. The objective of the research project is the development, validation and publication of algorithms and prediction models as well as the investigation of their predictive performance.	—

Measure

Time frame

No confirmatory trial; multiple complications see secondary endpoints. There is no primary endpoint in this study. The objective of this study is to explore postoperative complications using data-driven, personalized risk prediction from a large-scale clinical data-set, supplemented by patient-specific proteome analysis. Adding the data into the HeiPoDD-Registry (DRKS00025924) will facilitate combining the study data with the clinical routine data-set stored in the HeiPoDD-Registry allowing to start a prospective data collection to gather the necessary volume of data to perform more in-depth analyses through machine learning methods. The objective of the research project is the development, validation and publication of algorithms and prediction models as well as the investigation of their predictive performance.

—

Secondary

Measure	Time frame
Typical surgical complications like pain, bleeding, ischemia, thrombosis, embolism, infection, re-operation etc. as well as patient related outcomes (risk factors QoL), cardilogical, respiratory and urological endpoints	—

Countries

Germany

Contacts

Public ContactJan Larmann

Klinik für Anästhesiologie

jan.larmann@med.uni-heidelberg.de06221-56-39447

Outcome results

None listed

Source: DRKS (via WHO ICTRP) · Data processed: Aug 9, 2026