Outcome after surgery depends on both patient-related as well as procedure-related risks. Complications after surgery are a significant burden to patients and to the health system. A vast amount of often unstructured data from different sources are generated during surgery, which contain valuable information associated with outcome. Advances in computer hardware and machine learning now increasingly facilitate the development of prediction models in standardised, parametric, information-rich areas such as the perioperative setting. For the development and validation of risk scores and prediction models, high-fidelity data sources are required to arrive at meaningful and reliable predictions. However, data quality standards in retrospective studies are rarely met. Therefore, the prospective Heidelberg Perioperative Deep Data Registry and Biomaterial Bank (HeiPoDD - Registry and Bio Bank) was started to implement a clinical data base and a corresponding biobank merging the entirety of available clinical records.
The HeiPoDD - Registry and Bio Bank is a study-driven, prospective, single-centre observational registry data base and biomaterial bank. It contains data and material from eligible patients who give informed consent and undergo elective non-cardiac high-risk surgery at the surgical centre of the Heidelberg University Hospital. The screening for eligibility started in January 2022, with no maximum sample size specified in advance. Routine data are recorded and stored during hospital stay and potential readmissions within 90 days after index surgery. The data are merged with the potentially available genome, proteome, flow cytometry, and bio signal data. Endpoints are obtained from routine observations, stored data in the hospital information system and follow-up visits. Further, data and biological specimens from separate perioperative studies with the patients’ consent can be transferred into the HeiPoDD - Registry and Bio Bank as well. This large-scale data collection will allow the calculation of endpoint-specific prediction models using logistic regression models as well as machine learning models. The first 1040 patients included in the HeiPoDD - Registry and Bio Bank are also included in the HeiPoDD study.
The trial protocol and subsequent amendments were approved by the ethics committee of the University of Heidelberg (S-745/2021). Participating patients’ data will be entered only in pseudonymised form. Data and biomaterials will be kept for up to 30 years. The findings will be disseminated in peer-reviewed academic journals.
DRKS00025924, registered on 2021-11-12.