Perioperative adverse events increase morbidity and mortality. The rate and severity of complications and the risk for subsequent mortality are increased after high-risk procedures and in elevated-risk patients. Over the past decades, a multitude of prognostic studies identified perioperative risk factors at the population level. However, to allow for the advancement of precision surgery strategies, improved risk prediction on the individual patient level is warranted. Comprehensive, consecutive, multisource, structured, high-quality patient-related and procedure-related data sets, together with thorough follow-up and combined with state-of-the-art machine-learning analyses, are needed to facilitate precise prediction of perioperative complications. Therefore, we designed and currently conduct the Heidelberg Perioperative Deep Data study (HeiPoDD). Here, we report the rationale and design of the HeiPoDD study.

HeiPoDD is a prospective, single-centre, exploratory cohort study aiming to build up a large-scale deep-data base and corresponding biomaterial collection. 1040 adult patients planned for elective high-risk, non-cardiac surgery for any indication at Heidelberg University Hospital, Germany will be included. The obtained study-specific data set includes clinical data, lab values, genome- and proteome analysis as well as plasma, serum and peripheral blood mononuclear cells (PBMC) collected before and at days 1, 3 and 7 postsurgery. Urine samples are collected before and at day 1 postsurgery. Structured follow-up for perioperative complications such as redo-surgery, length of intensive care stay or length of hospital stay is conducted at days 30, 90 and 1 year postsurgery and for disease progression and survival after 3 and 5 years postsurgery. All study data will be transferred to the HeiPoDD registry to allow merging with all available routine clinical data from the hospital information system including imaging studies as well as haemodynamic and respiratory biosignals. Biomaterials will be stored in the HeiPoDD biomaterial bank to allow further analyses.

The trial protocol and amendments were approved by the ethics committee of the University of Heidelberg (S-758/2021). The protocol is registered with the German Clinical Trial Register (DRKS00024625). Participating patients’ data will be recorded only in pseudonymised form. After completion of the study, data collected during the study will be kept on file for up to 30 years. Biomedical samples collected during the study and entered into the biobank will be held for the same amount of time. The findings will be disseminated in peer-reviewed academic journals.

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.