Background and Aim: Cardiovascular (CV) diseases are the leading cause of death globally, hence it is important to detect CV risk as early as possible. National and international guidelines recommend using various equations for estimating risk e.g. in the context of primary prevention. Based on region, setting, ethnicity and other aspects different risk scores are suggested. The aim of this project was develop a modular open source software package as a tool for cardiologists and scientists to easily estimate CV risk using different scores within one workflow based on data from clinical cohorts or data of individual patients.

Methods and Results: Based on current guidelines and literature research the following risk scores were selected to be implemented in the first version of the software package: Systematic COronary Risk Evaluation from the European Society of Cardiology (ESC-SCORE), Systematic COronary Risk Evaluation in older persons (ESC-SCORE O.P.), Systematic COronary Risk Evaluation in a German Cohort (ESC-SCORE DE), PROCAM I Score, PROCAM II Score, Atherosclerotic cardiovascular disease score (ASCVD) Guideline from ACC/AHA on the Assessment of CV, Framingham Risk Score to assess risk of specific CVD (FRS-CVD), Framingham Risk Score to assess risk of CHD (FRS-CHD), Thrombin Receptor Antagonist in Secondary Prevention of Atherothrombotic Ischemic Events-TIMI 50 (TRA 2°P-TIMI), Reduction of Atherothrombosis for Continued Health (REACH).

As first step, a backend was created that is able to calculate risk with the scores above using the originally published formulas or risk tables. This backend is written using the open programming language R. It is freely availabe via GitHub and can be installed as integrated package within the statistical software environment of the user. Estimation of risk using this package is possible with indivdual patient data as well as large vectors representing e.g. study cohorts. As second step, an optional frontend was developed using the web based R Shiny graphical userinterface system. This frontend application is also freely available and can either be used directly in the web browser via shiny.io or downloaded to perform local calculations. If installed locally, no external data transfer is needed.

Conclusion and Outlook: The developed open source package allows the calculation of the most important CV risk scores seamlessly integrated into the individual statistical workflow. This uncomplicated and fast usage enables clinicians and scientists to perform individual CV risk assessment and CV risk asssement within large cohorts without the need to implement each risk score of interest individually. The modular design of the developed package allows the easy integration of future scores without changing the workflow. Due to the local use of the software no data has to be transferred facilitating strict data privacy concepts.