A Model-Based Dataset for In-Silico Exploration of the Patterns of Relative Blood Volume Changes During Hemodialysis^*

The patterns of cardiovascular response to hemodialysis (HD), including the relative blood volume (RBV) changes, are not fully understood. Here, we present a synthetic dataset of intradialytic profiles of RBV changes simulated using a lumped-parameter, physiologically-based model of the cardiovascular system and the whole-body water and solute kinetics in 5,000 virtual patients with randomly adjusted values of 90 physiological parameters. The dataset (HD-SIM-RBV) includes a wide range of RBV curves varying in shape and magnitude of RBV changes during HD and it may be used to investigate parameters influencing intradialytic RBV profiles as well as to study the possibility of predicting the end-of-dialysis RBV level using RBV data from the initial phase of HD to help guide HD treatment to avoid hemodynamic instability.Clinical Relevance: Mining this dataset may help elucidate the mechanisms of cardiovascular response to hemodialysis.