Vironix Health Applying Data Science to Prevent Chronic Kidney Disease Progression

Work group at the SIAM MPI Workshop held in June 2024 at the University of Vermont.

One in 7 American adults suffers from chronic kidney disease (CKD), with Medicare costs exceeding $77 billion. The silent and gradual decline in kidney function in CKD patients can lead to End Stage Kidney Disease (ESKD), requiring kidney transplants or dialysis. Early intervention in CKD patients can lead to an improved quality of life by slowing down the progression of CKD and healthcare expenses. Predictive models and dynamic risk stratification algorithms can aid in identifying patients at high risk of CKD degeneration (e.g., through changes in controller/BP medications and adjustments in diet, sleep, and exercise) as well as insights on how to manage and screen outpatients with CKD.

Vironix Health continues our work with other data scientists to understand disease progression and prevent kidney failure. In June, we presented at the Mathematical Problems in Industry (MPI) Workshop on “Analyzing the Influence of Virtual Care Management on Patient Health Outcomes & Risk Stratifying Chronic Kidney Disease Patients for Stage Degeneration.” Workshop participants at this Society for Industrial and Applied Mathematics (SIAM) event included senior faculty and attending scientists, postdoctoral fellows, graduate students, and industrial representatives, who discussed and tackled industry problems. 

Zachary Dana represented Vironix as our industry representative at the MPI workshop, leading a group of 12 applied math PhDs and industry professionals as the group developed approaches to industry challenges. He answered questions about the problems Vironix aims to solve, clarified the technology we use, and helped edit the summary papers.

The work group performed an extensive literature review and exploratory data analysis to identify potential factors associated with CKD risk, and proposed alternative modeling approaches for assessing the risk of CKD degeneration. We expect that SIAM will publish an academic article in August that further details the methods the Vironix group used.