Estimating and Predicting Hemodynamic Changes During Hemodialysis

• Collect physiological waveform data from patients undergoing hemodialysis at the University of Colorado Hospital, Children's Hospital Colorado, and Fresenius Medical Centers using non-invasive monitoring techniques.
• Combine the physiological data from patient monitors with clinical and demographic data, including age, gender, race, problem list, reason for dialysis, estimated dry weight, volume removed, arterial and venous pressures, etc. for use in developing mathematical models of hemodialysis.
• Develop robust, real-time, computational models for:

• estimating acute intravascular volume loss during hemodialysis
• predicting an optimal, individual specific, intravascular volume to be removed during a hemodialysis session
• predicting intradialytic hypotension
• Determine:

• which non-invasive signals are relevant to each model type
• which features extracted from these signals are relevant
• which algorithms are capable of using the extracted features for each decision type

Inclusion criteria

• Age: 2 - 89 years
• Undergoing hemodialysis at the Fresenius Medical Centers, University of Colorado Hospital or Children's Hospital Colorado

Exclusion criteria

• Pregnant
• Incarcerated
• Decisionally challenged
• Positive for hepatitis B surface antigen
• Limited access to or compromised monitoring sites for non-invasive finger and ear or forehead sensors