Estimating and Predicting Hemodynamic Changes During Hemodialysis

Machine learning techniques and algorithms originally developed for use in the field of robotics can be applied to continuous, noninvasive physiological waveform data to discover hidden, hemodynamic relationships. Newly developed algorithms can, in real-time: 1) estimate acute blood loss volume, 2) monitor and estimate fluid resuscitation needs, 3) predict cardiovascular collapse well ahead of any clinically significant changes in standard vital signs, and 4) estimate intracranial pressure. We hypothesize that these same methods can be used to monitor volume loss during hemodialysis, as well as predict intradialytic hypotension, well before it occurs.

Study Overview

• Status: Completed
• Conditions: Hemodialysis

Detailed Description

1. 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.
2. 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.

3. 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

4. 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

• Study Type: Observational
• Enrollment (Actual): 241

Contacts and Locations

Study Locations

• United States
  • Colorado
    • Aurora, Colorado, United States, 80045
      • Children's Hospital Colorado
    • Aurora, Colorado, United States, 80045
      • University of Colorado Hospital
    • Aurora, Colorado, United States, 80011
      • Fresenius Medical Center East Denver
    • Denver, Colorado, United States, 80209
      • Fresenius Medical Center Central
    • Denver, Colorado, United States, 80220
      • Fresenius Medical Center Rocky Mountain

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: 2 years to 89 years (ADULT, OLDER_ADULT, CHILD)
• Accepts Healthy Volunteers: No
• Genders Eligible for Study: All

• Sampling Method: Non-Probability Sample

Study Population

Adult and pediatric patients undergoing hemodialysis at Fresenius Medical Centers, University of Colorado Hospital or Children's Hospital Colorado will be the population base for enrollment in this study. Patients may have acute kidney injury or end stage renal disease. Subjects may be inpatients or outpatients.

Description

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

Study Plan

How is the study designed?

Number of groups / cohorts

1

Cohorts and Interventions

Group / Cohort
Hemodialysis; Patients undergoing hemodialysis

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Acute intravascular volume loss during hemodialysis	development of algorithm to estimate acute intravascular volume loss during hemodialysis	one hemodialysis session (approx 3-4 hours)

Collaborators and Investigators

• Sponsor: University of Colorado, Denver

Study record dates

Study Major Dates

• Study Start: September 1, 2012
• Primary Completion (ACTUAL): December 1, 2016
• Study Completion (ACTUAL): December 1, 2016

Study Registration Dates

• First Submitted: September 27, 2012
• First Submitted That Met QC Criteria: October 3, 2012
• First Posted (ESTIMATE): October 4, 2012

Study Record Updates

• Last Update Posted (ESTIMATE): December 5, 2016
• Last Update Submitted That Met QC Criteria: December 1, 2016
• Last Verified: December 1, 2016

More Information

Terms related to this study

• Keywords: Hemodialysis; Hemodynamics
• Other Study ID Numbers: 11-1437