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Continuous Noninvasive Method for Estimating and Predicting Maternal and Fetal Hemodynamic Changes During Regional Anesthesia

NCT01699243 · Status: COMPLETED · Type: OBSERVATIONAL · Enrollment: 19

Last updated 2023-09-28

No results posted yet for this study

Summary

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) predict cardiovascular collapse well ahead of any clinically significant changes in standard vital signs, 2) monitor and estimate fluid resuscitation needs, 3) estimate acute blood loss volume, and 4) estimate intracranial pressure. The investigators hypothesize that these same methods can be used to predict functional hypovolemia during regional anesthesia for labor or fetal intervention.

Conditions

  • Pregnancy
  • Anesthesia

Sponsors & Collaborators

  • University of Colorado, Denver

    lead OTHER

Principal Investigators

  • Steve Moulton, MD · University of Colorado, Denver

Eligibility

Min Age
14 Years
Max Age
44 Years
Sex
FEMALE
Healthy Volunteers
No

Timeline & Regulatory

Start
2012-09-01
Primary Completion
2016-06-01
Completion
2016-06-01

Countries

  • United States

Study Locations

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Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT01699243 on ClinicalTrials.gov