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

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

Status

Completed

Phases

Unknown

Study type

Observational

Source

ClinicalTrials.gov

Registry ID

NCT01699243

Enrollment

Registered

2012-10-03

Start date

2012-09-01

Completion date

2016-06-01

Last updated

2023-09-28

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Anesthesia, Pregnancy

Keywords

pregnancy, labor, epidural, fetal intervention

Brief 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.

Detailed description

Specific aims: 1. Collect noninvasive physiological waveform data from patients undergoing regional anesthesia for labor or fetal intervention at the University of Colorado Hospital and Children's Hospital Colorado. 2. Combine the physiological data from patient monitors with clinical and demographic data, including maternal problem list, medications, volume infused, use of vasopressors, arterial and venous pressures, fetal heart rate, fetal umbilical artery Doppler velocimetry, maternal uterine artery Doppler waveform, fetal and neonatal outcomes etc. for use in developing mathematical model for early detection of maternal functional hypovolemia. 3. Develop robust, real-time, computational models for: * estimating maternal volume status prior to administration of epidural anesthesia * estimating effective intravascular volume loss during maternal regional anesthesia * predicting an optimal, individual specific requirement for IV resuscitation and/or need for vasopressor agents while providing adequate analgesia using regional techniques and optimizing the fetal outcomes * identifying mothers susceptible to epidural induced hypotension

Interventions

None listed

Study design

Observational model

CASE_ONLY

Time perspective

PROSPECTIVE

Eligibility

Sex/Gender

FEMALE

Age

14 Years to 44 Years

Healthy volunteers

Inclusion criteria

* 1\. Age: 14 - 44 years * 2\. Pregnant * 3\. Undergoing regional anesthesia for labor or fetal intervention at the University of Colorado Hospital and Children's Hospital Colorado

Exclusion criteria

* 1\. Severe pre-eclampsia/eclampsia * 2\. Pre-procedural maternal hypertension requiring treatment * 3\. Significant fetal heart rate abnormalities prior to regional anesthesia * 4\. Incarcerated * 5\. Decisionally challenged * 6\. Limited access to or compromised monitoring sites for non-invasive finger and ear or forehead sensors

Design outcomes

Primary

Measure	Time frame	Description
effective intravascular volume loss during maternal regional anesthesia	during epidural, 1-4 hours	Develop algorithm for estimating effective intravascular volume loss during maternal regional anesthesia

Countries

United States

Outcome results