Entity

Time filter

Source Type

LONGMONT, CO, United States

Patent
Flashback Technologies, LLC and The Regents Of The University Of Colorado | Date: 2014-11-14

Novel tools and techniques for assessing, predicting and/or estimating effectiveness of hydration of a patient and/or an amount of fluid needed for effective hydration of the patient, in some cases, noninvasively.


Patent
Flashback Technologies, LLC and The Regents Of The University Of Colorado | Date: 2015-10-16

Novel tools and techniques are provided for assessing, predicting and/or effectiveness of cardiopulmonary resuscitation (CPR), in some cases, noninvasively. In various embodiments, tools and techniques are provided for implementing rapid estimation of a patients compensatory reserve index (CRI) before, during, and after CPR is performed, and using the CRI and variations in CRI values to determine, in some instances, in real-time, the effectiveness of CPR that is performed.


Patent
The Regents Of The University Of Colorado and Flashback Technologies, LLC | Date: 2012-07-20

Tools and techniques for estimating a probability that a patient is bleeding or has sustained intravascular volume loss (e.g., due to hemodialysis or dehydration) and/or to estimate a patients current hemodynamic reserve index, track the patients hemodynamic reserve index over time, and/or predict a patients hemodynamic reserve index in the future. Tools and techniques for estimating and/or predicting a patients dehydration state. Tools and techniques for controlling a hemodialysis machine based on the patients estimated and/or predicted hemodynamic reserve index.


Patent
Flashback Technologies, LLC and The Regents Of The University Of Colorado | Date: 2014-11-14

Novel tools and techniques for assessing, predicting and/or estimating effectiveness of fluid resuscitation of a patient and/or an amount of fluid needed for effective resuscitation of the patient, in some cases, noninvasively.


Convertino V.A.,U.S. Army | Grudic G.,Flashback Technologies, LLC | Mulligan J.,Flashback Technologies, LLC | Moulton S.,Flashback Technologies, LLC | Moulton S.,University of Colorado at Denver
Journal of Applied Physiology | Year: 2013

Trauma patients with "compensated" internal hemorrhage may not be identified with standard medical monitors until signs of shock appear, at which point it may be difficult or too late to pursue life-saving interventions. We tested the hypothesis that a novel machine-learning model called the compensatory reserve index (CRI) could differentiate tolerance to acute volume loss of individuals well in advance of changes in stroke volume (SV) or standard vital signs. Two hundred one healthy humans underwent progressive lower body negative pressure (LBNP) until the onset of hemodynamic instability (decompensation). Continuously measured photoplethysmogram signals were used to estimate SV and develop a model for estimating CRI. Validation of the CRI was tested on 101 subjects who were classified into two groups: low tolerance (LT; n = 33) and high tolerance (HT; n = 68) to LBNP (mean LBNP time: LT = 16.23 min vs. HT = 25.86 min). On an arbitrary scale of 1 to 0, the LT group CRI reached 0.6 at an average time of 5.27 ± 1.18 (95% confidence interval) min followed by 0.3 at 11.39 ± 1.14 min. In comparison, the HT group reached CRI of 0.6 at 7.62 ± 0.94 min followed by 0.3 at 15.35 ± 1.03 min. Changes in heart rate, blood pressure, and SV did not differentiate HT from LT groups. Machine modeling of the photoplethysmogram response to reduced central blood volume can accurately trend individual-specific progression to hemodynamic decompensation. These findings foretell early identification of blood loss, anticipating hemodynamic instability, and timely application of life-saving interventions. Copyright © 2013 the American Physiological Society. Source

Discover hidden collaborations