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Non-invasive Hemodynamic Monitoring During Blood Donation for Developing Models of Early Blood Loss

Non-invasive Hemodynamic Monitoring During Blood Donation for Developing Models of Early Blood Loss.

Status
Completed
Phases
Unknown
Study type
Observational
Source
ClinicalTrials.gov
Registry ID
NCT01448694
Enrollment
320
Registered
2011-10-07
Start date
2011-11-30
Completion date
2014-09-30
Last updated
2014-12-03

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

Conditions

Hemorrhage

Keywords

Hemorrhage

Brief summary

This study is part of a Phase II STTR project to develop an algorithm called CipherSensor to apply feature extraction and machine learning techniques to non-invasive hemodynamic data to identify early signs of acute blood loss. The availability of this information may help to establish required interventions for treating trauma patients and battlefield casualties. Study hypothesis: Hemodynamic changes measured non-invasively during the blood donation process can be modeled to provide early estimations of blood loss.

Interventions

OTHERNo treatment

No treatment, only collecting observational data.

Sponsors

United States Department of Defense
CollaboratorFED
University of Colorado, Denver
Lead SponsorOTHER

Study design

Observational model
CASE_ONLY
Time perspective
PROSPECTIVE

Eligibility

Sex/Gender
ALL
Age
18 Years to 89 Years
Healthy volunteers
Yes

Inclusion criteria

* Approved by Children's Hospital Colorado Blood Donation Center for blood donation * Age 18 -89 years * Previously donated blood (lower likelihood of vasovagal response)

Exclusion criteria

* Pregnant * Incarcerated * Limited access to or compromised monitoring sites for non-invasive sensors: finger, ear and forehead sensors, oral/nasal cannula, 3 ECG electrodes.

Design outcomes

Primary

MeasureTime frameDescription
Algorithm24 monthsMathematical model of early blood loss

Countries

United States

Outcome results

None listed

Source: ClinicalTrials.gov · Data processed: Feb 4, 2026