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

University of Colorado, Denver320 enrolled

Overview

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.

Study Type

OBSERVATIONAL

Enrollment

320

Conditions

Hemorrhage

Interventions

No treatmentOTHER

No treatment, only collecting observational data.

Eligibility

Sex: ALLMin age: 18 YearsMax age: 89 YearsHealthy volunteers:

Medical Language ↔ Plain English

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.

Locations (1)

Children's Hospital Colorado

Aurora, Colorado, United States

Outcomes

Primary Outcomes

Algorithm

Mathematical model of early blood loss

Time frame: 24 months

Data from ClinicalTrials.gov

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