Hemorrhage
Conditions
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
No treatment, only collecting observational data.
Sponsors
Study design
Eligibility
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
| Measure | Time frame | Description |
|---|---|---|
| Algorithm | 24 months | Mathematical model of early blood loss |
Countries
United States