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| Name | Class |
|---|---|
| United States Department of Defense | FED |
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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.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Blood donors | Healthy volunteers who are donating a pint of whole blood |
|
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| No treatment | Other | No treatment, only collecting observational data. |
|
| Measure | Description | Time Frame |
|---|---|---|
| Algorithm | Mathematical model of early blood loss | 24 months |
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Inclusion Criteria:
Exclusion Criteria:
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Healthy adults
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| Name | Affiliation | Role |
|---|---|---|
| Steve Moulton, MD | Children's Hospital Colorado | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Children's Hospital Colorado | Aurora | Colorado | 80045 | United States |
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| ID | Term |
|---|---|
| D006470 | Hemorrhage |
| ID | Term |
|---|---|
| D010335 | Pathologic Processes |
| D013568 | Pathological Conditions, Signs and Symptoms |
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