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| Name | Class |
|---|---|
| Sports Medicine Research and Testing Laboratory | INDUSTRY |
| Partnership for Clean Competition | OTHER |
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A total of 40 subjects will be recruited for participation in this study. 20 subjects (10 males and 10 females) will be randomized to the active group (those receiving re-infusion of autologous blood) and 20 subjects (10 males and 10 females) will be randomized to the placebo group (receiving NS infusion).
Autologous blood transfusion is a major problem in a wide range of competitive sports. Methods with increased sensitivity, specificity, and feasibility are needed to identify athletes who cheat in this manner and compromise their health and the integrity of their sports in general. Complete blood counts (CBC) offer routine high-resolution assessment of the current hematologic status of individuals, providing estimates of a number of blood characteristics, such as the total hemoglobin concentration in the blood (HGB) and the volume fraction of cells in the blood (HCT). These CBC components are homeostatically controlled by the carefully regulated dynamic processes of red blood cell (RBC) production in and release from the bone marrow, RBC maturation in the peripheral circulation over the course of the ~100-day RBC lifespan, and clearance and recycling of senescent cells. Any significant perturbation to the circulating population of RBCs, like autologous transfusion, will immediately trigger compensatory modulation of one or more of these dynamic processes. The investigators believe quantification of these underlying dynamic processes will enable us to detect autologous transfusion. These dynamic RBC processes cannot currently be measured directly, but novel mathematical modeling enables their inference from routine complete blood and reticulocyte counts. The investigators propose to test the ability of modeled RBC dynamics to identify instances of autologous blood transfusion.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Treatment - Autologous Transfusion | Experimental | Participants will be randomized to the treatment group (autologous transfusion) |
|
| Control - Normal Saline (Placebo) | Placebo Comparator | Participants will either be randomized to the control group (saline transfusion) |
|
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Autologous Transfusion | Other | Participants will receive autologous transfusion on Day 21 |
|
| Measure | Description | Time Frame |
|---|---|---|
| Hematocrit | This will be used within a mathematical model to define the volume (v) and hemoglobin (h) dynamics of a typical RBC as deterministic functions (f) and random fluctuations in the rates of these changes over time (ζ) (Patel, Patel, & Higgins, 2015). | 8 weeks |
| Hemoglobin | This will be used within a mathematical model to define the volume (v) and hemoglobin (h) dynamics of a typical RBC as deterministic functions (f) and random fluctuations in the rates of these changes over time (ζ) (Patel, Patel, & Higgins, 2015). | 8 weeks |
| Reticulocyte count | This will be used within a mathematical model to define the volume (v) and hemoglobin (h) dynamics of a typical RBC as deterministic functions (f) and random fluctuations in the rates of these changes over time (ζ) (Patel, Patel, & Higgins, 2015). | 8 weeks |
| Mean corpuscular volume | This will be used within a mathematical model to define the volume (v) and hemoglobin (h) dynamics of a typical RBC as deterministic functions (f) and random fluctuations in the rates of these changes over time (ζ) (Patel, Patel, & Higgins, 2015). | 8 weeks |
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Inclusion Criteria:
Exclusion Criteria:
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| Name | Affiliation | Role |
|---|---|---|
| Daniel Cushman, M.D. | University of Utah | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| University of Utah Center for Clinical & Translational Science | Salt Lake City | Utah | 84132 | United States |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 4847238 | Background | Cowell HR, Swickard JW. Autotransfusion in children's orthopaedics. J Bone Joint Surg Am. 1974 Jul;56(5):908-12. No abstract available. | |
| 1996486 | Background | Cregan P, Donegan E, Gotelli G. Hemolytic transfusion reaction following transfusion of frozen and washed autologous red cells. Transfusion. 1991 Feb;31(2):172-5. doi: 10.1046/j.1537-2995.1991.31291142950.x. |
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| Control - Normal Saline (Placebo) | Other | Participants will receive saline on Day 21 |
|
| 9563411 | Background | Domen RE. Adverse reactions associated with autologous blood transfusion: evaluation and incidence at a large academic hospital. Transfusion. 1998 Mar;38(3):296-300. doi: 10.1046/j.1537-2995.1998.38398222875.x. |
| 21059904 | Background | Higgins JM, Mahadevan L. Physiological and pathological population dynamics of circulating human red blood cells. Proc Natl Acad Sci U S A. 2010 Nov 23;107(47):20587-92. doi: 10.1073/pnas.1012747107. Epub 2010 Nov 8. |
| 25972952 | Background | Kumar S, Goyal K, Dube SK, Dubey S, Bindra A, Kedia S. Anaphylactic reaction after autologous blood transfusion: A case report and review of the literature. Asian J Neurosurg. 2015 Apr-Jun;10(2):145-7. doi: 10.4103/1793-5482.154983. |
| 19199200 | Background | Morkeberg J, Belhage B, Ashenden M, Borno A, Sharpe K, Dziegiel MH, Damsgaard R. Screening for autologous blood transfusions. Int J Sports Med. 2009 Apr;30(4):285-92. doi: 10.1055/s-0028-1105938. Epub 2009 Feb 6. |
| 7570932 | Background | Popovsky MA, Whitaker B, Arnold NL. Severe outcomes of allogeneic and autologous blood donation: frequency and characterization. Transfusion. 1995 Sep;35(9):734-7. doi: 10.1046/j.1537-2995.1995.35996029156.x. |
| 21382045 | Background | Pottgiesser T, Sottas PE, Echteler T, Robinson N, Umhau M, Schumacher YO. Detection of autologous blood doping with adaptively evaluated biomarkers of doping: a longitudinal blinded study. Transfusion. 2011 Aug;51(8):1707-15. doi: 10.1111/j.1537-2995.2011.03076.x. Epub 2011 Mar 7. |
| 21188579 | Background | Solymos E, Guddat S, Geyer H, Flenker U, Thomas A, Segura J, Ventura R, Platen P, Schulte-Mattler M, Thevis M, Schanzer W. Rapid determination of urinary di(2-ethylhexyl) phthalate metabolites based on liquid chromatography/tandem mass spectrometry as a marker for blood transfusion in sports drug testing. Anal Bioanal Chem. 2011 Aug;401(2):517-28. doi: 10.1007/s00216-010-4589-4. Epub 2010 Dec 25. |
| 21268732 | Background | Weatherall DJ. Systems biology and red cells. N Engl J Med. 2011 Jan 27;364(4):376-7. doi: 10.1056/NEJMcibr1012683. No abstract available. |
| Background | Basson, M. Red blood cells by the numbers. Nature Medicine 16, 1 (2010). |
| ID | Term |
|---|---|
| D001804 | Blood Transfusion, Autologous |
| ID | Term |
|---|---|
| D001803 | Blood Transfusion |
| D001691 | Biological Therapy |
| D013812 | Therapeutics |
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