Urinary di‐(2‐ethylhexyl) phthalate metabolites for detecting transfusion of autologous blood stored in plasticizer‐free bags
Bibliographic record
Abstract
BACKGROUND: Autologous blood transfusion (ABT) efficiently increases sport performance and is the most challenging doping method to detect. Current methods for detecting this practice center on the plasticizer di(2-ethlyhexyl) phthalate (DEHP), which enters the stored blood from blood bags. Quantification of this plasticizer and its metabolites in urine can detect the transfusion of autologous blood stored in these bags. However, DEHP-free blood bags are available on the market, including n-butyryl-tri-(n-hexyl)-citrate (BTHC) blood bags. Athletes may shift to using such bags to avoid the detection of urinary DEHP metabolites. STUDY DESIGN AND METHODS: A clinical randomized double-blinded two-phase study was conducted of healthy male volunteers who underwent ABT using DEHP-containing or BTHC blood bags. All subjects received a saline injection for the control phase and a blood donation followed by ABT 36 days later. Kinetic excretion of five urinary DEHP metabolites was quantified with liquid chromatography coupled with tandem mass spectrometry. RESULTS: Surprisingly, considerable levels of urinary DEHP metabolites were observed up to 1 day after blood transfusion with BTHC blood bags. The long-term metabolites mono-(2-ethyl-5-carboxypentyl) phthalate and mono-(2-carboxymethylhexyl) phthalate were the most sensitive biomarkers to detect ABT with BTHC blood bags. Levels of DEHP were high in BTHC bags (6.6%), the tubing in the transfusion kit (25.2%), and the white blood cell filter (22.3%). CONCLUSIONS: The BTHC bag contained DEHP, despite being labeled DEHP-free. Urinary DEHP metabolite measurement is a cost-effective way to detect ABT in the antidoping field even when BTHC bags are used for blood storage.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".