Standardization of reticulocyte counts in the athlete biological passport
Bibliographic record
Abstract
INTRODUCTION: The percentage of circulating reticulocytes (RET%) is a useful marker of blood doping in the context of the Athlete Biological Passport (ABP). The viability of the ABP depends on the comparability of sample data obtained across multiple laboratories for a given athlete. With the recent introduction of a different technology for the measurement of reticulocytes, the goal of this study was to compare currently employed Sysmex XT/XE analyzers to the recently introduced Sysmex XN analyzer. METHODS: RET% differences were searched in two independent data sets, the first consisting of 95 369 RET% values coming from 29 laboratories located in five continents as part of routine testing for the ABP, the second from a targeted study involving 510 samples analyzed on both a Sysmex XT and XN analyzers by two different laboratories. RESULTS: A relatively small but significant bias of 0.27 ([0.22-0.35] 95% CI) for the first data set and 0.19% ([0.16-0.22] 95% CI) for the second data set was observed with Sysmex XN analyzers returning higher values than Sysmex XT/XE analyzers. This bias appears constant over most of the range of RET% measured in elite athletes. CONCLUSION: When RET% values are obtained for the same athlete with different technologies (XT/XE vs XN), an adjustment of RET% emanating from the XT/XE instruments through a decrease of 0.22% within the ABP calculated ranges appears to be sufficient to integrate the results from the two technologies.
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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 | 0.000 | 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".