Immature reticulocytes are sensitive and specific to low‐dose erythropoietin treatment at sea level and altitude
Bibliographic record
Abstract
Abstract We investigated whether immature reticulocyte fraction (IRF) and immature reticulocytes to red blood cells ratio (IR/RBC) are sensitive biomarkers for low‐dose recombinant human erythropoietin (rhEpo) treatment at sea level (SL) and moderate altitude (AL) and whether multi (FACS) or single (Sysmex‐XN) fluorescence flow cytometry is superior for IRF and IR/RBC determination. Thirty‐nine participants completed two interventions, each containing a 4‐week baseline, a 4‐week SL or AL (2,230 m) exposure, and a 4‐week follow‐up. During exposure, rhEpo (20 IU kg −1 ) or placebo (PLA) was injected at SL (SL rhEpo , n = 25, SL PLA n = 9) and AL (AL rhEpo , n = 12, AL PLA n = 27) every second day for 3 weeks. Venous blood was collected weekly. Sysmex measurements revealed that IRF and IR/RBC were up to ~70% ( P < 0.01) and ~190% ( P < 0.001) higher in SL rhEpo than SL PLA during treatment and up to ~45% ( P < 0.001) and ~55% ( P < 0.01) lower post‐treatment, respectively. Compared with AL PLA , IRF and IR/RBC were up to ~20% ( P < 0.05) and ~45% ( P < 0.001) lower post‐treatment in SL rhEpo , respectively. In AL rhEpo , IRF and IR/RBC were up to ~40% ( P < 0.05) and ~110% ( P < 0.001) higher during treatment and up to ~25% ( P < 0.05) and ~40% ( P < 0.05) lower post‐treatment, respectively, compared with AL PLA . Calculated thresholds provided ~90% sensitivity for both biomarkers at SL and 33% (IRF) and 66% (IR/RBC) at AL. Specificity was >99%. Single‐fluorescence flow cytometry coefficient of variation was >twofold higher at baseline ( P < 0.001) and provided larger or similar changes compared to multi‐fluorescence, albeit with smaller precision. In conclusion, IRF and IR/RBC were sensitive and specific biomarkers for low‐dose rhEpo misuse at SL and AL.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| 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) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".