Plasma volume reduction and hematological fluctuations in high‐level athletes after an increased training load
Bibliographic record
Abstract
The time course of plasma volume ( PV ) reduction following an increased training load period is unknown and was investigated. The accompanying fluctuations in [Hb] and OFF ‐hr score were analyzed in the Athlete Biological Passport. Further, whether fluctuations in plasma albumin, soluble transferrin receptors ( sTfR ), and pro‐atrial natriuretic peptide (pro ANP ) concentrations correlate with PV fluctuations was investigated. Eleven high‐level competitive cyclists were investigated for 3 weeks. After initial measurements in week 1, training load was increased ~250% in week 2 followed by a reversion to baseline training load in week 3. PV and hematological variables were determined frequently during all weeks. The higher training load in week 2 increased ( P <.001) PV 10%, while [Hb] and OFF ‐hr score decreased ~6% ( P <.01) and ~16% ( P <.001), respectively. PV and [Hb] returned to baseline within 2 and 4 days after week 2, respectively, while OFF ‐hr score remained reduced for 6 days. Further, one and three atypical blood profiles of the ABP occurred during weeks 2 and 3, respectively. Individual changes in albumin, sTfR , and pro ANP only correlated weakly ( R 2 <.20) with PV fluctuations. In conclusion, PV and [Hb] fluctuations caused by an elevated training load period were reverted within 2 and 4 days after returning to baseline training load, respectively, while OFF ‐hr remained altered for 6 days. Furthermore, some atypical blood profiles were induced during and subsequent to the increased training load, demonstrating the importance of knowledge on naturally occurring hematological fluctuations. Finally, concentrations of albumin, sTfR , and pro ANP could not explain PV fluctuations.
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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 | 0.001 |
| 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".