Blood Flow-Restricted Training and Time Trial Performance: A Cohort Study of World-Class Rowers
Bibliographic record
Abstract
INTRODUCTION: This study aimed to explore the potential impact of incorporating blood flow restriction (BFR) training within a training block characterized by minimal high-intensity work on 2000-m rowing ergometer time trial (TT) performance in elite/world-class rowers. Physiological markers often associated with endurance performance (maximal aerobic capacity, V̇O 2max ; blood lactate thresholds and hemoglobin mass, Hb mass ) were measured to determine whether changes are related to an improvement in performance. METHODS: Using a quasi-experimental, observational study design (no control group), 2000-m TT performance, V̇O 2max , submaximal work rates eliciting blood lactate concentrations of ~2 and ~4 mmol·L -1 , and Hb mass were measured before and after 4 wk of noncompetitive season training, which included BFR rowing. BFR training consisted of 11 sessions of 2 × 10 min of BFR rowing at a workload equating to blood lactate concentrations of ~2 mmol·L -1 . Paired t -tests were used to compare pre-/postvalues, and Pearson correlation was used to examine whether physiological changes were associated with changes to TT performance. RESULTS: TT performance improved in both female (1.09% ± 1.2%, ~4.6 ± 5.2 s; P < 0.01) and male (1.17% ± 0.48%, ~4.5 ± 1.9 s; P < 0.001) athletes. V̇O 2max increased in female rowers only ( P < 0.01), but both sexes had an increase in work rates eliciting blood lactate concentrations of 2 mmol·L -1 (female: 184 ± 16 to 195 ± 15 W, P < 0.01; male: 288 ± 23 to 317 ± 26 W, P = 0.04) and 4 mmol·L -1 (female: 217 ± 13 to 227 ± 14 W, P = 0.02; male: 339 ± 43 to 364 ± 39 W, P < 0.01). No changes in Hb mass (both sexes, P = 0.8) were observed. Improvements in TT performance were not related to physiological changes (all correlations P ≥ 0.2). CONCLUSIONS: After 4 wk of training with BFR, the improvement in TT performance was greater than what is typical for this population. Physiological variables improved during this training block but did not explain improved TT performance.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".