Ischemic Preconditioning Improves Time Trial Performance at Moderate Altitude
Bibliographic record
Abstract
PURPOSE: Endurance athletes often compete and train at altitude where exercise capacity is reduced. Investigating acclimation strategies is therefore critical. Ischemic preconditioning (IPC) can improve endurance performance at sea level through improved O2 delivery and utilization, which could also prove beneficial at altitude. However, data are scarce, and there is no study at altitudes commonly visited by endurance athletes. METHODS: In a randomized, crossover study, we investigated performance and physiological responses in 13 male endurance cyclists during four 5-km cycling time trials (TT), preceded by either IPC (3 × 5 min ischemia/5-min reperfusion cycles at 220 mm Hg) or SHAM (20 mm Hg) administered to both thighs, at simulated low (FIO2 0.180, ~1200 m) and moderate (FIO2 0.154, ~2400 m) altitudes. Time to completion, power output, cardiac output (Q˙), arterial O2 saturation (SpO2), quadriceps tissue saturation index (TSI) and RPE were recorded throughout the TT. Differences between IPC and SHAM were analyzed at every altitude using Cohen effect size (ES) and compared with the smallest worthwhile change. RESULTS: At low altitude, IPC possibly improved time to complete the TT (-5.2 s, -1.1%; Cohen ES ± 90% confidence limits -0.22, -0.44; 0.01), power output (2.7%; ES 0.21, 0.08; 0.51), and Q˙ (5.0%; ES 0.27, 0.00; 0.54), but did not alter SpO2, muscle TSI, and RPE. At moderate altitude, IPC likely enhanced completion time (-7.3 s; -1.5%; ES -0.38, -0.55; -0.20), and power output in the second half of the TT (4.6%; ES 0.28, -0.15; 0.72), increased SpO2 (1.0%; ES 0.38, -0.05; 0.81), and decreased TSI (-6.5%; ES -0.27, -0.73; 0.20) and RPE (-5.4%, ES -0.27, -0.48; -0.06). CONCLUSIONS: Ischemic preconditioning may provide an immediate and effective strategy to defend SpO2 and enhance high-intensity endurance performance at moderate altitude.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| 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 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".