Effect of strength training and antioxidant supplementation on perceived and performance fatigability in breast cancer survivors: a randomized, double-blinded, placebo-controlled study
Bibliographic record
Abstract
This randomized, double-blinded, placebo-controlled study aimed to investigate the effect of strength training (ST) combined with vitamin C and E supplementation on perceived and performance fatigability in breast cancer survivors (BCS). Twenty-five BCS were randomly assigned to 1 of 2 groups: vitamins (VIT; n = 12; 51.0 ± 9.0 years) or placebo (PLA; n = 13; 48.2 ± 8.3 years). Both groups performed a 10-week ST protocol, twice a week. The VIT group was supplemented with vitamins C (500 mg/day) and E (180 mg/day) and the PLA group with polydextrose (1 g/day), once a day after breakfast. At the beginning and at the end of the training period, perceived fatigability was assessed using Multidimensional Fatigue Inventory (MFI)-20 (general fatigue and physical fatigue). Performance fatigability was assessed during 30 maximal isokinetic knee extensions at 120°/s. General fatigue decreased similarly in the VIT (p = 0.004) and PLA (p = 0.011) groups. Physical fatigue decreased similarly in the VIT (p = 0.011) and PLA (p = 0.001) groups. Performance fatigability also decreased similarly in the VIT (p = 0.026) and PLA (p < 0.001) groups. There was no difference between groups at any moment (p > 0.05). In summary, antioxidant supplementation does not add any positive synergistic effect to ST in terms of improving perceived or performance fatigability in BCS. This clinical trial is registered in the Brazilian Clinical Trials Registry, number RBR-843pth (UTN no.: U1111-1222-6511). Novelty ST with maximal repetitions reduces perceived and performance fatigability of BCS. Vitamins C and E supplementation does not add any positive synergistic effect to ST in terms of reducing fatigability in BCS.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".