Effects Of Aerobic Training On Determinants Of Peak Oxygen Consumption In Post-treatment Breast Cancer
Bibliographic record
Abstract
PURPOSE: Breast cancer (BC) therapy causes marked impairments in peak oxygen consumption (VO2peak), predisposing patients to elevated risk of cardiovascular morbidity and mortality. The determinants of impaired VO2peak and the effects of aerobic training (AT) on these determinants in post-treatment BC are not known. METHODS: Individual participant data from two randomized AT trials [(1) women at high risk of BC (BC risk; n = 24), (2) women 1-5 years post-treatment (n = 30)] were included. VO2peak and peak cardiac output (Q) were evaluated in women randomized to AT using identical treadmill-based peak cardiopulmonary and echocardiography exercise testing protocols before and after 12 (BC risk) or 16 weeks (post-treatment) of 150 min/wk of non-linear supervised AT. Arterial-venous oxygen content difference (a-vO2 Diff) was calculated using the Fick equation (VO2peak divided by Q). RESULTS: At baseline, relative to BC risk (mean age ± SD, 56.9 ± 9.3 years) post-treatment (61.3 ± 8.3 years) had lower VO2peak (post-treatment: 19.8 ± 3.8 ml O2·kg-1·min vs. 25.9 ± 4.7 ml O2·kg-1·min; p < 0.01). Peak Q was lower in post-treatment (14.5 ± 1.8 L/min) relative to BC risk (16.3 ± 2.3 L/min, p < 0.05); there were no significant differences in a-vO2 Diff. After AT, VO2peak improved in post-treatment (1.2 ± 1.7 ml O2·kg-1·min) and BC risk (2.5 ± 2.6 ml O2·kg-1·min). Peak a-vO2 Diff increased in both BC risk (0.8 ± 1.6 mL/dL) and post-treatment (0.8 ± 1.7 mL/dL). Peak Q increased in BC-risk (0.4 ± 2.0 L/min) and decreased in post-treatment (-0.1 ± 2.3 L/min). CONCLUSIONS: Aerobic training improves peak a-vO2 Diff but not peak cardiac output in post-treatment BC. These findings suggest that AT volume greater than 150 min/wk may be needed to induce cardiovascular improvements and further augment VO2peak response in post-treatment BC. 3U01CA271287-02S1
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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) | 0.001 | 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 | 0.001 |
| 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".