Adjuvant Trastuzumab Induces Ventricular Remodeling Despite Aerobic Exercise Training
Bibliographic record
Abstract
PURPOSE: To examine the effect of aerobic training in mitigating trastuzumab-mediated left ventricular (LV) remodeling in women with human epidermal growth factor receptor 2 (HER2)-positive breast cancer. EXPERIMENTAL DESIGN: Seventeen women (53 +/- 7 years) with HER2-positive breast cancer did aerobic training during the first 4 months of adjuvant trastuzumab. Peak oxygen consumption and magnetic resonance imaging assessment of LV volumes, mass, and rest and peak (dobutamine stress) ejection fraction were assessed before and after 4 months of trastuzumab. RESULTS: Participants attended 59% +/- 32% of prescribed exercise sessions at 78% +/- 6% of peak heart rate. Peak exercise heart rate, systolic and diastolic blood pressure, power output, and oxygen consumption were not different after training (all P-values > 0.05). Exercise adherence predicted change in peak oxygen consumption (r = 0.77; P = 0.000). Resting end-diastolic (pre: 120 +/- 23 mL versus post: 133 +/- 16 mL) and end-systolic volumes (pre: 44 +/- 12 mL versus post: 55 +/- 11 mL) and mass (pre: 108 +/- 21 g versus post: 114 +/- 18 g) increased, whereas ejection fraction (pre: 64% +/- 4% versus post: 59% +/- 4%) decreased from baseline to post-intervention (all P-values < 0.05). Peak ejection fraction was lower after 4 months (pre: 79 +/- 4 versus post: 76 +/- 6%; P = 0.087). CONCLUSION: Initiation of adjuvant trastuzumab therapy is associated with LV cavity dilation and reduced ejection fraction despite aerobic exercise training. The long-term consequences of trastuzumab-induced LV remodeling and the means to prevent LV dysfunction require further study.
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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 | 0.000 | 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".