Cardiovascular Reserve and Risk Profile of Postmenopausal Women After Chemoendocrine Therapy for Hormone Receptor–Positive Operable Breast Cancer
Bibliographic record
Abstract
Purpose. To examine cardiovascular function and risk profile of postmenopausal women treated with chemoendocrine therapy (CET) for hormone receptor-positive operable breast cancer. Methods. Forty-seven breast cancer patients and 11 age-matched healthy controls were studied. Participants performed a cardiopulmonary exercise test with expired gas analysis and impedance cardiography to assess peak aerobic power (VO(2peak)) and cardiovascular function (stroke volume, cardiac output, cardiac power output, and cardiac reserve). Traditional (i.e., body mass index, lipid profile, and fasting insulin and glucose) and novel (i.e., C-reactive protein, brain natriuretic peptide) cardiovascular risk biochemical factors were also assessed. Results. Breast cancer patients had significantly lower peak exercise stroke volume (68 +/- 9 versus 76 +/- 11 ml/beat), cardiac output (10.4 +/- 1.5 versus 11.7 +/- 2.4 l/minute), cardiac power output (3.0 +/- 0.5 versus 3.5 +/- 0.9 Watts), cardiac power output reserve (1.7 +/- 0.6 versus 2.4 +/- 0.8 Watts), and VO(2peak) (1.3 +/- 0.3 versus 1.6 +/- 0.2 l x min(-1)) than control subjects (p-values < .05). Patients with the greatest impairment in VO(2peak) had the worse cardiovascular risk profile. Exploratory analyses revealed several differences in study outcomes between the 26 patients receiving hormonal therapy with tamoxifen (TAM) and the 21 patients receiving aromatase inhibitor (AI) therapy. Conclusion. Breast cancer patients treated with adjuvant CET have a significantly and markedly lower cardiorespiratory fitness and cardiac functional reserve compared with age- and sex-matched controls. AI therapy may be associated with a more unfavorable cardiovascular risk profile than TAM. Prospective studies are required to further investigate the clinical value of these findings.
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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 | 0.001 |
| 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 | 0.000 | 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".