Aerobic Fitness Is Related to Myocardial Fibrosis Post–Anthracycline Therapy
Bibliographic record
Abstract
PURPOSE: We evaluated the impact of anthracyclines on left ventricular function and myocardial tissue characteristics using cardiovascular magnetic resonance (CMR) imaging to determine their relationship with V˙O2peak. METHODS: Women with breast cancer who had not yet received treatment (No-AT, n = 16) and had received anthracycline treatment ~1 yr earlier (Post-AT, n = 16) and controls without cancer (CON, n = 16) performed a maximal exercise test and a comprehensive 3T CMR examination, including native myocardial T1 mapping, where elevated T1 times are indicative of myocardial fibrosis. ANOVA and linear regression were used to compare CMR variables between groups and to determine associations with V˙O2peak. Subgroup analysis was performed by categorizing participants as "fit" or "unfit" based on whether their V˙O2peak value was greater or less than 100% of reference value for age, respectively. RESULTS: Left ventricular end-diastolic volume, ejection fraction, and mass were similar between groups. Post-AT, T1 times were elevated (1534 ± 32 vs 1503 ± 28 ms, P < 0.01), and V˙O2peak was reduced (23.1 ± 7.5 vs 29.5 ± 7.7 mL·kg-1⋅min-1, P = 0.02) compared with CON. In No-AT, T1 times and V˙O2peak were similar to CON. In the Post-AT group, T1 time was associated with V˙O2peak (R2 = 64%), whereas in the absence of anthracyclines (i.e., No-AT and CON groups), T1 time was not associated with V˙O2peak. Regardless of group, all fit women had similar T1 times, whereas unfit women Post-AT had higher T1 than unfit CON (1546 ± 22 vs 1500 ± 33 ms, P < 0.01). CONCLUSIONS: After anthracycline chemotherapy, an elevated T1 time suggesting greater extent of myocardial fibrosis, was associated with lower V˙O2peak. However, those who were fit did not have evidence of myocardial fibrosis after anthracycline treatment.
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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".