Running on Empty: Cardiovascular Reserve Capacity and Late Effects of Therapy in Cancer Survivorship
Bibliographic record
Abstract
Seminal investigations by Frank 1 and Starling 2 provided thefirst evidence that the heart possesses inherent reserve capacity—a key principle that is a pillar of modern cardiology research and practice. After 150 years of research, we now understand that cardiovascular reserve capacity (CVRC) is determined by the integrative ability of cross-system mechanisms (eg, neurohormonal, central, and peripheral oxygen delivery 3 ), which collectively possess remarkable adaptive capacity. Sequential as well as concurrent pathologic perturbations to either one or more of these mechanisms are offset by initial compensatory adaptive responses in other component systems to maintain whole-body homeostatic regulation—a process termed coordinated adaptation. 4 Unfortunately, CVRC is finite, and continued insults ultimately lead to overt dysfunction (eg, acute coronary syndromes, left ventricular dysfunction). Pathologic impairments in CVRC are etiologicinmanychronicdiseaseconditionsandarethusanintegralconsiderationindailypractice.Thepurposeofthiscommentaryistoprovidean overviewoftheguidingprinciplesandapplicationofCVRCintheoncology setting using early breast cancer as an illustrative model. Measurement of CVRC
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".