Exercise and Cardiac Autonomic Function in Cancer Survivors – A Short Review
Bibliographic record
Abstract
Purpose The aim of this work was to produce a narrative review associating exercise, cardiac autonomic function and cancer survivors, related to HRV (Heart Rate Variability). Methods It was searched in the literature articles relating exercise, cardiac autonomic function, and cancer survivors including studies associating heart rate variability as a method of assessment of cardiac autonomic function. Four official literary collections as PubMed, Web of Science, Alberta Health Services and, Embase were used. Results Selected articles revealed a total of 15 studies in which 6 were related to HRV and Exercise Training, 3 related to HRR (Heart Rate Recovery) and Exercise Training and, 6 related to Exercise Testing in Non-Exercise Trained Patients. Conclusion Exercise therapy showed beneficial results modulating cardiac autonomic function in câncer survivors through parasympathetic stimulation. HRV and HRR are valid to assess cardiac autonomic function in exercise programs or as tests to monitor organic functions and to prevent further cardiac events in cancer survivors. Implications for Cancer Survivors HRV and HRR are valid to assess cardiac autonomic function in exercise programs or as tests to monitor organic functions and to prevent further cardiac events in cancer survivors.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".