Improvement in Vagal Function in a Post Breast Cancer Patient Receiving Chiropractic Care: A Case Study
Bibliographic record
Abstract
Heart rate variability (HRV) is widely used to demonstrate the vagal function and sympathetic function of the autonomic nervous system and evaluate autonomic dysregulation. Current literature demonstrated that the HRV of women who have gone through breast cancer, surgery and chemotherapy stays low for possibly up to a year or more. The purpose of this paper was to chronicle the consistent improvements in salutogenesis, measured through HRV, in a 43-year-old woman post breast cancer following a course of chiropractic care focused on vertebral subluxation correction. Chiropractic care was provided to a 43-year-old woman following bilateral radical mastectomy and chemotherapy for management of breast cancer. Chiropractic care was focused on the assessment and correction of vertebral subluxation. The parameter numbers used were the standard interbeat interval (Sd IBI) from the heart rate analysis. Chiropractic care was provided over a period of 34 weeks. HRV assessment was performed at the initiation of care and again at weeks 4, 6, 13 and 34. The Sd IBI measurements recorded during the respective assessment visits indicated significant improvement compared to normative data for the same population. A course of chiropractic care focused on the assessment and correction of vertebral subluxation was associated with a salutogenic response in a woman post breast cancer, as measured via HRV. J Med Cases. 2019;10(6):171-178 doi: https://doi.org/10.14740/jmc3306
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".