Impact Of Cancer And Chemotherapy On Autonomic Nervous System Function
Bibliographic record
Abstract
Cancer- and chemotherapy-related autonomic nervous system (ANS) dysfunction may contribute to increased cardiovascular (CV) morbidity- and mortality-risks in cancer survivors. However, inconsistent participant screening and assessment methods may compromise the reliability of the supporting evidence. Thus, good laboratory practices must be established before the presence and nature of cancer-related autonomic dysfunction can be characterized. PURPOSE: To assess the feasibility of conducting concurrent ANS and CV evaluations in young adult cancer patients, by: i) identifying methodological pitfalls and proposing good laboratory practice criteria for ANS testing in cancer, and ii) providing composite autonomic scoring scale (CASS)-based evidence of autonomic perturbations in cancer patients. METHODS: We assessed 13 patients (mixed diagnoses) before and after 4 cycles of chemotherapy. Their results were compared to 12 sex- and age-matched controls. ANS function was assessed using standardized tests of resting CV (tilt-table, respiratory sinus arrhythmia and Valsalva maneuver) and sudomotor (quantitative sudomotor axon reflex test) reactivity. CV reactivity during exercise was assessed using a modified Astrand-Ryhming cycle ergometer protocol. Our feasibility criteria addressed: i) recruitment potential, ii) retention rates, iii) pre-chemotherapy assessment potential, iv) test performance/tolerability, and v) identification and minimizing the influence of potentially confounding medication. Repeated measures ANOVAs were used to assess between- and within-group differences at baseline and follow-up. RESULTS: The overall success rate in achieving our feasibility criteria was 98.4%. We found greater CASS-based evidence of ANS impairment in patients compared to controls at baseline and follow-up (38.5% vs. 0% and 33.1% vs. 9.1%, respectively). CONCLUSIONS: Our feasibility results suggest the study of ANS function in young adult cancer patients receiving chemotherapy is possible. To our knowledge, this is the first study to report CASS-based evidence of ANS and sudomotor dysfunction in any cancer population. We found support for cancer/chemotherapy-related parasympathetic dysfunction - as a possible contributor to CV disease pathogenesis in cancer survivors.
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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 | 0.004 |
| 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".