Effect and clinical mechanism exploration of acupuncture intervention for chemotherapy-related cognitive impairment (CRCI) in triple-negative breast cancer: study protocol for a randomized controlled trial
Bibliographic record
Abstract
Background: Chemotherapy-Related Cognitive Impairment (CRCI) significantly impacts the quality of life of breast cancer patients. Triple-negative breast cancer (TNBC) is associated with a higher risk of cognitive decline. The occurrence of CRCI is linked to the expression of inflammatory cytokines. Currently, limited research has examined the efficacy of acupuncture for treating CRCI in TNBC patients. This randomized controlled trial aims to evaluate the effectiveness of acupuncture in managing CRCI among TNBC patients and explore the mechanism by which acupuncture treatment affects CRCI through the inflammatory signaling pathway. Methods: This study is designed as a prospective, parallel, randomized, sham-controlled, assessor-blinded clinical trial. It will involve 50 patients diagnosed with TNBC who also experience CRCI. Participants will be randomly assigned to two groups, with an equal 1:1 allocation ratio into either the intervention group or the control group. Both groups will receive acupuncture sessions twice weekly for 8 weeks, with each session lasting approximately 20 min. The primary outcome of this study will be the percentage of subjects showing improvement in the Montreal Cognitive Assessment (MoCA) score at the end of treatment. Secondary outcome measures will include the Mini-Mental State Examination (MMSE) score, EORTC QLQ-C30 score, and the expression of inflammatory cytokines. Discussion: The findings of this study are expected to provide additional evidence supporting the efficacy of acupuncture and contribute clinical data that may elucidate the potential therapeutic mechanisms by which acupuncture ameliorates CRCI. Trial registration: https://www.chictr.org.cn/showproj.html?proj=218356, identifier: ChiCTR2400080147.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Protocol About the Canadian research system: no · About a Canadian topic: no | Randomized trial | low |
| gpt | no category Domain: not available · Genre: Protocol About the Canadian research system: no · About a Canadian topic: no | Randomized trial | low |
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 | 0.019 | 0.022 |
| Meta-epidemiology (narrow) | 0.006 | 0.003 |
| Meta-epidemiology (broad) | 0.013 | 0.006 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.008 | 0.006 |
| Insufficient payload (model declined to judge) | 0.054 | 0.007 |
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, unvalidatedLabeled directly by 2 models reading the full record.
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".