High versus low frequency transcutaneous acupoint electrical stimulation as an adjunct therapy to prevent nausea and vomiting in the first 24 hours after infusion of high-grade emetic chemotherapy: A randomized controlled trial
Bibliographic record
Abstract
Background: Transcutaneous acupoint electrical stimulation (TAES) has been tested as antiemetic therapy. Objective: Evaluation of the effectiveness of two different frequencies of the electrical current as adjunctive therapy in the prevention of nausea and vomiting. Methods: This placebo-controlled clinical trial compared the incidence of nausea and vomiting (within the first 24 hours after high-grade emetic chemotherapy infusion) of 61 women (54 ± 11 years) with breast cancer undergoing three modes of TAES: high frequency (HF:150 Hz), low frequency (LF:10 Hz), and placebo (P). Electrodes were fixed at the acupuncture point PC6 and a symmetric bipolar current (pulse width 200 μs) was applied in a single 30-minute session prior to the start of chemotherapy infusion. All patients receive fixed antiemetic treatment infusions (ondansetron 8 mg) and rescue medication instructions, if necessary, according to the routine for infusions of cyclophosphamide associated with anthracycline. Results: The incidence of nausea was 47% in P, 45% in HF and 26% in LF. Although not significant, the intervention with LF-TAES at PC6 acupoint reached relevant values in reducing the relative risk of developing nausea (RR = 0.51; CI 95% = 0.18 to 1.44; p = 0.18) and a trend toward improved reported well-being (p = 0.06) and a lower Edmonton Symptom Rating Scale score (p = 0.08). The incidence of vomiting and the consumption of rescue antiemetic doses were very similar between the groups. Conclusion: New studies with LF and HF of TAES as adjuvant therapy for the prevention of nausea and vomiting should be carried out to confirm this hypothesis.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".