Electrical Stimulation of Acupuncture Points and Blood Pressure Responses to Postural Changes: A Pilot Study
Bibliographic record
Abstract
BACKGROUND: Application of transcutaneous electrical stimulation over acupuncture points (Acu-TENS) facilitates heart rate recovery after exercise and restores hemodynamic stability after open heart surgery. The role of Acu-TENS on cardiovascular parameters in response to postural changes has not been reported. OBJECTIVE: To investigate (1) the effect of Acu-TENS on blood pressure responses to -10º head-down postural change and (2) whether such effects were associated with modulation by the autonomic nervous system. METHOD: Sixteen healthy volunteers, mean age 22.8 (SD, 3.1) years, were subjected to a -10º head-down tilt from the supine position on 3 separate occasions and received in random order the following 3 intervention protocols for 40 minutes before the postural change: Acu-TENS (over bilateral acupuncture points, PC6), sham-TENS (TENS applied to the skin over the patellae), and control (no electrical output from the TENS device applied at PC6). Mean arterial pressure, large artery elasticity index, cardiac output, and heart rate were recorded and compared at different stimulation protocols in the supine and -10º head-down tilt positions. Spectral analysis of heart rate variability was used to determine any modulation by the autonomic nervous system. RESULTS: Change in large artery elasticity index was observed only in the Acu-TENS group (P < .05) and mean arterial pressure appeared most stable during Acu-TENS. Autonomic nervous system modulation was not apparent with spectral analysis, irrespective of intervention. Sympathetic activity predominated in all positions. CONCLUSION: Acu-TENS seems to reduce blood pressure changes with -10º head-down tilt with concomitant changes in arterial vessel tone.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".