Effectiveness of electroacupuncture for the treatment of long covid brain fog
Bibliographic record
Abstract
Objective: This article is aimed at demonstrating the effectiveness of electroacupuncture in treating Long COVID brain fog in 57 cases in Eastern Canada. Method: 57 patients (mean age 37, range 25-55 years, 56% female, 44% male), suffering from brain fog after a COVID-19 infection were treated with electroacupuncture using the acupoints DU20 (Baihui), DU24 (Shenting) and EX-HN1 (Sishencong), and the duration of each session was 30 minutes. The frequency of treatment was three times a week for 4 consecutive weeks. Results: After a 12-treatment course for each of the 57 patients, 48 cases were clinically cured, and 9 cases were ineffective. The rate of overall effectiveness was 84.2%. Conclusion: Electroacupuncture improved memory, concentration and attention; restored healthy function of the brain, liver, kidneys and spleen; and improved the patients’ physical condition and quality of life.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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".