Observations on the Efficacy of Acupuncture plus Chinese Medicine Fumigation-washing in Treating Facial Neuritis
Bibliographic record
Abstract
Objective To investigate the clinical efficacy of acupuncture plus Chinese medicine fumigation-washing in treating facial neuritis.Methods Eighty patients with facial neuritis were randomly allocated to treatment and control groups,40 cases each.The treatment group received acupuncture plus Chinese medicine fumigation-washing and the control group,acupuncture alone.The pre-and post-treatment House-Braekmann(H-B) grading scale scores and Toronto Facial Grading System(TFGS) scores were compared between the two groups.Results There was a statistically significant pre-/post-treatment difference in the TFGS score in the two groups(P0.05).There was a statistically significant post-treatment difference in the H-B grading scale score between the two groups(P0.05).The cure rate was 95.0% in the treatment group and 80.0% in the control group;there was a statistically significant difference between the two groups(P0.05).There was a statistically significant difference in the time to cure the disease between the two groups(P0.05).Conclusions Acupuncture plus Chinese medicine fumigation-washing is an effective way to treat facial neuritis.Its therapeutic effects is superior to that of acupuncture alone.
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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) | 0.000 | 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".