The Effectiveness of Acupuncture versus Clonazepam in Patients with Burning Mouth Syndrome
Bibliographic record
Abstract
OBJECTIVE: Burning mouth syndrome (BMS) is a chronic oral condition, characterised by burning symptoms, which mainly affects perimenopausal and postmenopausal women. Neuropathy might be the underlying cause of the condition. There are still insufficient data regarding successful therapy. The aim of this study was to compare the effectiveness of acupuncture and clonazepam. METHODS: Forty-two patients with BMS (38 women, 4 men) aged 66.7±12.0 years were randomly divided into two groups. Acupuncture was performed on 20 participants over 4 weeks, 3 times per week, on points ST8, GB2, TE21, SI19, SI18 and LI4 bilaterally as well as GV20 in the midline, each session lasting half an hour. Twenty-two patients took clonazepam once a day (0.5 mg in the morning) for 2 weeks and, after 2 weeks, two tablets (0.5 mg in the morning and in the evening) were taken for the next 2 weeks. Prior to and 1 month after either therapy, participants completed questionnaires: visual analogue scale, Beck Depression Inventory, Leeds Assessment of Neuropathic Symptoms and Signs (LANSS) pain scale, 36-item Short Form Health Survey (SF-36) and Montreal Cognitive Assessment (MoCA). RESULTS: There were significant improvements in the scores of all outcome measures after treatment with both acupuncture and clonazepam, except for MoCA. There were no significant differences between the two therapeutic regimens regarding the scores of the performed tests. CONCLUSIONS: Acupuncture and clonazepam are similarly effective for patients with BMS.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.002 | 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".