Lack of efficacy of alpha‐lipoic acid in burning mouth syndrome: A double‐blind, randomized, placebo‐controlled study
Bibliographic record
Abstract
BACKGROUND: A systematic review from the Cochrane Collaboration stated that alpha-lipoic acid (ALA) may help in the management of burning mouth syndrome (BMS). Because all of the data on ALA came from a single group, it has been stressed that its effectiveness should be reproduced in other populations. AIM: A double-blind, randomized, placebo-controlled study, including two test groups (Group A and Group B) and one control group (Group C), was carried out to evaluate the efficacy of systemic ALA (400 mg) and ALA (400 mg) plus vitamins in the treatment of BMS. METHODS: Sixty-six patients (54 females and 12 males) were included in an 8-week trial. Symptoms were evaluated by using a visual analogue scale (VAS) and the McGill Pain Questionnaire (MPQ) at 0, 2, 4, 8 and 16 weeks. RESULTS: Fifty-two patients (43 females and 9 males, aged 67.3+/-11.9 years) completed the study. All three groups had significant reductions in the VAS score and in the mixed affective/evaluative subscale of the MPQ; the responders' rate (at least 50% improvement in the VAS score) was about 30%. No significant differences were observed among the groups either in the response rate or in the mean latency of the therapeutic effect. CONCLUSIONS: The fairly high placebo effect observed is very similar to data obtained from patients affected by atypical facial pain. This study failed to support a role for ALA in the treatment of BMS, and further investigations are needed to identify the cause of BMS in order to develop efficacious therapies.
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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 | 0.020 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.006 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".