<p>Therapeutic Dose of Amitriptyline for Older Patients with Burning Mouth Syndrome</p>
Bibliographic record
Abstract
OBJECTIVE: To assess the therapeutic dose and safety of amitriptyline and the outcome following treatment with amitriptyline among older patients with burning mouth syndrome (BMS). METHODS: 187 consecutive patients were prescribed amitriptyline as a first-line medication from April 2016 to September 2018 and followed-up for >1 month. Patients were divided into 3 groups: group 1, 113 patients aged <65 years; group 2, 52 patients aged between 65 and 74 years; and group 3, 22 patients aged 75 years or older. The visual analog scale (VAS), Pain Catastrophizing Scale (PCS), Somatic Symptom Scale-8 (SSS-8), Patient Global Impression of Change (PGIC), and Short-form McGill Pain Questionnaire (SF-MPQ) were used for analysis. RESULTS: Thirty-two patients (17 in group 1, 10 in group 2, and 5 in group 3) stopped taking amitriptyline due to side effects. There were no differences among the groups with respect to sex; scores of VAS, PCS, and SSS-8; and drop-out ratio. There were no significant differences in the VAS, PCS, and PGIC scores among the groups after 1 month. The mean daily dose after 1 month was 20.4 ± 8.6 mg in group 1, 17.3 ± 8.7 mg in group 2, and 13.2 ± 5.8 mg in group 3; this difference was significant (p value = 0.003). About 76% of patients showed improvements in their symptoms (PGIC ≥ 3). About 90% of patients reported side effects. No serious side effects occurred. CONCLUSION: The therapeutic dose of amitriptyline may be lower for older BMS patients than for younger patients.
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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 | 0.001 |
| 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".