Gabapentin for the treatment of menopausal hot flashes
Bibliographic record
Abstract
OBJECTIVE: To compare the effectiveness and tolerability of gabapentin with placebo for the treatment of hot flashes in women who enter menopause naturally. DESIGN: A randomized, double-blind, placebo-controlled trial was conducted across the greater Toronto area between March 2004 and April 2006 in the community and primary care settings. Eligible participants were 200 women in natural menopause, aged 45 to 65 years, having at least 14 hot flashes per week. Study participants were randomized to receive gabapentin 300 mg oral capsules or placebo three times daily for 4 weeks. The primary outcome measure was the mean percentage change from baseline to week 4 in daily hot flash score, determined from participant diaries. Secondary outcome measures included changes in weekly mean hot flash scores and frequencies, quality of life, and adverse events. RESULTS: Of the 197 participants, 193 (98%) completed the study. Analysis was by intention to treat. Hot flash scores decreased by 51% (95% CI: 43%-58%) in the gabapentin group, compared with 26% (95% CI: 18%-35%) on placebo, from baseline to week 4. This twofold improvement was statistically significant (P < 0.001). The Menopause-Specific Quality-of-Life vasomotor score decreased by 1.7 (95% CI: 1.3-2.1; P < 0.001) in the gabapentin group. These women reported greater dizziness (18%), unsteadiness (14%), and drowsiness (12%) at week 1 compared with those taking placebo; however, these symptoms improved by week 2 and returned to baseline levels by week 4. CONCLUSIONS: Gabapentin at 900 mg/day is an effective and well-tolerated treatment for hot flashes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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 | 0.001 |
| 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".