Topiramate in Treatment of Patients With Chronic Low Back Pain
Bibliographic record
Abstract
OBJECTIVE: Chronic low back pain (CLBP) is a widespread ailment. The aim of this study was to assess the efficacy of topiramate in the treatment of CLBP and the changes in anger status and processing, body weight, subjective pain-related disability and health-related quality of life during the course of treatment. METHODS: We conducted a 10-week, randomized, double-blind, placebo-controlled study of topiramate in 96 (36 women) patients with CLBP. The subjects were randomly assigned to topiramate (n=48) or placebo (n=48). Primary outcome measures were changes on the McGill Pain Questionnaire, State-Trait Anger Expression Inventory, Oswestry Low Back Pain Disability Questionnaire and SF-36 Health Survey scales, and in body weight. RESULTS: In comparison with the placebo group (according to the intent-to-treat principle), significant changes on the pain rating index of McGill Pain Questionnaire (Ps<0.001), State-Trait Anger Expression Inventory Scales (all Ps<0.001), Oswestry Low Back Pain Disability Questionnaire (P<0.001), and SF-36 Health Survey scales (all P<0.001, except on the role-emotional scale) were observed after 10 weeks in the patients treated with topiramate. Weight loss was also observed and was significantly more pronounced in the group treated with topiramate than in those treated with placebo (P<0.001). Most patients tolerated topiramate relatively well but 2 patients dropped out because of side effects. DISCUSSION: Topiramate seems to be a relatively safe and effective agent in the treatment of CLBP. Significantly positive changes in pain sensitivity, anger status and processing, subjective disability, health-related quality of life, and loss of weight were observed.
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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) | 0.001 | 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) | 0.003 | 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".