Lamotrigine for intractable sciatica: correlation between dose, plasma concentration and analgesia
Bibliographic record
Abstract
An open trial was conducted to study the potential efficacy of the antiepileptic agent lamotrigine in relieving the sciatic pain and the relationship between lamotrigine dosage, plasma concentration and the clinical response. Subsequent to a 1 week washout period from previous analgesics, lamotrigine dose was titrated on a weekly basis from 25 to 400mg/day and was maintained at that dose for additional 4 weeks. Spontaneous pain, the Short Form McGill Pain Questionnaire (SFMPQ), the Straight Leg Raise (SLR) test, and range of motion of the lumbar spine (leaning foreword, to the affected side) were used to assess lamotrigine efficacy. Lamotrigine plasma concentration was tested at the end of each week during the titration period and at the end of the study. Fourteen patients were enrolled in the study. All outcome measurers improved compared to baseline during the titration period, but reached a statistically significant level of improvement only at the 400mg dose. A linear correlation was found between mean lamotrigine dose, mean plasma concentration and mean weekly spontaneous pain, mean SLR and mean bending the affected side, but not with the SFMPQ score. Study results suggest lamotrigine is a potentially effective and safe compound for the treatment of painful lumbar radiculopathy, and that it is likely to act in a dose- and plasma concentration-dependent fashion.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".