[Effectiveness and safety of oxcarbazepine in chronic neuropathic pain: a study of 40 cases].
Bibliographic record
Abstract
INTRODUCTION: Neuropathic pain (NP) often fails to respond to the commonly established analgesic treatment. This fact, together with the existence of side effects, has led to the need to evaluate the analgesic effectiveness of antiepileptic drugs, which, as in the case of oxcarbazepine (OXC), are a valid alternative. AIMS: The aim of this study was to evaluate the effectiveness and safety of OXC in patients suffering from chronic NP. PATIENTS AND METHODS: We conducted a prospective, open study involving a series of 40 patients diagnosed with a long history of NP, which was previously resistant to different kinds of treatment with anticonvulsants, non-steroidal anti-inflammatory (NSAI) drugs, opiates and adjuncts. Patients were treated with OXC and they were evaluated in both the basal (prior to treatment) and final visits (after treatment) by means of the visual analogue scale (VAS), SF-McGill questionnaire and the Lattinen test. The patient's general impression of the result was also obtained. The statistical analysis was performed by calculating the "effect size", by computing Cohen's d. RESULTS: Treatment with OXC diminishes different symptomatic variations of this pain, but especially so in the case of lancinating discharges (d = 0.87, important effect) and burning pain (d = 0.60, moderate-important effect), although the allodynia (d = 0.48, moderate effect) also improved with treatment. In the opinion of the patients themselves, response to treatment was good or very good in 50% of cases. The chief side effects observed were dizziness, drowsiness and abdominal upsets. CONCLUSIONS: OXC can be seen as a therapeutic alternative to be taken very much into account in patients with NP having different aetiologies; it has a good benefit-risk ratio and is a form of treatment that is well accepted by 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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".