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Record W1983061276 · doi:10.1016/s1090-3801(03)00020-x

Lamotrigine for intractable sciatica: correlation between dose, plasma concentration and analgesia

2003· article· en· W1983061276 on OpenAlexfundaboutno aff
Elon Eisenberg, Gassan Damunni, Erica Hoffer, Yelena Baum, Norberto Krivoy

Bibliographic record

VenueEuropean Journal of Pain · 2003
Typearticle
Languageen
FieldMedicine
TopicPharmacological Effects and Toxicity Studies
Canadian institutionsnot available
FundersMcGill University
KeywordsLamotrigineSciaticaMedicineAnesthesiaLumbarPlasma concentrationSurgeryPharmacologyEpilepsy

Abstract

fetched live from OpenAlex

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.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.281
Threshold uncertainty score0.215

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.029
GPT teacher head0.290
Teacher spread0.261 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations30
Published2003
Admission routes2
Has abstractyes

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