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Record W4239461645 · doi:10.1002/14651858.cd001133

Anticonvulsant drugs for acute and chronic pain

2000· review· en· W4239461645 on OpenAlexaff
Philip J Wiffen, Sally Collins, H J McQuay, Dawn Carroll, Alejandro R. Jadad, Andrew Moore

Post-publication record

NatureRetraction
ReasonRetract and Replace;Withdrawn as Out of Date;
Date1/20/2010 0:00
Flagged by OpenAlex?Yes

Source: Retraction Watch, joined by DOI. OpenAlex records retraction as is_retracted, a boolean over a state space with at least four values, so it cannot express an expression of concern, a correction or a reinstatement; it reports them as false, which reads as “fine”.

Bibliographic record

VenueThe Cochrane Database of Systematic Reviews · 2000
Typereview
Languageen
Field
Topic
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMedicineAnalgesicPlaceboAdverse effectNeuropathic painClinical trialAnticonvulsantCarbamazepineChronic painRandomized controlled trialNumber needed to treatAnesthesiaPharmacologyInternal medicinePhysical therapyEpilepsyAlternative medicinePsychiatry

Abstract

fetched live from OpenAlex

BACKGROUND: Anticonvulsant drugs have been used in the management of pain since the 1960s. The clinical impression is that they are useful for neuropathic pain, especially when the pain is lancinating or burning. OBJECTIVES: To evaluate the analgesic effectiveness of anticonvulsant drugs compared to either placebo or other drugs in order to provide evidence-based recommendations for pain management in clinical practice and to identify a clinical research agenda. Adverse effects are also considered. SEARCH STRATEGY: Randomised trials of anticonvulsants in acute, chronic or cancer pain were identified by Medline (Silver Platter 3.0, 3.1 and 3.11) from 1966 to February 1994. In addition, 40 medical journals were hand searched (published between 1950 and 1990). Additional reports were identified from the reference list of the retrieved papers, and contacting investigators. Date of the most recent searches: 1994. SELECTION CRITERIA: Randomised trials reporting the analgesic effects of anticonvulsant drugs in patients, with pain assessment as either the primary or a secondary outcome. DATA COLLECTION AND ANALYSIS: Data were extracted by two independent reviewers, and trials were quality scored. Numbers-needed-to-treat (NNTs) were calculated from dichotomous data for effectiveness, adverse effects and drug-related study withdrawal, for individual studies and for pooled data. MAIN RESULTS: Twenty trials of four anticonvulsants were considered eligible (746 patients). The only placebo-controlled study in acute pain found no analgesic effect of sodium valproate. Three placebo-controlled studies of carbamazepine in trigeminal neuralgia had a combined NNT for effectiveness of 2.6, for adverse effects 3.4, and for severe effects (withdrawal from study) 24. Three placebo-controlled studies of diabetic neuropathy had a combined NNT for effectiveness of 3, for adverse effects 2.5, and for severe effects 20. Three placebo-controlled studies of migraine prophylaxis had a combined NNT for effectiveness of 2.4, for adverse effects 2.4 and for severe effects 39. Phenytoin had no effect in irritable bowel syndrome, and carbamazepine little effect in post-stroke pain. Clonazepam was effective in one study of temporomandibular joint dysfunction. No study compared one anticonvulsant with another. Anticonvulsants fared poorly against other treatments. REVIEWER'S CONCLUSIONS: Although anticonvulsants are used widely in chronic pain surprisingly few trials show analgesic effectiveness. No trial compared different anticonvulsants. There is no evidence that anticonvulsants are effective for acute pain. In chronic pain syndromes other than trigeminal neuralgia anticonvulsants should be withheld until other interventions have been tried.

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 imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.019
Threshold uncertainty score0.062

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.010
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0080.008
Science and technology studies0.0000.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0190.002

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 head0.103
GPT teacher head0.403
Teacher spread0.300 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSystematic review
Domainnot available
GenreReview

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

Citations130
Published2000
Admission routes1
Has abstractyes

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