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Herbal medicine for low back pain

2006· reference-entry· en· W4245351930 on OpenAlexaff
Joel Gagnier, Maurits W. van Tulder, Brian Berman, Claire Bombardier

Bibliographic record

VenueCochrane Database of Systematic Reviews · 2006
Typereference-entry
Languageen
Field
Topic
Canadian institutionsInstitute for Work & HealthNational Defence Medical Centre
Fundersnot available
KeywordsMedicineLow back painMEDLINEAlternative medicineBack painClinical trialPsychological interventionRandomized controlled trialPhysical therapyConsolidated Standards of Reporting TrialsTraditional medicineChronic painFamily medicineInternal medicinePsychiatryPathology

Abstract

fetched live from OpenAlex

BACKGROUND: Low-back pain is a common condition and a substantial economic burden in industrialized societies. A large proportion of patients with chronic low-back pain use complementary and alternative medicine (CAM), visit CAM practitioners, or both. Several herbal medicines have been purported for use in low-back pain. OBJECTIVES: To determine the effectiveness of herbal medicine for non-specific low-back pain. SEARCH STRATEGY: We searched the following electronic databases: Cochrane Complementary Medicine Field Trials Register (Issue 3, 2005), MEDLINE (1966 to July 2005), EMBASE (1980 to July 2005); checked reference lists in review articles, guidelines and retrieved trials; and personally contacted individuals with expertise in this very specialized area. SELECTION CRITERIA: We included randomized controlled trials, examining adults (over 18 years of age) suffering from acute, sub-acute or chronic non-specific low-back pain. The interventions were herbal medicines, defined as plants that are used for medicinal purposes in any form. Primary outcome measures were pain and function. DATA COLLECTION AND ANALYSIS: Two authors (JJG & MVT) conducted the database searches. One author contacted content experts and acquired relevant citations. Full references and abstracts of the identified studies were downloaded. A hard copy was retrieved for final inclusion decisions. Methodological quality and clinical relevance were assessed separately by two individuals. Disagreements were resolved by consensus. MAIN RESULTS: Ten trials were included in this review. Two high quality trials examining the effects of Harpagophytum Procumbens (Devil's Claw) found strong evidence that daily doses standardized to 50 mg or 100 mg harpagoside were better than placebo for short-term improvements in pain and rescue medication. Another high quality trial demonstrated relative equivalence to 12.5 mg per day of rofecoxib (Vioxx). Two trials examining the effects of Salix Alba (White Willow Bark) found moderate evidence that daily doses standardized to 120 mg or 240 mg salicin were better than placebo for short-term improvements in pain and rescue medication. An additional trial demonstrated relative equivalence to 12.5 mg per day of rofecoxib. Three low quality trials on Capsicum Frutescens (Cayenne), examining various topical preparations, found moderate evidence that Capsicum Frutescens produced more favourable results than placebo and one trial found equivalence to a homeopathic ointment. AUTHORS' CONCLUSIONS: Harpagophytum Procumbens, Salix Alba and Capsicum Frutescens seem to reduce pain more than placebo. Additional trials testing these herbal medicines against standard treatments are needed. The quality of reporting in these trials was generally poor. Trialists should refer to the CONSORT statement extension for reporting trials of herbal medicine interventions.

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)0.002
metaresearch head score (Gemma)0.004
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: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.013
Threshold uncertainty score0.044

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0030.002
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0130.001

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 head0.359
Teacher spread0.256 · 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

Citations41
Published2006
Admission routes1
Has abstractyes

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