MétaCan
Menu
Back to cohort

Transcutaneous Electrical Nerve Stimulation for the Treatment of Chronic Low Back Pain: A Systematic Review

2005· review· en· W1984224889 on OpenAlexaff
Amole Khadilkar, Sarah Milne, Lucie Brosseau, George A. Wells, Peter Tugwell, Vivian Robinson, Beverley Shea, Michael Saginur

Bibliographic record

VenueSpine · 2005
Typereview
Languageen
FieldMedicine
TopicPain Management and Treatment
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsMedicineTranscutaneous electrical nerve stimulationMeta-analysisRandomized controlled trialPhysical therapyOdds ratioMEDLINEChronic painConfidence intervalLow back painStrictly standardized mean differencePlaceboPopulationInternal medicinePathology

Abstract

fetched live from OpenAlex

STUDY DESIGN: Systematic review. OBJECTIVE: To determine the effectiveness of transcutaneous electrical nerve stimulation (TENS) in the management of chronic LBP. SUMMARY OF BACKGROUND DATA: Chronic low back pain (LBP) affects a significant proportion of the population. TENS was introduced more than 30 years ago as an adjunct to pharmacologic pain management. However, despite its widespread use, the usefulness of TENS in chronic LBP is still controversial. METHODS: We searched MEDLINE, EMBASE, PEDro, and the Cochrane Central Register of Controlled Trials (Issue 2, 2005), up to April 1, 2005. Only randomized controlled clinical trials (RCTs) evaluating the effect of TENS on chronic LBP were included. Two reviewers independently selected trials and extracted data using predetermined forms. Heterogeneity was tested with Cochrane's Q test. A fixed effect model was used throughout for calculating continuous variables, except where heterogeneity existed, in which case a random effects model was used. Results are presented as weighted mean differences with 95% confidence intervals (95% CI), where the difference between the treated and control groups was weighted by the inverse of the variance. Standardized mean differences were calculated by dividing the difference between the treated and control by the baseline variance. Standardized mean differences were used when different scales were used to measure the same concept. Dichotomous outcomes were analyzed with odds ratios. RESULTS: Two RCTs (175 patients) were included. They differed with respect to study design, methodologic quality, inclusion and exclusion criteria, characteristics of TENS application, treatment schedule, cointerventions, and measured outcomes. In one RCT, TENS produced significantly greater pain relief than the placebo control. However, in the other RCT, no statistically significant differences between treatment and control groups were shown for multiple outcome measures. Preplanned subgroup analyses, intended to examine the impact of different stimulation parameters, sites of TENS application, treatment durations, and baseline patient characteristics were not possible because of the small number of included trials. CONCLUSIONS: Evidence for the efficacy of TENS as an isolated intervention in the management of chronic LBP is limited and inconsistent. Larger, multicenter, RCTs are needed to better resolve its role in this condition. Increased attention should be given to the risks and benefits of long-term use, which more appropriately addresses the realities of managing chronic low back pain.

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)0.011
metaresearch head score (Gemma)0.053
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 score0.011
Threshold uncertainty score0.060

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.053
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0110.005
Bibliometrics0.0080.011
Science and technology studies0.0010.001
Scholarly communication0.0020.003
Open science0.0020.001
Research integrity0.0030.001
Insufficient payload (model declined to judge)0.0060.001

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 head0.045
GPT teacher head0.349
Teacher spread0.303 · 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

Citations117
Published2005
Admission routes1
Has abstractyes

Explore more

Same venueSpineSame topicPain Management and TreatmentFrench-language works237,207