Efficacy of the Transcutaneous Electrical Nerve Stimulation for the Treatment of Chronic Low Back Pain
Notice bibliographique
Résumé
BACKGROUND: Low back pain affects a large proportion of the population. Transcutaneous electrical nerve stimulation (TENS) was introduced more than 30 years ago as an alternative therapy to pharmacologic treatments for chronic pain. However, despite its widespread use, the efficacy of TENS is still controversial. PURPOSE: The aim of this meta-analysis was to determine the efficacy of TENS in the treatment of chronic low back pain. METHODS: The authors searched MEDLINE, EMBASE, PEDro, and the Cochrane Controlled Trials Register up to June 1, 2000. Only randomized controlled clinical trials of TENS for the treatment of patients with a clinical diagnosis of chronic low back pain were included. Abstracts were excluded unless further data could be obtained from the authors. Two reviewers independently selected trials and extracted data using predetermined forms. DATA ANALYSIS: Heterogeneity was tested with Cochrane's Q test. A fixed effects model was used throughout for 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, 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 integrated to measure the same concept. Dichotomous outcomes were analyzed with odds ratios. MAIN RESULTS: Five trials were included, with 170 subjects randomized to the placebo group receiving sham TENS and 251 subjects receiving active TENS (153 for conventional mode, 98 for acupuncture-like TENS). The schedule of treatments varied greatly between studies ranging from one treatment/day for 2 consecutive days, to three treatments/day for 4 weeks. There were no statistically significant differences between the active TENS group compared with the placebo TENS group for any outcome measures. Subgroup analysis performed on TENS application and methodologic quality did not demonstrate a significant statistical difference (P > 0.05). Remaining preplanned subgroup analysis was not conducted because of the small number of included trials and the variety of outcome measures reported. CONCLUSION: The results of the meta-analysis present no evidence to support the use or nonuse of TENS alone in the treatment of chronic low back pain. Considering the small number of studies responding to the criteria to be included in this meta-analysis, it is clear that more appropriately designed studies are needed before a final conclusion. Clinicians and researchers should consistently report the characteristics of the TENS device and the application techniques used. New trials on TENS should make use of standardized outcome measures. This meta-analysis lacked data on how TENS efficacy is affected by four important factors: type of applications, site of application, treatment duration of TENS, and optimal frequencies and intensities.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,012 | 0,030 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,001 |
| Méta-épidémiologie (sens large) | 0,009 | 0,014 |
| Bibliométrie | 0,004 | 0,003 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,003 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,002 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».