Motorised lumbar traction in the management of low back pain with nerve root involvement: A feasibility study of effectiveness
Notice bibliographique
Résumé
PURPOSE: Nerve root involvement accompanies between 3-10% of Low Back Pain (LBP) and despite current guidelines, lumbar traction is a treatment still used by 40% of physiotherapists treating such patients. However its benefits remain to be established. The aim of this study was to establish the feasibility of a pragmatic Randomized Controlled Trial (RCT) to compare two treatment protocols reflecting current clinical practice (manual therapy, exercise and advice, with or without traction) in the management of acute/sub acute low back pain with ‘nerve root’ involvement. RELEVANCE: Evidence for the effectiveness of lumbar traction remains inconclusive due to the poor methodological quality, inadequate treatment doses, and heterogeneous populations used in past studies. This study addressed these issues by investigating a homogeneous group (‘nerve root’) and used treatment parameters for traction established from a UK wide survey of current practice. This represents the first high quality trial reflecting current traction use. PARTICIPANTS: 30 patients with nerve root pain, with or without neurological signs, were recruited between March 2004 and February 2005 within Down Lisburn Health and Social Care Trust, Northern Ireland. METHODS: A pragmatic RCT design was employed with patients randomly assigned to one of two treatment groups: Manual therapy (manual therapy, exercises and the ‘Back Book’) or Lumbar traction (lumbar traction, manual therapy, exercises and the ‘Back Book’). Outcome measures used were the: McGill pain questionnaire, Roland Morris disability questionnaire, Short form 36, and the Acute LBP Screening Questionnaire; these were recorded at baseline, discharge, 3 and 6 months post-discharge. In addition, visual analogue scale (VAS) scores for back and leg pain, the percentage of overall improvement (patient’s perception), and changes in neurological and neurodynamic tests were recorded. ANALYSIS: Data recorded from the primary outcome measures, VAS scores and percentage overall improvement were considered interval level and analysed with parametric statistics: repeated measures ANOVA (within group changes) and the independent t-test (between group changes). RESULTS: 27 patients completed treatment with a loss of four patients at the 3 and 6 month follow up: data for 23 patients were analysed. ANOVA showed a significant improvement in pain and disability from baseline to all follow up points for both groups; however there was no significant difference between groups. Feasibility issues highlighted that recruitment, selection, and outcome measures were appropriate however a sample size calculation suggested that a large study would be unfeasible (n=1,975). CONCLUSIONS: The results demonstrated that both groups improved with treatment but that no additional benefit was achieved with the addition of lumbar traction to the package of care. IMPLICATIONS: This study demonstrates that a study with this subgroup of LBP is feasible; however in light of the sample size calculation some aspects of the design would need to be reconsidered prior to a fully powered pragmatic RCT
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 | 0,025 | 0,047 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,003 | 0,003 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,003 |
| Communication savante | 0,001 | 0,002 |
| Science ouverte | 0,001 | 0,002 |
| Intégrité de la recherche | 0,003 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,009 | 0,001 |
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 ».