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Record W4319957213 · doi:10.1136/bmjopen-2022-065999

Mechanisms of chiropractic spinal manipulative therapy for patients with chronic primary low back pain: protocol for a mechanistic randomised placebo-controlled trial

2023· article· en· W4319957213 on OpenAlexafffund
Carlos Gevers‐Montoro, Arantxa Ortega, Mathieu Piché

Bibliographic record

VenueBMJ Open · 2023
Typearticle
Languageen
FieldMedicine
TopicMusculoskeletal pain and rehabilitation
Canadian institutionsUniversité du Québec à Trois-RivièresCanadian Chiropractic Association
FundersFonds de recherche du Québec – Nature et technologiesFonds de Recherche du Québec - SantéEuropean Centre for Chiropractic Research ExcellenceFondation Chiropratique du Québec
KeywordsMedicineChiropracticSpinal manipulationPhysical therapyManual therapyPlaceboLow back painAlternative medicineBack painRandomized controlled trialProtocol (science)Chronic painClinical trialPhysical medicine and rehabilitationSurgeryInternal medicinePathology

Abstract

fetched live from OpenAlex

INTRODUCTION: Chronic low back pain (CLBP) is a highly prevalent and disabling condition. Identifying subgroups of patients afflicted with CLBP is a current research priority, for which a classification system based on pain mechanisms was proposed. Spinal manipulative therapy (SMT) is recommended for the management of CLBP. Yet, little data are available regarding its mechanisms of action, making it difficult to match this intervention to the patients who may benefit the most. It was suggested that SMT may influence mechanisms associated with central sensitisation. Therefore, classifying patients with CLBP according to central sensitisation mechanisms may help predict their response to SMT. METHODS AND ANALYSIS: This protocol describes a randomised placebo-controlled trial aiming to examine which variables linked to central sensitisation may help predict the clinical response to SMT in a cohort of patients with CLBP. One hundred patients with chronic primary low back pain will be randomised to receive 12 sessions of SMT or placebo SMT over a 4-week period. Pain intensity and disability will be assessed as primary outcomes after completing the 4-week treatment (primary endpoint), and at 4-week and 12-week follow-ups. Baseline values of two pain questionnaires, lumbar pressure pain thresholds, concentrations of an inflammatory cytokine and expectations of pain relief will be entered as predictors of the response to SMT in a multiple regression model. Changes in these variables after treatment will be used in a second multiple regression model. The reference values of these predictors will be measured from 50 age and sex-matched healthy controls to allow interpretation of values in patients. Mixed analyses of variance will also be conducted to compare the primary outcomes and the predictors between groups (SMT vs placebo) over time (baseline vs post-treatment). ETHICS AND DISSEMINATION: Ethical approval was granted by the Fundación Jiménez Díaz Clinical Research Ethics Committee. TRIAL REGISTRATION NUMBER: NCT05162924.

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)0.029
metaresearch head score (Gemma)0.031
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.066
Threshold uncertainty score0.221

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0290.031
Meta-epidemiology (narrow)0.0070.003
Meta-epidemiology (broad)0.0120.007
Bibliometrics0.0020.003
Science and technology studies0.0040.004
Scholarly communication0.0050.003
Open science0.0040.003
Research integrity0.0090.008
Insufficient payload (model declined to judge)0.0660.013

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 head0.066
GPT teacher head0.400
Teacher spread0.334 · 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 designRandomized trial
Domainnot available
GenreProtocol

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

Citations6
Published2023
Admission routes2
Has abstractyes

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