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Record W1877178298 · doi:10.1016/j.jmpt.2015.06.001

The Effectiveness of Noninvasive Interventions for Musculoskeletal Thoracic Spine and Chest Wall Pain: A Systematic Review by the Ontario Protocol for Traffic Injury Management (OPTIMa) Collaboration

2015· review· en· W1877178298 on OpenAlexafffundabout
Danielle Southerst, Andrée-Anne Marchand, Pierre Côté, Heather M. Shearer, Jessica J. Wong, Sharanya Varatharajan, Kristi Randhawa, Deborah Sutton, Hainan Yu, Douglas P. Gross, Craig Jacobs, Rachel Goldgrub, Maja Stupar, Silvano Mior, Linda Carroll, Anne Taylor‐Vaisey

Bibliographic record

VenueJournal of Manipulative and Physiological Therapeutics · 2015
Typereview
Languageen
FieldMedicine
TopicMusculoskeletal pain and rehabilitation
Canadian institutionsCentre for Disability Prevention and RehabilitationUniversity of AlbertaOntario Tech UniversityCanadian Memorial Chiropractic CollegeMount Sinai Hospital
FundersCanadian Institutes of Health Research
KeywordsMedicineCINAHLPhysical therapyMEDLINERandomized controlled trialAcupuncturePsychological interventionElectrotherapySystematic reviewChiropracticPsycINFOEvidence-based medicinePhysical medicine and rehabilitationAlternative medicineSurgery

Abstract

fetched live from OpenAlex

OBJECTIVE: The purpose of this study was to critically appraise and synthesize evidence on the effectiveness of noninvasive interventions, excluding pharmacological treatments, for musculoskeletal thoracic pain. METHODS: Randomized controlled trials (RCTs), cohort studies, and case-control studies evaluating the effectiveness of noninvasive interventions were eligible. We searched MEDLINE, EMBASE, PsycINFO, and the Cochrane Central Register of Controlled Trials accessed through Ovid Technologies, Inc, and CINAHL Plus with Full Text accessed through EBSCOhost from 1990 to 2015. Our search strategies combined controlled vocabulary relevant to each database (eg, MeSH for MEDLINE) and text words relevant to our research question and the inclusion criteria. Random pairs of independent reviewers screened studies for relevance and critically appraised relevant studies using the Scottish Intercollegiate Guidelines Network criteria. Studies with a low risk of bias were synthesized following best evidence synthesis principles. RESULTS: We screened 6988 articles and critically appraised 2 studies. Both studies had a low risk of bias and were included in our synthesis. One RCT compared thoracic spinal manipulation, needle acupuncture, and placebo electrotherapy for recent thoracic spine pain. There were statistically significant but clinically nonimportant short-term reductions in pain favoring manipulation. There were no differences between acupuncture and placebo electrotherapy. Another RCT compared a multimodal program of care and a session of education for recent musculoskeletal chest wall pain. The multimodal care resulted in statistically significant but clinically nonimportant short-term reductions in pain over education. However, participants receiving multimodal care were more likely to report important improvements in chest pain. CONCLUSIONS: Quality evidence on the management of musculoskeletal thoracic pain is sparse. The current evidence suggests that compared to placebo, spinal manipulation is associated with a small and clinically nonimportant reduction in pain intensity and that acupuncture leads to similar outcomes as placebo. Furthermore, a multimodal program of care (ie, manual therapy, soft tissue therapy, exercises, heat/ice, and advice) and a single education session lead to similar pain reduction for recent-onset musculoskeletal chest wall pain. However, patients who receive multimodal care are more likely to report pain improvements.

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)0.071
metaresearch head score (Gemma)0.131
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: none
Teacher disagreement score0.980
Threshold uncertainty score0.375

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0710.131
Meta-epidemiology (narrow)0.0040.003
Meta-epidemiology (broad)0.0160.013
Bibliometrics0.0190.019
Science and technology studies0.0040.003
Scholarly communication0.0060.005
Open science0.0050.005
Research integrity0.0040.003
Insufficient payload (model declined to judge)0.0190.002

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 head0.252
GPT teacher head0.473
Teacher spread0.220 · 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

Citations21
Published2015
Admission routes3
Has abstractyes

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