The effect of chronic, non-specific low back pain on superficial lumbar muscle activity: a protocol for a systematic review and meta-analysis
Bibliographic record
Abstract
INTRODUCTION: Chronic, non-specific low back pain is a major global cause of disability. One factor which might potentially contribute to ongoing pain is maladaptive variation in the level of activity in the lumbar musculature. Several studies have investigated this activity using surface electromyography, in varied muscles and during a number of functional activities. Due to differences in the applied methodology, the results have been difficult to compare, and previous reviews have been limited in scope. In this protocol, we aim to perform a comprehensive review of the effect of chronic low back pain on lumbar muscle activity. METHODS AND ANALYSIS: This protocol was informed by the Preferred Reporting Items for Systematic Review and Meta-analysis Protocols (PRISMA-P) and results will be reported in line with the PRISMA. Searches will be conducted on the Web of Science, PubMed, MEDLINE, EMBASE, ZETOC and CINAHL databases, along with a comprehensive review of grey literature and key journals. One reviewer will conduct the searches, but two independent reviewers will screen potential studies and assess the risk of bias within studies which meet the inclusion criteria. The Newcastle-Ottawa risk of bias tool, and the Grading of Recommendations, Assessment, Development and Evaluation (GRADE) guidelines will be used to assess the quality of the data. Meta-analysis will be conducted where appropriate on groups of studies with homogenous methodology. Where studies are too heterogeneous to allow for meta-analysis, meta-synthesis will instead be completed, comparing results in terms of net increases or decreases of activity. ETHICS AND DISSEMINATION: This review aims to identify common adaptations of muscle activity in people with low back pain and it is expected that the results will influence future research directions and future rehabilitation approaches. The results will be submitted for publication in a peer-reviewed journal and presented at conferences. PROSPERO REGISTRATION NUMBER: CRD42019125156.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.119 | 0.176 |
| Meta-epidemiology (narrow) | 0.007 | 0.006 |
| Meta-epidemiology (broad) | 0.020 | 0.031 |
| Bibliometrics | 0.012 | 0.012 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.007 | 0.005 |
| Research integrity | 0.012 | 0.010 |
| Insufficient payload (model declined to judge) | 0.055 | 0.009 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".