Physical measures of physical functioning as prognostic factors in predicting outcomes for neck and thoracic pain: Protocol for a systematic review
Bibliographic record
Abstract
BACKGROUND: Spinal pain is prevalent and burdensome worldwide. A large proportion of patients with neck and thoracic pain experience chronic symptoms, which can significantly impact their physical functioning. Therefore, it is important to understand factors predicting outcome to inform effective examination and treatment. Knowledge of physical measures of physical functioning as prognostic factors can enhance patient-centered care and aid decision-making. The evidence regarding physical outcome measures as prognostic factors for neck and thoracic pain is unclear. The objective of this study is to summarize the evidence for physical outcome measures of physical functioning as prognostic factors in predicting outcomes in people with neck and thoracic pain. METHODS AND ANALYSIS: This systematic review follows Cochrane guidelines and aligns with the Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols (PRISMA-P). Included studies will be prospective longitudinal cohort studies in which physical measures of physical functioning are explored as prognostic factors for adults with neck and thoracic pain. A comprehensive search will be performed in key databases (MEDLINE, EMBASE, CINAHL, Scopus, and Web of Science) and the grey literature, with hand searches of key journals, and the reference lists of included studies. Two reviewers will independently perform study selection, data extraction, risk of bias assessment (QUIPS, Quality in Prognostic Studies tool), and quality assessment (Grading of Recommendations Assessment, Development, and Evaluation). IMPLICATIONS: This systematic review will identify physical measures of physical functioning prognostic factors for neck and thoracic pain populations. Findings will inform researchers about gaps in existing evidence, and clinicians about factors to aid their clinical decisions and to enhance the overall quality of care for individuals with neck and thoracic pain.
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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 | 0.072 | 0.114 |
| Meta-epidemiology (narrow) | 0.006 | 0.005 |
| Meta-epidemiology (broad) | 0.019 | 0.022 |
| Bibliometrics | 0.012 | 0.012 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.009 | 0.008 |
| Open science | 0.005 | 0.005 |
| Research integrity | 0.008 | 0.008 |
| Insufficient payload (model declined to judge) | 0.065 | 0.008 |
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".