Physical measures of physical functioning as prognostic factors to predict outcomes in low back pain: A systematic review and narrative synthesis
Bibliographic record
Abstract
BACKGROUND: Low back pain (LBP) remains a major global health challenge. Effective management of LBP requires prognostic research to identify people at risk of poor outcome, enabling timely and targeted interventions. OBJECTIVE: To synthesize the evidence for physical measures of physical functioning as prognostic factors for predicting outcome in LBP. METHODS: This systematic review followed PRISMA and published protocol [PROSPERO-CRD42023406796] [1]. Searches were conducted in MEDLINE, EMBASE, CINAHL, Scopus and ProQuest Dissertations/Theses from inception to 29/5/2024. Hand searches of key journals and screening reference lists of included studies was performed. Prospective longitudinal studies, evaluating physical measures of physical functioning as prognostic factors, in adults 18years≥ with LBP and/or LBP-related leg pain were included. LBP related to malignancy, fracture, infection, cauda equina, inflammatory conditions, and measures; imaging, EMG, and motion capture with force plates or 3D video analysis were excluded. Two independent reviewers screened articles, extracted data, assessed risk of bias (RoB) using QUIPS. Due to high heterogeneity a narrative synthesis was conducted and GRADE determined the quality of evidence. RESULTS: From 15,889 citations, 42 studies were included, with 50% assessed as high RoB. Low-quality evidence supports no predictive ability of high isometric back extension endurance, high handgrip strength, and high fingertip-to-floor test for good long term LBP outcomes. Very low-quality evidence supports inconsistent predictive ability of high lumbar extension range of motion and high straight leg raise range for good short-term outcomes, and high isometric back flexion endurance for good long-term LBP outcome. For studies that could not be synthesized, 41 physical measures of physical functioning were investigated, with 23 of them showing promising predictive ability for LBP outcome. CONCLUSION: This review highlights a lack of high-quality evidence regarding the predictive ability of physical measures of physical functioning in LBP. Findings indicate that the existing evidence is low-quality for no predictive ability and very low-quality for inconsistent predictive ability of physical measures of physical functioning. Low/very low-quality evidence suggests cautious interpretation. Imprecision, high RoB studies, and inadequately controlled confounding factors contributed to low/very low-quality evidence. This review also identifies emerging potential prognostic factors. An adequately powered, low RoB prospective longitudinal study using standardized measurement protocols and multivariable analysis is required to further investigate the promising predictive ability of physical measures of physical functioning in LBP. Future prognostic research should be grounded in strong theoretical rationale, including biological plausibility.
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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 | 0.036 | 0.124 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.013 | 0.012 |
| Bibliometrics | 0.016 | 0.013 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.000 |
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".