Association between clinical findings and the presence of lumbar spine osteoarthritis imaging features: A systematic review
Bibliographic record
Abstract
OBJECTIVE: Spinal osteoarthritis is difficult to study and diagnose, partly due to the lack of agreed diagnostic criteria. This systematic review aims to give an overview of the associations between clinical and imaging findings suggestive of spinal osteoarthritis in patients with low back pain to make a step towards agreed diagnostic criteria. DESIGN: We searched MEDLINE, Embase, Web of Science, and CINAHL from inception to April 29, 2021 to identify observational studies in adults that assessed the association between selected clinical and imaging findings suggestive of spinal osteoarthritis. Risk of bias was assessed using the Newcastle Ottawa Scale and the quality of evidence was graded using an adaptation of the GRADE approach. RESULTS: After screening 7902 studies, 30 met the inclusion criteria. High-quality evidence was found for the longitudinal association between low back pain (LBP) intensity, and both disc space narrowing and osteophytes, as well as for the association between LBP-related physical functioning and lumbar disc degeneration, the presence of spinal morning stiffness and disc space narrowing and for the lack of association between physical functioning and Schmorl's nodes. CONCLUSIONS: There is high- and moderate-quality evidence of associations between clinical and imaging findings suggestive of spinal osteoarthritis. However, the majority of the studied outcomes had low or very low-quality of evidence. Furthermore, clinical and methodological heterogeneity was a serious limitation, adding to the need and importance of agreed criteria for spinal osteoarthritis, which should be the scope of future research.
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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 | 0.010 | 0.058 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.006 |
| Bibliometrics | 0.009 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".