Current evidence for spinal X-ray use in the chiropractic profession: a narrative review
Bibliographic record
Abstract
The use of routine spinal X-rays within chiropractic has a contentious history. Elements of the profession advocate for the need for routine spinal X-rays to improve patient management, whereas other chiropractors advocate using spinal X-rays only when endorsed by current imaging guidelines. This review aims to summarise the current evidence for the use of spinal X-ray in chiropractic practice, with consideration of the related risks and benefits. Current evidence supports the use of spinal X-rays only in the diagnosis of trauma and spondyloarthropathy, and in the assessment of progressive spinal structural deformities such as adolescent idiopathic scoliosis. MRI is indicated to diagnose serious pathology such as cancer or infection, and to assess the need for surgical management in radiculopathy and spinal stenosis. Strong evidence demonstrates risks of imaging such as excessive radiation exposure, overdiagnosis, subsequent low-value investigation and treatment procedures, and increased costs. In most cases the potential benefits from routine imaging, including spinal X-rays, do not outweigh the potential harms. The use of spinal X-rays should not be routinely performed in chiropractic practice, and should be guided by clinical guidelines and clinician judgement.
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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 | 0.002 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".