Medial Branch Blocks for Diagnosis of Facet Joint Pain Etiology and Use in Chronic Pain Litigation
Bibliographic record
Abstract
A commonly disputed medicolegal issue is the documentation of the location, degree, and anatomical source of an injured plaintiff's ongoing pain, particularly when the painful region is in or near the spine, and when the symptoms have arisen as result of a relatively low speed traffic crash. The purpose of our paper is to provide health and legal practitioners with strategies to identify the source of cervical pain and to aid triers of fact (decision makers) in reaching better informed conclusions. We review the medical evidence for the applications and reliability of cervical medial branch nerve blocks as an indication of painful spinal facets. We also present legal precedents for the legal admissibility of the results of such diagnostic testing as evidence of chronic spine pain after a traffic crash. Part of the reason for the dispute is the subjective nature of pain, and the fact that medical documentation of pain complaints relies primarily on the history given by the patient. A condition that can be documented objectively is chronic cervical spine facet joint pain, as demonstrated by medial branch block (injection). The diagnostic accuracy of medial branch blocks has been extensively described in the scientific medical literature, and evidence of facet blocks to objectively document chronic post-traumatic neck pain has been accepted as scientifically reliable in courts and tribunals in the USA, Canada and the United Kingdom. We conclude that there is convincing scientific medical evidence that the results of cervical facet blocks provide reliable objective evidence of chronic post-traumatic spine pain, suitable for presentation to an adjudicative decision maker.
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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 | 0.004 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".