Chiropractic Referral for Computed-Tomography Angiography to Rule Out Vertebral Artery Dissection: A Case Report
Bibliographic record
Abstract
Objective: This paper describes a case of chiropractic referral to medical emergency services for computed-tomography angiography (CTA) imaging to rule out vertebral artery dissection (VAD). Clinical Features: A 50-year-old female presented to a chiropractic physician with an idiopathic onset of neck pain, headache, nausea, and dizziness. Differential diagnosis included VAD, internal carotid artery dissection (ICAD), as well as cerebral aneurysm or other intracranial abnormality. Due to symptoms of potential VAD, the patient was referred to medical emergency services for CTA imaging to rule out VAD. CTA revealed a possible posterior communicating artery (PCom) aneurysm vs. infundibulum, and left C3-C4 facet arthropathy. No VAD was noted. Intervention/Outcome: The patient was referred to a neurosurgeon who concluded the patient's abnormality was an incidental finding of infundibulum, not an aneurysm. The patient was referred to physical therapy for treatment of the C3-C4 facet arthropathy, which resolved her symptoms. Conclusion: This case report highlights the role of chiropractors in interdisciplinary care by referring suspected non-neuromusculoskeletal conditions to medical emergency services for advanced imaging to ensure patient safety.
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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 | 0.000 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.005 | 0.002 |
| 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".