Cauda Equina Syndrome in Ankylosing Spondylitis: Challenges in Diagnosis, Management, and Pathogenesis
Bibliographic record
Abstract
OBJECTIVE: Cauda equina syndrome (CES) is a rare neurologic complication of longstanding ankylosing spondylitis (AS). It is unclear what causes CES, and no proven or effective therapy has been reported to date. We have encountered 6 patients with longstanding AS diagnosed with CES. We set about to study their features, review the literature, and generate hypotheses regarding pathophysiology, as well as to speculate on the possibilities of early recognition and prevention. METHODS: We obtained permission from 6 patients with longstanding AS and CES to access their medical records and imaging studies for research purposes related to this paper. We collected and reviewed each patient's medical history, imaging studies, disease duration, past therapies especially those that relate to AS, laboratory data, as well as any treatment they received for CES and followup results of each case to the present time. RESULTS: The 6 cases of CES with AS have remarkable similarity to each other in that several decades of the disease had passed before neurologic symptoms and later signs appeared. All cases have fused spines and facet joints without spinal fractures, spinal stenosis, or disc herniation. CONCLUSION: CES is a rare yet debilitating neurologic complication of longstanding AS. The pathophysiology and treatments are far from clear. We postulate that chronic enthesitis of the vertebral column initiates the process that results in dural stiffening and formation of ectasias, causing downstream nerve root damage.
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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 | 0.005 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.001 | 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".