Idiopathic Hypertrophic Pachymeningitis: A Report of Two Patients and Review of the Literature
Bibliographic record
Abstract
PURPOSE: We report the treatment and follow-up, including MRI, of two patients with idiopathic hypertrophic pachymeningitis and review the English language literature, with emphasis on management and outcome in this rare disorder. METHODS AND MATERIALS: The files of two patients were reviewed, with relevant histopathology and imaging (MRI). The first patient has been followed for sixteen years (the longest MRI-documented postoperative course reported for this condition) and the second for two years. The English language literature was reviewed, including a summary of all reported patients that have been followed with MRI or CT imaging. RESULTS: Despite extensive investigation, no underlying etiology was determined in either patient. Histopathological studies revealed a chronic inflammatory dural infiltrate in both patients, with granulomas in the first but not the second patient. The first patient underwent surgery twice and has remained stable for sixteen years, despite persistent neurologic deficits. The second patient was managed with dexamethasone after a surgical biopsy, and experienced complete resolution of all neurological deficits and abnormalities seen with MRI. CONCLUSIONS: Although prompt and extensive surgery has been recommended for this condition, the results from our second patient indicate that complete remission can be achieved in some patients with biopsy and steroid therapy. This also supports the view that autoimmune mechanisms underlie idiopathic hypertrophic pachymeningitis. The first patient illustrates that extensive laminectomies may be an effective therapeutic option but chronic discomfort may result. If extensive surgery must be performed, laminoplasty should be done because of the potential for reduced pain and improved long-term spinal stability.
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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 | 0.001 | 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 | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.004 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".