Characteristics, outcome and treatments with cranial pachymeningitis
Bibliographic record
Abstract
The aim of this study was to determine the characteristics, treatment, and outcome according to each etiology of pachymeningitis.We conducted a retrospective multicenter French nationwide study between 2000 and 2016 to describe the characteristics, outcome, and treatment of pachymeningitis.We included 60 patients (median age 55.5 years; interquartile range [IQR] 30-80, female/male ratio 0.43). Neurologic signs were present in 59 patients (98%) and consisted of headache in 43 (72%), cranial nerve palsy in 33 (55%), confusion in 10 (17%), seizures in 7 (12%), and focal neurologic signs in 9 (15%). Fever and weight loss were present in 8 (13%) and 13 cases (22%), respectively. Cerebral venous thrombosis was present in 8 cases (13%). Analysis of cerebrospinal fluid showed moderate hyperproteinorachia (median 0.68 g/L; IQR 0.46-3.2) with or without pleiocytosis. Diagnosis included idiopathic pachymeningitis (n = 18; 30%); granulomatosis with polyangiitis (n = 13; 17%); Erdheim-Chester disease (n = 10; 17%); IgG4-related disease and tuberculosis (n = 3; 5% each); Rosai-Dofman disease, microscopic polyangiitis, and sarcoidosis (n = 2, 3% each); cryptococcal meningitis, Lyme disease, ear-nose-throat infection, postlumbar puncture, low spinal-fluid pressure syndrome, and lymphoma (n = 1 each). We found no difference in demographics and neurologic presentation among idiopathic pachymeningitis, Erdheim-Chester disease, and granulomatosis with polyangiitis. In contrast, frequencies were lower with idiopathic pachymeningitis than Erdheim-Chester disease for general signs (6% and 40%, respectively, P = .041) and complete neurologic response (0% vs 39%, P = .045).The detection of extraneurologic signs and routine screening are needed to classify the pachymeningitis origin. Prospective studies are warranted to determine the best treatment in each case.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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 teacher head, 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".