Brain biopsy in children with primary small‐vessel central nervous system vasculitis
Bibliographic record
Abstract
OBJECTIVE: Primary angiitis of the central nervous system in childhood (cPACNS) is an immune-mediated inflammatory process directed toward blood vessels in the central nervous system. It has been associated with variable clinical and radiological presentations, and devastating consequences without treatment. Brain biopsy is required for definitive diagnosis. The objective of this study was to characterize the clinical and histopathological features of brain biopsies in small-vessel cPACNS (SVcPACNS). METHODS: A single-center prospective cohort study of children diagnosed with cPACNS from 1998 to 2008 was performed. All patients with negative cerebral angiography and brain biopsy were included. Patient data were reviewed for clinical, laboratory, and radiological characteristics at presentation. Standardized brain biopsy review protocols were established, with independent analysis by 2 neuropathologists. Histopathology was correlated with collected clinical data. RESULTS: A total of 13 SVcPACNS patients were included. Ages ranged from 5 to 17 years. Presenting features included seizures (85%), headache (62%), and cognitive decline (54%). Brain biopsy confirmed SVcPACNS in 11 patients with intramural lymphocytic infiltrate. Two had nonspecific perivascular inflammation only. All 6 nonlesional biopsies yielded a diagnosis of SVcPACNS. Lack of specific histological features correlated with prolonged time to biopsy, prior steroid treatment, and inadequate specimen sampling. INTERPRETATION: In children presenting with new onset severe headaches, seizures, or cognitive decline, SVcPACNS and brain biopsy should be considered. Lesional biopsies are preferred; however, nonlesional biopsies may succeed in yielding the diagnosis. Steroid treatment prior to biopsy and inadequate biopsy sampling may obscure the diagnosis in true cases of SVcPACNS.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".