SPINAL CORD INFLAMMATION IN CHILDREN WITH SMALL VESSEL PRIMARY CNS VASCULITIS
Bibliographic record
Abstract
BACKGROUND: Small vessel childhood primary angiitis of CNS (SVcPACNS) is an increasingly recognized inflammatory brain disease requiring rapid targeted investigation and initiation of tailored therapies to prevent brain damage. Spinal cord involvement has never been systematically investigated. OBJECTIVES: To determine the presenting clinical and laboratory features, neuroimaging, treatment and outcome of children with spinal cord involvement in SVcPACNS. DESIGN/METHODS: A single center cohort study of children with small vessel primary CNS vasculitis diagnosed between 2002 and 2016 was conducted. Children were included, if they were 1) age 18years, 2) met Calabrese criteria and 3) had evidence of spinal cord inflammation. Data were captured in the BrainWorks database. Outcome: Neurological function at 12 months was determined using the Pediatric Stroke Outcome Measure; secondary outcomes included the estimated disease activity and damage. RESULTS: A total of 158 children were diagnosed with primary CNS vasculitis; 52 (33%) were found to have SVcPACNS, of whom 20 had spinal cord imaging for clinical concerns. These were 13 girls and 7 boys; median age was 10.1 years (range 5.4-17.7). The median time from onset of symptoms to diagnosis was 57 days (range 10-1041). A total of 11 (55%) had evidence of spinal inflammatory lesions on MRI. Their clinical features at diagnosis included hemiparesis (13), visual impairment (10), optic neuritis (4) and status epilepticus (4). At diagnosis, 8/9 tested (89%) had abnormal serum inflammatory markers (ESR 6/9, CRP 3/9) or vWF antigen (3/7, 42%). Raised CSF cell count was seen in 7/9 (78%). Imaging: 21 lesions were detected; the spinal lesion load was 1.9 per patient. Distribution: Nine lesions were located in the cervical, 10 in the thoracic and 2 in the lumbar spine. 17 lesions (81%) were long segments (> 3 vertebrae). Gadolinium enhancement was seen in 7/9 (78%), cord swelling in 3/11 (27%). All children were treated with the BrainWorks SVcPACNS protocol. Outcome: A total of eight patients (73%) hadno functional neurological deficit at 12 months. The median disease activity was 3/10 (range 0.5-8) and estimated disease damage 1/10 (range 0.1-3) at 12 months. CONCLUSION: One in five children with brain biopsy confirmed primary CNS vasculitis had symptomatic spinal cord inflammation. The differential diagnosis of myelitis should include SVcPACNS. Rapid diagnosis and targeted therapy may improve the outcome.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| 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".