Bibliographic record
Abstract
PURPOSE OF THE REVIEW: To summarize the current literature on central nervous system vasculitis in childhood because this condition remains a diagnostic and therapeutic challenge. RECENT FINDINGS: Central nervous system vasculitis in childhood may be primary or secondary to a variety of conditions including infections, collagen vascular diseases, systemic vasculitides, and malignancies. Conditions that result in vasospasm or are associated with noninflammatory vasculopathies may mimic the features of central nervous system vasculitis. Recent studies have described the clinical spectrum of CNS vasculitis in childhood. The most common presenting features are headaches and focal neurologic deficits. The diagnosis of central nervous system vasculitis remains particularly difficult because the available investigative modalities have limited sensitivities and specificities. The most helpful diagnostic tests include cerebrospinal fluid analysis, MRI of the brain, and angiography. However, brain biopsy may be required to diagnose small vessel vasculitis. SUMMARY: This review summarizes recent data on primary central nervous system vasculitis and some of the secondary CNS vasculitides in children. Awareness of the presenting clinical features of CNS vasculitis should lead to consideration of the diagnosis. Awareness of the sensitivity and specificity of the various diagnostic tests should lead to the more prudent use of invasive diagnostic tests including angiography and brain biopsy.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".