Distinguishing features in the presentations of childhood inflammatory brain diseases at a tertiary-care centre
Bibliographic record
Abstract
A single centre cohort study was performed with consecutive children up to 18 years of age who were diagnosed with IBrainD from June 1989 to December 2010. Patients who were seen at The Hospital for Sick Children were identified by a search of the BrainWorks database. Demographic, clinical, laboratory, neuroimaging and histologic data from the time of diagnosis were collected. Data were analysed using descriptive and univariate statistical analysis. Cluster analysis will also be performed. A total of 165 children (47% females, median age 8.3 years) with IBrainD were identified: 124 primary angiitis of the central nervous system (cPACNS), 11 secondary CNS vasculitis (due to systemic lupus erythematosus in 4, systemic vasculitis in 2, Crohn’s disease in 1, and infection in 4), 6 neuronal-antibody associated syndromes, 6 post-infectious IBrainD, 4 other diagnoses (2 neurosarcoidosis, 1 channelopathy, 1 moya moya), and 14 non-specific IBrainD. Male sex (71%) and motor symptoms (87%), such as hemiparesis and ataxia, were more prominent in children with angiography-positive cPACNS compared to other IBrainD. Children with angiography-negative cPACNS (AN-cPACNS) and neuronal-antibody associated syndromes were more likely to be female (74% and 83%, respectively) and present with behaviour changes (56% and 50%) and cognitive dysfunction (35% and 50%) compared to other conditions. These two diagnoses could be further distinguished by the presence of headache in 62%, seizures in 79%, and abnormal MRI findings in 91% of patients with AN-cPACNS, compared to 17%, 33%, and 17%, respectively, in patients with neuronal-antibody associated syndromes. Differences observed in groups of symptoms (motor vs. cognitive-behaviour) at presentation should be considered in the development of distinct diagnostic criteria for the various childhood IBrainD, leading to earlier diagnosis and appropriate treatment.
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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 | 0.001 |
| 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) | 0.000 | 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".