Inflammatory Type Focal Cerebral Arteriopathy of the Posterior Circulation in Children: a comparative cohort study
Bibliographic record
Abstract
Abstract Background Inflammatory type Focal Cerebral Arteriopathy (FCA-i) in the anterior circulation (AC) is well characterized and the FCA severity score (FCASS) reflects the severity of disease. We identified cases of FCA-i in the posterior circulation (PC) and adapted the FCASS to describe these cases. Methods Patients from the Swiss NeuroPaediatric Stroke Registry (SNPSR) with ischemic stroke in the PC and AC due to FCA-i and available neuroimaging were gathered. Comparison of data regarding Pediatric National Institutes of Health Stroke Scale (pedNIHSS) score and Pediatric Stroke Outcome Measure (PSOM) and FCASS was performed. We estimated infarct size by the modified pediatric Alberta Stroke Program Early Computed Tomography Score (pedASPECTS) in children with AC stroke and the adapted Bernese posterior diffusion-weighted imaging (DWI) score in the PC. Results Thirty-six children with a median age of 6.3 years ([IQR 2.8,8.6; range 0.9,15.6], 21 males, 58.3%) with FCA-i were identified. The total incidence rate was 0.151/100 000/year (95%CI 0.109–0.209). Seven had PC FCA-i and 5 had FCA-i in both circulations. Time to final FCASS was longer in the PC compared to AC, evolution of FCASS did not differ. Initial pedNIHSS was highest in children with FCA-i in the PC with a median of 8.0 (IQR 5.0-18.0), compared to 4.5 (IQR 2.0-8.0) in those with AC FCA-i and 6.0 (IQR 6.0-6.0) with involvement of both AC and PC. Different to the anterior cases PC infarct volume did not correlate with higher discharge, maximum or final FCASS scores (R 0.25, 0.35, 0.54). Conclusion The PC is affected in up to one third of cases of FCA-i. These cases should be included in future investigations on FCA-i. Although it did not correlate with clinical outcome in our cohort, the modified FCASS may well serve as a marker for the evolution of the arteriopathy in posterior FCA-i.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".