The Spectrum of Influenza-Associated Acute Necrotizing Encephalopathy of Childhood: A Case Series
Bibliographic record
Abstract
BACKGROUND: Acute necrotizing encephalopathy of childhood (ANEC) is a rare inflammatory neurological disease with characteristic neuroimaging findings commonly leading to disability or death. It is associated with a variety of infectious agents, most commonly influenza. METHODS: This study is a retrospective case series describing three children presenting with ANEC during the 2023-2024 influenza season. RESULTS: All patients were influenza A positive with a variable duration of prodromal infectious symptoms. Each presented with witnessed or suspected seizures and persistent encephalopathy. Initial computed tomography (CT) was unremarkable in two patients; however, on follow-up neuroimaging all evolved multifocal brain lesions, including symmetric bilateral thalamic involvement consistent with ANEC. All patients received intravenous pulse methylprednisolone, but the timing and selection of additional immunomodulatory interventions differed between patients. Outcomes spanned from slight disability to death. CONCLUSIONS: These patients illustrate the spectrum of ANEC presentations and outcomes and underscore the importance of prompt investigations in children with persistent encephalopathy and prodromal infectious symptoms, even with unremarkable findings on initial CT. The variability in treatment and outcomes within a single center emphasizes the need for further research to establish a better pathophysiologic understanding of ANEC and optimal treatment protocols.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".