Early identification of NORSE and transfer to care setting with appropriate supports: A proposed algorithm
Bibliographic record
Abstract
New-onset refractory status epilepticus (NORSE) is a clinical presentation where an individual develops refractory status epilepticus without active epilepsy, or related neurological conditions. A subset of these individuals has a preceding fever and would be diagnosed with febrile infection-related epilepsy syndrome (FIRES). The underlying etiology of this condition varies and includes autoimmune and viral encephalitides. These conditions require multiple specialized health care teams working collaboratively and specific resources for investigation of the underlying etiology and management to provide optimal patient care. In this paper, we provide: (1) recommendations upon early recognition of NORSE and FIRES, (2) guidance on the resources needed to optimally provide care, and (3) guidance on considerations to initiate transfer of patients to a more specialized medical center. Additional recommendations for resource-austere centers without the ability to transfer such patients are also discussed. These recommendations are only for adult patients with NORSE as pediatric patients may require additional special considerations.
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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 | 0.005 | 0.018 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.005 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.005 | 0.006 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.012 | 0.004 |
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".