Severe acute disseminated encephalomyelitis: a paediatric intensive care population-based study
Bibliographic record
Abstract
There is a paucity of literature on the epidemiology of severe acute disseminated encephalomyelitis (ADEM). We describe a Paediatric Intensive Care Unit (PICU) population-based study to determine the epidemiology and clinical characteristics of children with ADEM requiring PICU admission or resulting in death. Anonymized data from the Paediatric Intensive Care Audit Network (PICANet) were obtained for all children under 16 years with a diagnosis of ADEM admitted to 25 PICUs in England and Wales (2004-2008). The Office for National Statistics (ONS) mortality database was also searched. In total, 27 PICANet cases (13 females:14 males; median age 4.8 years) were ascertained and all were alive on discharge. In addition, three cases were identified from the ONS mortality database. Of the 27 PICANet cases, clinical features included; seizures (n = 5); upper airway respiratory obstruction/stridor (n = 2); unspecified encephalopathy (n = 27); and polyfocal neurological deficits (n = 6). The median duration of ventilation was 3 days. Inotropic support was required in 4/27 patients, and one patient had invasive intracranial pressure monitoring. None received plasmapheresis. We conclude that the incidence of childhood ADEM admitted to the PICU in England and Wales is approximated at 0.5 per million children/year, thus representing approximately one quarter of children admitted with ADEM (denominator: 2009 Canadian surveillance data).
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".