International Survey of Critically Ill Children With Acute Neurologic Insults: The Prevalence of Acute Critical Neurological Disease in Children: A Global Epidemiological Assessment Study*
Bibliographic record
Abstract
OBJECTIVE: The international scope of critical neurologic insults in children is unknown. Our objective was to assess the prevalence and outcomes of children admitted to PICUs with acute neurologic insults. DESIGN: Prospective study. SETTING: Multicenter (n = 107 PICUs) and multinational (23 countries, 79% in North America and Europe). PATIENTS: Children 7 days to 17 years old admitted to the ICU with new traumatic brain injury, stroke, cardiac arrest, CNS infection or inflammation, status epilepticus, spinal cord injury, hydrocephalus, or brain mass. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: We evaluated the prevalence and outcomes of children with predetermined acute neurologic insults. Child and center characteristics were recorded. Unfavorable outcome was defined as change in pre-post insult Pediatric Cerebral Performance Category score greater than or equal to 2 or death at hospital discharge or 3 months, whichever came first. Screening data yielded overall prevalence of 16.2%. Of 924 children with acute neurologic insults, cardiac arrest (23%) and traumatic brain injury (19%) were the most common. All-cause mortality at hospital discharge was 12%. Cardiac arrest subjects had highest mortality (24%), and traumatic brain injury subjects had the most unfavorable outcomes (49%). The most common neurologic insult was infection/inflammation in South America, Asia, and the single African site but cardiac arrest in the remaining regions. CONCLUSIONS: Neurologic insults are a significant pediatric international health issue. They are frequent and contribute substantial morbidity and mortality. These data suggest a need for an increased focus on acute critical neurologic diseases in infants and children including additional research, enhanced availability of clinical resources, and the development of new therapies.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".