Factors Associated with Death in the Emergency Department among Children Dying of Complex Chronic Conditions: Population-Based Study
Bibliographic record
Abstract
OBJECTIVES: To determine the percentage of deaths occurring or confirmed in an emergency department (ED) among children dying of complex chronic conditions and identify factors associated with that percentage. METHODS: The population and variables of this population-based study were derived from three administrative databases. The study focuses on all children aged 1-19 years who died of complex chronic conditions in Quebec in 1997-2001. Children not hospitalized on seventh day before death were considered at risk of ED death at that time. The percentage of ED deaths was measured in association with year of death, sociodemographic characteristics, outpatient visits, and hospitalizations in the last 6 months of life. RESULTS: Among all 506 deaths, 13.8% died in an ED. Among the 300 children not hospitalized on the seventh day before death, 21.7% had an ED death. Compared to children dying from malignancies, the adjusted odds of ED deaths were higher for those with cardiovascular conditions (odds ratio [OR] = 6.3; 95% confidence interval [CI] = 2.3-17.5), metabolic and other congenital or genetic defect (OR = 4.5; 95% CI = 1.5-13.5) and neuromuscular conditions (OR = 3.7; 95% CI = 1.5-9.4). The adjusted odds of ED deaths increased over time and were lower for children with hospitalizations in tertiary pediatric centers (OR = 0.3; 95% CI = 0.1-0.8), compared to those with no hospitalization. CONCLUSIONS: EDs play an important role in end-of-life care of children with complex chronic conditions. Multidisciplinary teams of tertiary pediatric centers may be better able to assess prognosis and provide appropriate advanced care planning.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".