Evaluating associations between late intensive care admission and mortality, intensive care days, and organ dysfunctions: a secondary analysis of data from the EPOCH cluster randomized trial
Bibliographic record
Abstract
Abstract Purpose To determine whether late admission to pediatric intensive care (ICU) from hospital wards is associated with patient outcomes. Methods Secondary analysis of prospectively collected data from an international multicenter cluster-randomized trial. Clinical deterioration events with urgent ICU admission were defined as late if the Children’s Resuscitation Intensity Scale was > 2 (indicating critical care interventions started from 12 h pre- to 1 h post-urgent ICU admission). The association of late admission with primary outcomes (ICU and hospital mortality) was estimated using logistically generalized estimating equation models adjusted for PIM2 probability of death. Results There were 2979 clinical deterioration events in 2502 patients, including 620 (20.8%) late ICU admissions. ICU mortality of the last urgent ICU admission was 15.4% for late compared to 4.5% for non-late ICU admission (PIM-adjusted OR (95%CI) 1.63 (1.14, 2.33), p < 0.01). Hospital mortality was 19.7% in late compared to 6.0% for non-late urgent ICU admission (PIM-adjusted OR 1.56 (1.12, 2.16), p < 0.01). Late ICU admissions accounted for 20.9% of clinical deterioration events, and 90/179 (50.2.0%) of ICU and 103/222 (46.4%) of hospital deaths after clinical deterioration events. Secondary outcomes associated with late ICU admission included longer ICU stay (2.3 days, p = 0.02), more ventilation days (407/1000 ICU days, p < 0.0001), and more frequent treatment with dialysis, inhaled nitric oxide, and extracorporeal membrane oxygenation (p < 0.01). Conclusion Late ICU admission from hospital wards was associated with higher ICU and hospital mortality, greater use of ICU technologies, and longer ICU stays. How to prevent late ICU admission and its consequences requires further study.
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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 | 0.007 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.005 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".