3 In-Hospital Child Mortality after Consolidation of Two Pediatric Intensive Care Units
Bibliographic record
Abstract
Abstract Background While high-volume specialized Pediatric Intensive Care Units (PICUs) increase the survival of critically ill children, the benefits of consolidating PICUs to a single site may be outweighed by the need to transport critically ill children when the area serviced has a low population density and vast geography. Objectives This study seeks to describe the impact of PICU consolidation on mortality of children from the southern part of a Canadian province, after presentation to nearest hospital, following consolidation of PICUs to a single more centrally located PICU. Design/Methods We conducted a retrospective chart review of children with a primary residence in the southern part of the province, who died between January 2008 and December 2017 after presentation to the nearest hospital. Children who died prior to presentation to hospital or did not have return of spontaneous circulation at any time after presentation were excluded from analysis. Child demographics, year of death, cause of death, and Pediatric Risk of Mortality III (PRISM III) score, and duration and type of treatments provided were abstracted from health records. Population census data was obtained from the 2016 Canada Census. Deaths were grouped for analysis according to the child’s place of residence within three specific administrative areas. Nonparametric Mann Whitney U-test was used for descriptive analysis. Results Eighty-six (86) children from the southern part of the province died following presentation to the nearest hospital during the 10-year study period. The observed population rate of in-hospital deaths was 6.8 per 100,000 children per year before consolidation and 8.5 per 100,000 children per year after consolidation of PICU services. Variation in the population rate of in-hospital deaths before and after consolidation of PICUs was observed between administrative areas (p=0.016). The data did not appear to show an association with urban or non-urban areas. Children who died after consolidation were more likely to receive pain relief (p=0.013), and palliative care consultation (p=0.005) than those who died prior to consolidation. No change in acuity at presentation to hospital or cause of death was observed following PICU consolidation (p=0.3). Conclusion This study did not find evidence of a change in the rate of in-hospital child deaths per 100,000 children following consolidation of PICU services in a Canadian province.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".