Implementation of a Multicenter Rapid Response System in Pediatric Academic Hospitals Is Effective
Bibliographic record
Abstract
OBJECTIVES: This is the first large multicenter study to examine the effectiveness of a pediatric rapid response system (PRRS). The primary objective was to determine the effect of a PRRS using a physician-led team on the rate of actual cardiopulmonary arrests, defined as an event requiring chest compressions, epinephrine, or positive pressure ventilation. The secondary objectives were to determine the effect of PRRSs on the rate of PICU readmission within 48 hours of discharge and PICU mortality after readmission and urgent PICU admission. METHODS: A PRRS was developed, implemented, and evaluated in a standardized manner across 4 pediatric academic centers in Ontario, Canada. The team responded to activations for inpatients and followed patients discharged from the PICU for 48 hours. A 2-year, prospective, observational study was conducted after implementation, and outcomes were compared with data collected 2 years before implementation. RESULTS: After PRRS implementation, there were 55 963 hospital admissions and a team activation rate of 44 per 1000 hospital admissions. There were 7302 patients followed after PICU discharge. Implementation of the PRRS was not associated with a reduction in the rate of actual cardiopulmonary arrests (1.9 vs 1.8 per 1000 hospital admissions; P=.68) or PICU mortality after urgent admission (1.3 vs 1.1 per 1000 hospital admissions; P=.25). There was a reduction in the PICU mortality rate after readmission (0.3 vs 0.1 death per 1000 hospital admissions; P=.05). CONCLUSION: The standardized implementation of a multicenter PRRS was associated with a decrease in the rate of PICU mortality after readmission but not actual cardiopulmonary arrests.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.020 | 0.053 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 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".