Increased Mortality and Length of Stay Associated With Medical Emergency Team Review in Hospitalized Pediatric Patients: A Retrospective Cohort Study*
Bibliographic record
Abstract
OBJECTIVE: Rapid response systems using medical emergency teams reduce hospital wide cardiorespiratory arrest and mortality. While rapid response systems improve hospital-wide outcomes, children receiving medical emergency team review may still be at increased risk for morbidity and mortality. The study purpose was to compare the length of stay and mortality rate in children receiving a medical emergency team review with those of other hospitalized children. DESIGN: Retrospective cohort study. SETTING: Tertiary Pediatric Hospital, Children's Hospital of Eastern Ontario, Ottawa, Canada. PATIENTS: Cohort of 42,308 pediatric admissions to the general inpatient ward. INTERVENTIONS: Data over 7 years were obtained from a prospectively maintained rapid response systems database. MEASUREMENTS AND MAIN RESULTS: From the cohort, 995 (2.35%) of the admissions had one and 276 (0.65%) had multiple medical emergency team activations. When compared with patients without, children having one or multiple medical emergency team reviews had 13.34 (95% CI, 5.33-33.2) and 50.10 (95% CI, 19.86-126.39) times the odds of death, respectively. Patients experiencing a medical emergency team review stayed in hospital 1.59 times (95% CI, 1.39-1.82) longer, whereas those with multiple medical emergency team reviews stayed 2.44 times (95% CI, 1.85-3.20) longer. The associations remained significant after controlling for important confounders and excluding elective admissions from the analyses. Most repeat medical emergency team reviews occurred within a day of the initial review or involved patients with multiple comorbidities. CONCLUSIONS: Our study suggests that pediatric patients reviewed by the medical emergency team are at significantly higher risk of mortality and longer length of stay than general ward inpatients. As well, patients with multiple medical emergency team reviews were at particularly high risk compared with patients with one medical emergency team review. Patients who experience medical emergency team reviews should be recognized as a high-risk group, and future studies should consider how to decrease morbidity and mortality. Based on our findings, we suggest that these patients be followed for 24-48 hours after any medical emergency team activation.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".