Time to Asthma-Related Readmission in Children Admitted to the ICU for Asthma*
Bibliographic record
Abstract
OBJECTIVES: To compare the time to asthma-related readmissions between children with a previous ICU hospitalization for asthma and those with a non-ICU hospitalization and to explore predictors of time to readmission in children admitted to the ICU. DESIGN: Retrospective cohort study using a pan-Canadian administrative inpatient database from April 1, 2008, to March 31, 2014. SETTING: All adult and pediatric Canadian hospitals. SUBJECTS: Children 2-17 years old with a hospitalization for asthma. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: A total of 26,168 children were hospitalized 33,304 times during the study period. The time to readmission was shorter in the ICU group compared with the non-ICU group (median time to readmission 27 mo in ICU vs 35 mo in non-ICU group). Preschool-aged children (hazard ratio, 1.48; 95% CI, 1.02-2.14) and increased length of stay (hazard ratio, 1.63; 95% CI, 1.17-2.27) were associated with a shorter time to readmission. CONCLUSIONS: Children previously admitted to the ICU for asthma had a shorter time to asthma-related readmission, compared with children who did not require intensive care, underlining the importance of targeted long-term postdischarge follow-up of these children. Children of preschool age and who have a lengthier hospital stay are particularly at risk for future morbidity.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".