Discharge Directly Home From the PICU: A Retrospective Cohort Study
Bibliographic record
Abstract
OBJECTIVE: Healthcare constraints with decreasing bed availability cause strain in acute care units, and patients are more frequently being discharged directly home. Our objective was to describe the population, predictors, and explore PICU readmission rates of patients discharged directly home from PICU, compared with those discharge to the hospital ward, then home. DESIGN: An observational cohort study. SETTING: Children admitted to the PICU of CHU Sainte-Justine, between January 2014 and 2020. PATIENTS: Patients less than 18 years old, who survived their PICU stay, and were discharged directly home or to an inpatient ward. Patients discharged directly home were compared with patients discharged to the ward using descriptive statistics. Logistic regression was used to identify factors associated with home discharge. Propensity scores were used to compare PICU readmission rates in patients discharged directly home to those discharged to the ward. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Among the 5,531 admissions included, 594 (10.7%) were discharged directly home from the PICU. Patients who were more severe ill (odds ratio [OR], 0.93; 95% CI, 0.90-0.97), had invasive ventilation (OR, 0.70; 95% CI, 0.53-0.92), or had vasoactive agents (OR, 0.70; 95% CI, 0.53-0.92) were less likely to be discharged directly home. Diagnoses associated with discharge directly home were acute intoxication, postoperative ear-nose-throat care, and shock states. There was no difference in the rate of readmission to PICU at 2 (relative risk [RR], 0.20 [95% CI, 0.02-1.71]) and 28 days (RR, 1.20 [95% CI, 0.61-3.36]) between propensity matched patients discharged to the ward for 2 or less days, compared with those discharged directly home. CONCLUSION: Discharge directly home from the PICU is increasing locally. The population includes less severely ill patients with rapidly resolving diagnoses. Rates of PICU readmission between patients discharged directly home from the PICU versus to ward are similar, but safety of the practice requires ongoing evaluation.
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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) | 0.001 | 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".