PP161 Topic: AS15–Lung: Respiratory Support/Acute Respiratory Failure/Other: GLOBAL COMPARISON OF THE EPIDEMIOLOGY OF PROLONGED MECHANICAL VENTILATION IN PICUS
Bibliographic record
Abstract
Aims & Objectives: Managing children requiring prolonged mechanical ventilation (PMV) in the pediatric intensive care unit (PICU) has been identified as challenging for healthcare improvement in various settings. Methods: A cross-sectional and prospective cohort study was conducted every 3 months from 2019 to 2022. PMV was defined as mechanical respiratory support for at least 15 consecutive days. We collected data on the prevalence of PMV in the PICU, healthcare resource utilization, and 90-day outcomes. Global differences in four regions (Asia/Oceania; AO, Europe; Euro, North America; NA, and South America; SA) were examined. Results: We included 2,614 patient records from 158 ICUs in 28 countries, of which 34 were in AO, 55 in Euro, 37 in NA, and 32 in SA. The median prevalence was 21.5% (14.3-33.3) in AO, 20.0% (11.3-30.0) in Euro, 21.0% (16.7-30.0) in NA, and 12.2% (0-31.7) in SA, with p=0.09. The patient-to-nursing ratios for the cases varied, with 54% in AO and 53% in NA having a ratio of 1:1, while 65% in Euro and 53% in SA had 1:2. The 90-day survival was 21.2% in AO, 18.4% in Euro, 16.1% in NA, and 19.7% in SA. The mode of death varied, with ‘withholding or withdrawal’ being the most common in AO (68.5%) and NA (82.2%), while ‘failure to resuscitate’ was more prevalent in Euro (40.3%) and SA (43.6%). Conclusions: The prevalence of children requiring PMV in the PICU is high, and their prognosis is poor, necessitating significant medical resources. This study indicates a global variability in the PMV associated healthcare burden and outcomes. Keywords: prolonged ventilation, global, prevalence, epidemiology
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".