Bibliographic record
Abstract
Background and aims: Specialized transport teams have been shown to reduce complications and mortality during interhospital transfers of critically ill patients. In Quebec, the Centre Hospitalier Universitaire de Sherbrooke (CHUS) is the only center with a specialized pediatric transport team. Aims: The aim of this study was to describe the interhospital transports of all patients admitted to our PICU. Methods: Charts of all patients admitted to the PICU within 12 hours of their arrival at the CHUS after being transferred from a remote center, from 2008 to 2011, were reviewed. Demographics, medical conditions, reason for transfer, complications, interventions and delays during transport were collected and compared between the specialized team and referring center team. The IRB waived the need for informed consent. Results: One hundred and fifty one transfers were analysed, 44% by the specialized team. The median age was 1.5 years and 61% were males. The most frequent reason for transfer was respiratory distress (40%). The patients transferred by the specialized team were more severely ill (PRISM ≥ 6: 21% vs 11%), and more frequently intubated (30% vs 6%) or on non-invasive mechanical ventilation (6% vs 0%). During transport, desaturation was more frequently observed (19% PICU vs 4%); however there was no significant difference in other types of complications and no patient needed intubation. The PIM was reduced by 0.12% vs 0% during transport time. Conclusions: This study portrays transports by the first and only pediatric transport team in Quebec. We think it is mandatory all critically ill pediatric patients be transferred to a PICU by a specialized transport team.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.572 | 0.408 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".