Epidemiology of Pediatric Critical Care Transport in Northern Alberta and the Western Arctic
Bibliographic record
Abstract
OBJECTIVE: Specialized pediatric critical care transport teams are essential to pediatric retrieval systems. This study aims to describe the contemporary transports performed by a Canadian pediatric critical care transport team and to compare the treatment and outcomes of children referred from high-level care (hospitals offering pediatric services where an adult ICU exists) and nonhigh-level care (all other hospitals) hospitals. DESIGN: A descriptive cohort study. SETTING: The Stollery Children's Hospital in Edmonton, Alberta, Western Canada. PATIENTS: Children younger than 17 years old transported by the transport team from referral hospitals within the Stollery Children's Hospital catchment area to Stollery Children's Hospital between 1998 and 2015. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Characteristics of transports, patient demographics presenting vital signs, and outcomes were described overall and compared by transport-related time and referral hospital types (high-level care and nonhigh-level care). In total, 3,352 transports met the inclusion criteria; 1,049 were retrieved from eight high-level care hospitals and 2,303 from 53 nonhigh-level care hospitals; the median one-way transport distance was 383 kilometers, and 70% of the transports were air transports. The annual number of transports has increased during the study period. The PICU admission rate was between 40% and 55%. Transports from high-level care hospitals had significantly higher odds of being admitted to the PICU (odds ratio, 1.96; 95% CI, 1.31-2.93). The odds of intubation at the referral hospital were higher in the high-level care group, but the odds of intubation upon PICU admission was similar between the two groups. Mortality during or after transport was not significantly different between high-level care and nonhigh-level care hospitals. CONCLUSIONS: The current transport system has multiple priorities with regard to efficiency and quality. The medical services at referral hospitals may affect the likelihood of PICU admission and subsequent PICU length of stay; however, no negative impact was observed in other outcomes including mortality.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".