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Record W2791597642 · doi:10.1097/pcc.0000000000001491

Epidemiology of Pediatric Critical Care Transport in Northern Alberta and the Western Arctic

2018· article· en· W2791597642 on OpenAlexaffabout
Atsushi Kawaguchi, Charlene C. Nielsen, Gonzalo Garcia Guerra, L. Duncan Saunders, Yutaka Yasui, Allan DeCaen

Bibliographic record

VenuePediatric Critical Care Medicine · 2018
Typearticle
Languageen
FieldMedicine
TopicTrauma and Emergency Care Studies
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMedicineReferralOddsPsychological interventionOdds ratioEmergency medicineDemographicsEpidemiologyFamily medicinePediatricsDemographyLogistic regressionNursingInternal medicine

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.013
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.114
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.013
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.003
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.038
GPT teacher head0.362
Teacher spread0.324 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations12
Published2018
Admission routes2
Has abstractyes

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