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Record W2316508197 · doi:10.3357/asem.2886.2011

International Medical Evacuation in Children: A Primary Care Pediatric Clinic's 3-Year Experience

2011· article· en· W2316508197 on OpenAlexaff
Miguel Glatstein, Jonathan Halevy, Yaron Atzmon, Raphael J. Kot, Dennis Scolnik

Bibliographic record

VenueAviation Space and Environmental Medicine · 2011
Typearticle
Languageen
FieldMedicine
TopicTravel-related health issues
Canadian institutionsHospital for Sick Children
Fundersnot available
KeywordsMedical emergencyMedical evacuationMedicineIntensive careMultidisciplinary approachEmergency medicinePediatricsIntensive care medicine

Abstract

fetched live from OpenAlex

BACKGROUND: The decision whether to immediately evacuate children who have become ill is a challenge for pediatricians working in countries with limited medical resources. The aim of this study is to describe the injuries and diseases that required evacuation of children from our clinics in Ho Chi Minh City and Hanoi to tertiary critical care hospitals over a 3-yr period. METHODS: A retrospective chart review was performed of all patients aged less than 17 yr who underwent an international medical evacuation between April 1, 2006, and February 28, 2009. Patients were allocated to one of two groups: those requiring immediate aeromedical evacuation by air ambulance and those whose condition allowed nonurgent evacuation by commercial flight. RESULTS: There were 19 international medical evacuations that were executed: 5 immediate aeromedical evacuations with air ambulance and 14 nonurgent evacuations using commercial flights. Immediate evacuations were undertaken to Thailand and Singapore to access pediatric cardiac surgery and intensive care facilities. Some evacuations were performed mainly at parental request. CONCLUSIONS: Aeromedical evacuation requires a multidisciplinary approach and patient age, local resources, availability, location of resources, and parental preference are important factors to be considered. Effective communication is paramount and choice of transportation should be governed by pre-established policies and procedures if possible.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.018
GPT teacher head0.286
Teacher spread0.268 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations4
Published2011
Admission routes1
Has abstractyes

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