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Record W1998866190 · doi:10.1136/ip.2010.029215.390

Association between socioeconomic status and access to trauma care for victims of injury in a Canadian trauma system

2010· article· en· W1998866190 on OpenAlexaffabout
Lynne Moore, A Lavoie, AF Turgeon, Marie‐Josée Sirois, V Murat

Bibliographic record

VenueInjury Prevention · 2010
Typearticle
Languageen
FieldMedicine
TopicTrauma and Emergency Care Studies
Canadian institutionsMcGill University
Fundersnot available
KeywordsSocioeconomic statusMedicineResidenceInjury preventionPoison controlDemographyPopulationOccupational safety and healthMultilevel modelInjury Severity ScoreSuicide preventionMetropolitan areaComorbidityGerontologyEmergency medicineEnvironmental healthPsychiatry

Abstract

fetched live from OpenAlex

The association between low socioeconomic status (SES) and increased population-based risk of injury is well documented. However, little is known about the association between SES and access to trauma care. We aimed to evaluate the association between SES and time to definitive trauma care in an inclusive Canadian trauma system. SES was quantified using an ecological index of material deprivation via patients residential postal code. Data was drawn from the Quebec trauma registry based on mandatory data collection for all patients with major trauma treated within the inclusive provincial trauma system (1999–2006). The association between SES and time to definitive care was evaluated using hierarchical linear regression. The study sample comprised 88 235 patients treated in 59 trauma centres. The proportion of patients in the highest quintile of material deprivation ranged from 16% in metropolitan regions to 71% in regions with no metropolitan influence. Following adjustment for injury severity, age and comorbidity, those in the highest quintile of material deprivation had a mean time to definitive care 0.926 h longer (p<0.0001) than those in the lowest quintile. However, after adjustment for region of residence, the mean time difference approached zero (0.075 h, p=0.2). High material deprivation is associated with longer delays to definitive care. However, this association appears to be entirely explained by the fact that patients with high material deprivation are more likely to live in rural regions and are therefore further from hospitals offering definitive trauma care.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.327
Threshold uncertainty score0.961

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.016
GPT teacher head0.330
Teacher spread0.314 · 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.

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

Citations1
Published2010
Admission routes2
Has abstractyes

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