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Record W4391995903 · doi:10.1503/cjs.005722

Predictors of clinical deterioration and intensive care unit admission in trauma patients transferred from northern Quebec to a level 1 trauma centre: a retrospective cohort study

2024· article· en· W4391995903 on OpenAlexaffvenueabout
Jeongyoon Moon, Tarek Razek, Jeremy Grushka, Dan Deckelbaum, Nathalie Boulanger, Larry Watt, Kosar Khwaja, Paola Fata, Katherine M. McKendy, Atif Jastaniah, Evan G. Wong

Bibliographic record

VenueCanadian Journal of Surgery · 2024
Typearticle
Languageen
FieldMedicine
TopicTrauma and Emergency Care Studies
Canadian institutionsMcGill UniversityNunavik Regional Board of Health and Social Services
Fundersnot available
KeywordsMedicineGlasgow Coma ScaleInterquartile rangeInjury Severity ScoreIntensive care unitRetrospective cohort studyMajor traumaOdds ratioConfidence intervalEmergency medicineAbbreviated Injury ScalePoison controlInjury preventionInternal medicineSurgery

Abstract

fetched live from OpenAlex

BACKGROUND: Trauma care in Nunavik, Quebec, is highly challenging. Geographic distances and delays in transport can translate into precarious patient transfers to tertiary trauma care centres. The objective of this study was to identify predictors of clinical deterioration during transport and eventual intensive care unit (ICU) admission for trauma patients transferred from Nunavik to a tertiary trauma care centre. METHODS: This is a retrospective cohort study using the Montreal General Hospital (MGH) trauma registry. All adult trauma patients transferred from Nunavik and admitted to the MGH from 2010 to 2019 were included. Main outcomes of interest were hemodynamic and neurologic deterioration during transport and ICU admission. RESULTS: In total, 704 patients were transferred from Nunavik and admitted to the MGH during the study period. The median age was 33 (interquartile range [IQR] 23-47) years and the median Injury Severity Score was 10 (IQR 5-17). On multiple regression analysis, transport time from site of injury to the MGH (odds ratio [OR] 1.04, 95% confidence interval [CI] 1.01-1.06), thoracic injuries (OR 1.75, 95% CI 1.03-2.99), and head and neck injuries (OR 3.76, 95% CI 2.10-6.76) predicted clinical deterioration during transfer. Injury Severity Score (OR 1.04, 95% CI 1.01-1.08), abnormal local Glasgow Coma Scale score (OR 2.57, 95% CI 1.34-4.95), clinical deterioration during transfer (OR 4.22, 95% CI 1.99-8.93), traumatic brain injury (OR 2.44, 95% CI 1.05-5.68), and transfusion requirement at the MGH (OR 4.63, 95% CI 2.35-9.09) were independent predictors of ICU admission. CONCLUSION: Our study identified several predictors of clinical deterioration during transfer and eventual ICU admission for trauma patients transferred from Nunavik. These factors could be used to refine triage criteria in Nunavik for more timely evacuation and higher level care during transport.

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)0.001
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 score0.179
Threshold uncertainty score0.360

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.001
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 head0.080
GPT teacher head0.321
Teacher spread0.241 · 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

Citations3
Published2024
Admission routes3
Has abstractyes

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