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Record W7117465297 · doi:10.29173/cjen537

Individuals Experiencing Houselessness and Severe Frostbite in Edmonton and Calgary; a three-winter review

2025· article· W7117465297 on OpenAlexvenueaboutno aff
Domhnall O'Dochartaigh, Christopher Picard, Alex Poole`, Daniel Tiwana, Elaine Hyshka, Alexis Armour, Alexis Mageau, Stacey Middleton, Lisa   Allen, Sean Crooks, MAtthew J Douma, Kathryn Dong, Brian   Whiteside, Monty Ghosh, Heather Briana   Boucher, Jevon Brown, Lindsay Burnett, Michael Zakhary, Jake Hayward, Yvonne Chuka Efegoma, Kimberly Byrnes, Ted Harrigan, Lindsay Robinson, Scott MacLean

Bibliographic record

VenueCanadian Journal of Emergency Nursing · 2025
Typearticle
Language
FieldMedicine
TopicBurn Injury Management and Outcomes
Canadian institutionsnot available
Fundersnot available
KeywordsFrostbiteLogistic regressionPopulationEmergency departmentInjury preventionCold injuryPoison control

Abstract

fetched live from OpenAlex

Background: Edmonton and Calgary are Albertan cities with populations of over 1 million each and experience cold winter temperatures, making frostbite a common emergency departments (ED) presentation. In 2024 the estimated unhoused population was approximately 7000 across both cities. Our primary objective was to assess the frequency and severity of frostbite injuries in individuals experiencing houselessness (IEH) compared to those with housing. Methods: This retrospective study of administrative data assessed patients treated in Edmonton and Calgary with severe frostbite over three winters. Data abstracted include patient characteristics, frostbite grade, and time between injury and ED presentation. Ambient temperatures at injury time were assessed from the Alberta Climate Information Service. IEH was determined via clinician notes. Descriptive analysis and statistical methods were used to compare housing status and the grade of injury and arrival time to the ED. The relationship between homelessness and time of injury to arrival at the hospital was examined using ordinal logistic regression. The dependent variable, Time of Injury to Arrival, was categorized as: <12 hours, 12 to 24 hours, 24 to 48 hours, 48 to 72 hours, and >72 hours. Results: 257 cases of severe frostbite were abstracted. Mean age 42.5 (SD13.7), Sex male 208/257(80.9%). IEH comprised 140/257 (54.5%) of cases and unknown in 40/257(15.6%). Houselessness was a precipitating frostbite factor in 102/257(39.7%). IEH was not found to be a statistically significant predictor of frostbite grade (p = .109); OR = 1.55 (95% CI = 0.910 - 2.67). IEH experienced delays in arrival to the ED (p < .001, OR = 2.90, 95% CI = 1.73 - 4.91). IEH were nearly three times as likely to fall into a higher delay category of arrival time compared to non-IEH. Additionally, among the IEH population in this study, 43.48% of Grade 4, 25.86% of Grade 3, and 34.48% of Grade 2 cases occurred at temperatures warmer than -20 degrees Celsius. Implication and lessons learned: Individuals experiencing houselessness had a threefold increase in the likelihood of delayed frostbite ED presentation. Additionally, a significant proportion of frostbite injuries occurred at temperatures warmer than -20C. This study suggests a need for current cold weather system responses to reexamine opportunities for prevention, proactive care, and the availability of shelter for IEH at temperatures warmer than -20C, which is warmer than many cities cold weather responses.

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)0.004
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.876
Threshold uncertainty score0.247

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.006
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
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 head0.023
GPT teacher head0.313
Teacher spread0.290 · 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

Citations0
Published2025
Admission routes2
Has abstractyes

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