SEASONAL DIFFERENCES IN BURN INJURIES AND OUTCOMES AMONG ADULTS AND OLDER ADULTS AT A CANADIAN PROVINCIAL BURN CENTER
Bibliographic record
Abstract
ABSTRACT: Background: The literature provides hints of seasonal influences on burn injury occurrence and outcomes in temperate climates. Still, data for geographic regions experiencing significant changes in climate throughout the year is scarce. Especially the influence of seasonal differences in burn incidence and outcomes for older adults (≥60 years old), a particularly vulnerable patient cohort with increased mortality and morbidity compared to adults (18-59 years old), has not been investigated so far. Because burns pose a significant public health concern, we aimed to understand seasonal burn injury admission patterns and outcomes to utilize them for targetable prevention measures and effective resource allocation. Methods: This retrospective single-center cohort study examined data from adult burn patients (≥18 years) with reported %TBSA (total body surface area) treated between 2006 and 2020 at a provincial burn center in Ontario, Canada. Patients were stratified based on age group: adults (18-59 years) and older adults (≥60 years) Demographic data, comorbidities, and clinical outcomes were compared. Results: A total of 2,445 eligible patients were enrolled in this study. Most burn injuries occurred in Summer, in which the burn patient population was also significantly younger compared to Winter. Summer admissions showed a greater median %TBSA. In contrast, length of stay per %TBSA (LOS:TBSA) revealed a shorter hospitalization in Summer compared to Winter. However, mortality did not show differences across seasons. Conclusion: Seasonal variations in the incidence and severity of burn injuries, along with associated fluctuations in LOS:TBSA, exist between age groups. This understanding can assist in tailoring burn prevention programs and aid in anticipating the types of burn injuries that may occur during specific times of the year to enhance patient care strategies.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".