290 Pediatric Frostbite: A 10-year Single-center Retrospective Study
Bibliographic record
Abstract
Frostbite is a thermal injury from frozen tissue. Literature is limited on children, a vulnerable population not in control of their environment. The objective is to describe frostbite in children referred to a regional pediatric hospital and intrinsic (psychological and behavioral) and extrinsic (meteorological and safety hazard) factors related to the injury. Retrospective chart review of 47 patients < 18 years old examining demographics, and intrinsic and extrinsic factors related to injuries. Demographic characteristics included sex, with whom the child lives with, illicit drug use, physical comorbidities, and region of residence. Injury characteristics included anatomical location, management, ambient temperature at the time of injury, exposure duration, injury circumstance, and factors related to injury including intoxication and supervision. Summary statistics are presented as median (IQR) or number (%) unless otherwise noted. Kolmogorov-Smirnov test was used to determine normality. Mann-Whitney U test was used to compare differences in median ambient temperature or median exposure duration between groups that had one or more procedures compared to none. Statistically significant differences between groups were defined as p < 0.05. Median age was 15 years (IQR 12–16) and 49% were admitted. Frequently documented risk activities included use of alcohol (53%), cigarettes (34%), marijuana (23%), and symptoms of depression and/or suicidality (32%). Although frostbite starts to present at ≤ -6°C, procedures were only required for frostbite occurring at temperatures ≤ -23°C (p = .001). Along with colder ambient temperature, long exposure duration (p < .001) was significantly related to likelihood of procedure, as opposed to conservative wound management. Two factors related to the injury were identified: intoxication and lack of supervision. Among patients 0–12 years, lack of supervision at time of injury was common (64%), while intoxication among older patients ages 13–17 was common (61%). To our knowledge, this is the largest retrospective study of pediatric frostbite. These findings call for targeted outreach to reduce frostbite incidence. For younger children, the focus must be on involving and educating parents on risks of unsupervised care. For older children, informing youth on risks of frostbite alongside approaches to curb adolescent alcohol use are warranted.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".