Management of severe frostbite with iloprost, alteplase and heparin: a Yukon case series
Bibliographic record
Abstract
BACKGROUND: We identified the need to modernize frostbite management in our northern centre and implemented a treatment protocol in 2015. Our aim was to describe the clinical course of patients presenting to the hospital since the implementation of the protocol. METHODS: This was a retrospective case series from Whitehorse General Hospital, Whitehorse, Yukon Territory, Canada. We reviewed the charts of patients who presented to the hospital with grade 2-4 frostbite and were treated as per our protocol between Feb. 9, 2015, and Feb. 8, 2020. Patients with grade 2-4 frostbite received iloprost; in addition, those with grade 4 frostbite received alteplase and heparin. We determined the number of digits affected and salvaged, and the time from presentation to the emergency department to treatment initiation. We also examined patients' demographic characteristics, predisposing events, frostbite severity and adverse drug reactions. RESULTS: In 22 patients treated for grade 2-4 frostbite, 142 digits were affected: 59 with grade 2 frostbite, 25 with grade 3 frostbite and 58 with grade 4 frostbite; of the 142, 113 (79.6%) were salvaged. All 29 digits amputated had grade 4 frostbite. The mean time from presentation to iloprost initiation was reduced from 32.9 hours in 2015 to 3.0 hours in 2020. Sports (10 cases [45%]) and alcohol use (6 [27%]) were the most common precipitating events, with alcohol use tending to result in more severe injury (grade 4 in 5 of 6 cases). Adverse reactions with iloprost (e.g., headache) were common but mild. Adverse reactions with alteplase (e.g., bleeding) were less common but of greater clinical significance. INTERPRETATION: Over the study period, our protocol contributed to improvement in frostbite care at our institution, resulting in a digit salvage rate comparable to other published results. Our 5-year experience shows that advanced medical care of frostbite can be achieved, even at a rural centre.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".