Working to Investigate New Treatments and Evaluating Results; Comparison of Iloprost Therapy for Frostbite in Two Canadian Cities
Bibliographic record
Abstract
Background: Edmonton and Calgary are cities with populations of over 1 million. Both experience cold winter temperatures, making frostbite a common emergency departments (ED) presentation. Recently some EDs added iloprost for frostbite care. Iloprost is available in Canada via the Special Access Program. Its effectiveness for preventing amputations requires further investigation. The primary study objective compares amputation rates in patients with severe frostbite who did and did not receive Iloprost in two cities. Also assessed was iloprost adverse events. Methods: This retrospective study assessed administrative data of patients ≥18 years treated in Edmonton and Calgary with grade 2-4 frostbite over a 3-year period. Abstracted data was categorized to include grade and amputation by digit, iloprost, and adverse medication events. Descriptive analysis and multivariable linear regression controlling for potential confounders was performed to identify predictors of amputation, for those receiving standard care (SC) or iloprost (IC). Results: 257 patients met inclusion criteria (177/80 SC/IC). Mean age was 42.5(13.7SD), male sex n=208 (80.9%), comorbidities: houseless 140 (54.5%), active substance use/alcohol use disorder (175, 59.1%/ 69, 26.8%). Overall amputation rate for patients with grade 2 injury was similar between groups (SC 3/873.4%; IC 1/30 3.3%). For grade 3 injuries there was a higher proportion of amputations in SC (34/69, 69% vs IC 9/21, 42%; p = 0.042). For grade 4 injuries, there was no difference between groups (SC 17/21, 81%; IC 16/19, 84%; p = 0.787). Logistic regression suggests IC patients were less likely to have an amputation (p= 0.038, OR = 0.49, 95% CI = 0.25 - 0.96), and fewer digits amputated (p < 0.001, βST = -0.6, 95% CI = -0.91 - -0.3). Adverse effects of iloprost were reported in 49 (61.25%) patients, 44 (55%) having multiple adverse effects. Including (n): headache (25, 2.1%),Tachycardia >100 (14,13.1%), Nausea (13,12.1%), Hypotension (13, 12.1%), flushing (10, 9.3%), vomiting (7, 6.5%), myalgias (5, 4.7%), hypertension (4, 3.7%); Dizziness/abdominal pain/chills/palpitations (each n2, 1.9%); and chest pain, vein redness, tiredness, restless (each n1, 0.9%). implications and lessons learned: Iloprost was associated with a lower likelihood and number of amputations for grade 2 and 3 frostbite injuries, but not in grade 4 injuries when compared to standard care.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".