Management of Anterior Epistaxis in the Emergency Department Using Rapid Rhino and Merocel: A Cost Analysis
Bibliographic record
Abstract
IMPORTANCE: Epistaxis affects approximately 60% of the population over their lifetime. When conservative attempts fail, nasal tampons are often required to stop anterior bleeding. Health economics is critical in our publicly funded system. Determination of cost-effective interventions is crucial. OBJECTIVE: To compare the total cost of Merocel and Rapid Rhino from the perspective of a provincial payer and an academic hospital for the management of anterior epistaxis. DESIGN: Retrospective review. SETTING: London Health Sciences Centre emergency department (Victoria and University campus). PARTICIPANTS: Patients ≥18 years of age presenting with anterior epistaxis. The participants were 67% men and 33% women. Approximately, 63% were on anticoagulant medication, and 35% used an ambulance to arrive at the hospital. INTERVENTION: Rapid Rhino or Merocele, which was dependent on the site of presentation. MAIN OUTCOME MEASURES: Rebleed rate. RESULTS: The rate of rebleeds with Merocel was 42% (26/62), whereas it was 24% (4/17) with Rapid Rhino. The inverse probability weighted regression adjustment results show that patients receiving Rapid Rhino did not have a statistically significant difference in costs per patient ($62.40, 95% CI: -$25.75 to $150.55) from the hospital perspective or the provincial health care payer perspective ($78.25, 95% CI: -$18.38 to $174.89). CONCLUSION AND RELEVANCE: There was no significant difference in cost between Rapid Rhino and Merocel for anterior epistaxis from a hospital or provincial payer perspective.
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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 | 0.004 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.008 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".