Prospective clinical trial of gelatin‐thrombin matrix as first line treatment of posterior epistaxis
Bibliographic record
Abstract
OBJECTIVES/HYPOTHESIS: To evaluate the effectiveness of gelatin-thrombin matrix for first line treatment of posterior epistaxis. Secondarily, we evaluated discomfort during treatment and the cost savings of treatment with gelatin-thrombin matrix compared to posterior packing, endoscopic, or endovascular treatment at our institution. STUDY DESIGN: Prospective pilot, nonblinded, noncontrolled registered clinical trial (NCT01098578). METHODS: Twenty patients with posterior epistaxis were enrolled into this study. Gelatin-thrombin matrix was used for posterior epistaxis treatment with simultaneous ipsilateral choanal occlusion. Patients were discharged within 2 hours of being successfully treated. A visual analog scale (range 0-10) was used to assess treatment discomfort. Patients were evaluated in clinic 5 and 30 days after treatment to assess for intranasal complications and recurrent epistaxis. RESULTS: Gelatin-thrombin matrix successfully treated epistaxis in 80% of the patients. The procedure was associated with a mean discomfort of 3.6 (range 0-9.7). The institutional per case cost of treatment of patients with posterior epistaxis with gelatin-thrombin matrix is 80.3%, 87.4%, and 89.4% less than with endoscopic surgery, posterior packing, or embolization, respectively. There were no complications. CONCLUSION: This pilot study demonstrated that gelatin-thrombin matrix is a safe and both a clinically effective and cost-saving means of treating posterior epistaxis. In this study, its use is associated with a low level of discomfort. This treatment method may improve the quality of care for patients with posterior epistaxis.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".