Contemporary perspectives on the management of posterior epistaxis: survey of canadian otolaryngologists.
Bibliographic record
Abstract
OBJECTIVE: To describe current management of posterior epistaxis among Canadian otolaryngology-head and neck surgeons. METHODS: A cross-sectional Internet-based survey was distributed to all 550 members of the Canadian Society of Otolaryngology-Head and Neck Surgery with an electronic mail contact. The survey consisted of three sections: (1) demographic data, (2) opinions regarding management options for posterior epistaxis, and (3) opinions regarding management of complications after placement of a posterior nasal pack. The survey was available for completion from July 2009 until October 2009. Main outcome measures were ranking of preference, comfort level, and perceived best management option for posterior epistaxis. RESULTS: A total of 152 completed surveys were collected (28% response rate). Respondents were most comfortable with and most preferred inflatable balloon packing for treatment of posterior epistaxis. However, it was felt that endoscopic sphenopalatine arterial ligation was the best available intervention. After placement of a posterior nasal pack, respondents felt that monitoring of vital signs was required for all patients, but a lower-intensity monitoring setting may be sufficient. CONCLUSIONS: There is a discrepancy between actual practice and perceived best available management for posterior epistaxis. Respondents also favoured a lower-intensity monitoring setting for patients with posterior nasal packing. Practice guidelines may be helpful in ensuring that patients receive the best possible care while making the best use of limited hospital resources.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.002 | 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) | 0.003 | 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".