Management of Peritonsillar Abscesses in Adults: Survey of Otolaryngologists in Canada and the United States
Bibliographic record
Abstract
OBJECTIVE: The management of peritonsillar abscess (PTA) has evolved over time. We sought to define contemporary practice patterns for the diagnosis and treatment of PTA. STUDY DESIGN: Cross-sectional survey. SETTING: The 15-question survey was distributed to members of the Canadian Society of Otolaryngology-Head and Neck Surgery (CSO) and the American Academy of Otolaryngology-Head and Neck Surgery (AAO-HNS). METHODS: An iterative, consensus-based process was used for survey development. Primary outcomes were to determine methods of diagnosis and first-line treatments for PTA. Exploratory, secondary outcomes were analyzed using multivariable logistic regression models. RESULTS: The survey response rate was 12.6% (n = 1176). Most participants were attending staff (86%) in a community hospital setting (60%) and had been in practice for more than 20 years (38%). Most respondents (78%) indicated that at least half of the time, cross-sectional imaging had already been performed before they were consulted. Half of respondents (49%) indicated that they perform incision and drainage of the abscess as first-line treatment, while few (16%) provide medical management alone. In exploratory analysis, participants from the AAO-HNS had higher odds of imaging already being performed before consultation (odds ratio [OR], 11.7; 95% CI, 4.6-29.4) and increased odds of using medical management alone as a first-line treatment (OR, 2.4; 95% CI, 1.3-4.2) compared to respondents from the CSO. CONCLUSION: There is wide practice variation in the diagnosis and management of acute, uncomplicated PTA among otolaryngologists in Canada and the United States. The use of cross-sectional imaging and medical management alone may differ between countries of practice.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".