How standardised are antibiotic regimens in otologic surgery?
Bibliographic record
Abstract
Abstract Background Within otologic surgery, a paucity of well-controlled studies assessing the use of systemic antibiotic to reduce surgical site infections exists. Moreover, discrepancies in wound classification of procedures challenge consensus in antimicrobial prescribing patterns. We sought to compare surgeons from two different health systems to examine how surgeons’ prescribing habits compared to practice guidelines for numerous otologic procedures. Methods An online questionnaire was distributed to 33 Canadian and 32 Austrian surgeons who regularly perform otologic surgery. Current systemic antibiotic prescribing habits for cochlear implantation, cholesteatoma surgery, stapes surgery, and tympanoplasty ± ossiculoplasty were collected. Results Eighteen of 33 (54.5%) Canadian surgeons provided responses, while 18 of 32 (56.3%) of Austrian surgeons answered. Clear consistency with clinical practice guidelines exists for pre-operative antibiotics use in cochlear implant surgery and infected cholesteatoma surgery. However, for stapes surgery and tympanoplasty ± ossiculoplasty, consensus is lacking for both pre- and post-operative antibiotic prescribing habits. Notable differences between the two countries include post-operative antibiotics for cochlear implant surgery (Austria: 36.4%, Canada: 71.4%) and uninfected cholesteatoma surgery (Austria: 33.3%, Canada: 77.8%). Across all procedures, both induction and post-operative antibiotic administration was not significantly associated with surgeon seniority when stratified by five-year increments. Conclusion The lack of consensus among each country’s otologic surgeons underscores the uncertainty in wound classification and thus, adherence to clinical practice guidelines. Graphical Abstract
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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 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".