International registry of otolaryngologist–head and neck surgeons with COVID‐19
Bibliographic record
Abstract
BACKGROUND: It has become clear that healthcare workers are at high risk, and otolaryngology has been theorized to be among the highest risk specialties for coronavirus disease 2019 (COVID-19). The purpose of this study was to detail the international impact of COVID-19 among otolaryngologists, and to identify instructional cases. METHODS: Country representatives of the Young Otolaryngologists-International Federation of Otolaryngologic Societies (YO-IFOS) surveyed otolaryngologists through various channels. Nationwide surveys were distributed in 19 countries. The gray literature and social media channels were searched to identify reported deaths of otolaryngologists from COVID-19. RESULTS: A total of 361 otolaryngologists were identified to have had COVID-19, and data for 325 surgeons was available for analysis. The age range was 25 to 84 years, with one-half under the age of 44 years. There were 24 deaths in the study period, with 83% over age 55 years. Source of infection was likely clinical activity in 175 (54%) cases. Prolonged exposure to a colleague was the source for 37 (11%) surgeons. Six instructional cases were identified where infections occurred during the performance of aerosol-generating operations (tracheostomy, mastoidectomy, epistaxis control, dacryocystorhinostomy, and translabyrinthine resection). In 3 of these cases, multiple operating room attendees were infected, and in 2, the surgeon succumbed to complications of COVID-19. CONCLUSION: The etiology of reported cases within the otolaryngology community appear to stem equally from clinical activity and community spread. Multiple procedures performed by otolaryngologists are aerosol-generating procedures (AGPs) and great care should be taken to protect the surgical team before, during, and after these operations.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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 | 0.000 |
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 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".