CSO (Canadian Society of Otolaryngology - Head & Neck Surgery) position paper on rhinologic and skull base surgery during the COVID-19 pandemic
Bibliographic record
Abstract
Healthcare services in many countries have been partially or completely disrupted by the Coronavirus (COVID-19) pandemic since its onset in the end of 2019. Amongst the most impacted are the elective medical and surgical services in order to conserve resources to care for COVID-19 patients. As the number of infected patients decrease across Canada, elective surgeries are being restarted in a staged manner. Since Otolaryngologists – Head & Neck Surgeons manage surgical diseases of the upper aerodigestive tract where the highest viral load reside, it is imperative that these surgeries resume in a safe manner. The aim of this document is to compile the current best evidence available and provide expert consensus on the safe restart of rhinologic and skull base surgeries while discussing the pre-operative, intra-operative, and post-operative care and tips. Risk assessment, patient selection, case triage, and pre-operative COVID-19 testing will be analyzed and discussed. These guidelines will also consider the optimal use of personal protective equipment for specific cases, general and specific operative room precautions, and practical tips of intra-operative maneuvers to optimize patient and provider safety. Given that the literature surrounding COVID-19 is rapidly evolving, these recommendations will serve to start our specialty back into elective rhinologic surgeries over the next months and they may change as we learn more about this disease.
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 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 | 0.006 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.005 | 0.008 |
| Insufficient payload (model declined to judge) | 0.044 | 0.011 |
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".