Recommendations from the Canadian Association of Head and Neck Surgical Oncology for the Management of Head and Neck Cancers during the COVID-19 pandemic
Bibliographic record
Abstract
INTRODUCTION: The SARS-CoV-2 virus (COVID19) pandemic has placed extreme pressures on the Canadian Healthcare system. Many health care regions in Canada have cancelled or limited surgical and non-surgical interventions on patients to preserve healthcare resources for a predicted increase in COVID19 related hospital admissions. Also reduced health interventions may limit the risk of possible transmission of COVID19 to other patients and health care workers during this pandemic. The majority of institutions in Canada have developed their own operational mandates regarding access to surgical resources for patients suffering from Head and Neck Cancers during this pandemic. There is a large degree of individual practitioner judgement in deciding access to care as well as resource allocation during these challenging times. The Canadian Association of Head and Neck Surgical Oncology (CAHNSO) convened a task force to develop a set of guidelines based on the best current available evidence to help Head and Neck Surgical Oncologists and all practitioners involved in the care of these patients to help guide individual practice decisions. MAIN BODY: The majority of head and neck surgical oncology from initial diagnosis and work up to surgical treatment and then follow-up involves aerosol generating medical procedures (AGMPs) which inherently put head and neck surgeons and practitioners at high risk for transmission of COVID19. The aggressive nature of the majority of head and neck cancer negates the ability for deferring surgical treatment for a prolonged period of time. The included guidelines provide recommendations for resource allocation for patients, use of personal protective equipment for practitioners as well as recommendations for modification of practice during the current pandemic. CONCLUSION: 1. Enhanced triaging should be used to identify patients with aggressive malignancies. These patients should be prioritized to reduce risk of significant disease progression in the reduced resource environment of COVID19 era. 2. Enhanced triaging including aggressive pre-treatment COVID19 testing should be used to identify patients with high risk of COVID19 transmission. 3. Enhanced personal protective equipment (PPE) including N95 masks and full eye protection should be used for any AGMPs performed even in asymptomatic patients. 4. Enhanced PPE including full eye protection, N95 masks and/or powered air purifying respirators (PAPRs) should be used for any AGMPs in symptomatic or presumptive positive COVID 19 patients.
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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 | 0.016 | 0.060 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.008 | 0.004 |
| Research integrity | 0.015 | 0.017 |
| Insufficient payload (model declined to judge) | 0.017 | 0.009 |
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".