Institution-Specific Strategies for Head and Neck Oncology Triage During the COVID-19 Pandemic
Bibliographic record
Abstract
BACKGROUND: This work seeks to better understand the triage strategies employed by head and neck oncologic surgical divisions during the initial phases of the coronavirus 2019 (COVID-19) outbreak. METHODS: Thirty-six American head and neck surgical oncology practices responded to questions regarding the triage strategies employed from March to May 2020. RESULTS: Of the programs surveyed, 11 (31%) had official department or hospital-specific guidelines for mitigating care delays and determining which surgical cases could proceed. Seventeen (47%) programs left the decision to proceed with surgery to individual surgeon discretion. Five (14%) programs employed committee review, and 7 (19%) used chairman review systems to grant permission for surgery. Every program surveyed, including multiple in COVID-19 outbreak epicenters, continued to perform complex head and neck cancer resections with free flap reconstruction. CONCLUSIONS: During the initial phases of the COVID-19 pandemic experience in the United States, head and neck surgical oncology divisions largely eschewed formal triage policies and favored practices that allowed individual surgeons discretion in the decision whether or not to operate. Better understanding the shortcomings of such an approach could help mitigate care delays and improve oncologic outcomes during future outbreaks of COVID-19 and other resource-limiting events. LEVEL OF EVIDENCE: 4.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".