The effect of the COVID-19 pandemic on bariatric surgery delivery in Edmonton, Alberta: a single-centre experience
Bibliographic record
Abstract
<h3>Summary</h3> Delays in the delivery of bariatric surgery in Canada in the context of the COVID-19 pandemic have not been previously explored. Understanding the potential barriers associated with these delays may help in the implementation and delivery of enhanced bariatric protocols, thereby minimizing health care system burden and improving bariatric delivery. We present the experience of a single high-volume, accredited bariatric program in Edmonton, Alberta, in 2020. Although reductions in bariatric cases occurred during lockdown months, the overall number of cases was comparable to 2019 owing to the adoption of strategies aimed at offsetting the burden of hospital resources. These strategies included optimizing patient selection, implementing bariatric Enhanced Recovery After Surgery protocols, and minimizing unnecessary postoperative investigations to allow most patients to be discharged on postoperative day 1. We advocate to continue optimizing bariatric delivery in the face of the COVID-19 pandemic that so disproportionally affects those with severe obesity and its metabolic complications.
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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 | 0.002 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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) | 0.000 | 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".