The Safe Resumption of Elective Plastic Surgery in Accredited Ambulatory Surgery Facilities During the COVID-19 Pandemic
Bibliographic record
Abstract
BACKGROUND: On March 11, 2020, the World Health Organization declared the novel Coronavirus-19 (COVID-19) a worldwide pandemic, resulting in an unprecedented shift in the Canadian healthcare system, where protection of an already overloaded system became a priority; all elective surgeries and non-essential activities were ceased. With the impact being less than predicted, on May 26, 2020, elective surgeries and non-essential activities were permitted to resume. OBJECTIVES: The authors sought to examine outcomes following elective aesthetic surgery and the impact on the Canadian healthcare system with the resumption of these services during the COVID-19 worldwide pandemic. METHODS: Data were collected in a prospective manner on consecutive patients who underwent elective plastic surgery procedures in 6 accredited ambulatory surgery facilities. Data included patient demographics, procedural characteristics, COVID-19 polymerase chain reaction (PCR) test status, airway management, and postoperative outcomes. RESULTS: A total of 368 patients underwent elective surgical procedures requiring a general anesthetic. All 368 patients who underwent surgery were negative on pre-visit screening. A COVID-19 PCR test was completed by 352 patients (95.7%) and all were negative. In the postoperative period, 7 patients (1.9%) had complications, 3 patients (0.8%) required a hospital visit, and 1 patient (0.3%) required hospital admission. No patients or healthcare providers developed COVID-19 symptoms or had a positive test for COVID-19 within 30 days of surgery. CONCLUSIONS: With appropriate screening and safety precautions, elective aesthetic plastic surgery can be performed in a manner that is safe for patients and healthcare providers and with a very low risk for accelerating virus transmission within the community.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".