Detection of SARS CoV-2 contamination in the Operating Room and Birthing Room Setting: Risks to attending health care workers
Bibliographic record
Abstract
ABSTRACT Background The exposure risks to front-line health care workers who are in close proximity for prolonged periods of time, caring for COVID-19 patients undergoing surgery or obstetrical delivery is unclear. Understanding of sample types that may harbour virus is important for evaluating risk. Objectives To determine if SARS-CoV-2 viral RNA from patients with COVID-19 undergoing surgery or obstetrical care is present in: 1) the peritoneal cavity of males and females 2) the female reproductive tract, 3) the environment of the surgery or delivery suite (surgical instruments, equipment used, air or floors) and 4) inside the masks of the attending health care workers. Methods The presence of SARS-CoV-2 viral RNA in patient, environmental and air samples was identified by real time reverse transcriptase polymerase chain reaction (RT-PCR). Air samples were collected using both active and passive sampling techniques. Results In this multi-centre observational case series, 32 patients with COVID-19 underwent urgent surgery or obstetrical delivery and 332 patient and environmental samples were collected and analyzed to determine if SARS-CoV-2 RNA was present. SARS-CoV-2 RNA was detected in: 4/24(16.7%) patient samples, 5/60(8.3%) floor, 1/54(1.9%) air, 10/23(43.5%) surgical instruments/equipment, 0/24 cautery filters and 0/143 inner surface of mask samples. Conclusions While there is evidence of SARS-CoV-2 RNA in the surgical and obstetrical operative environment (6% of samples taken), the finding of no detectable virus inside the masks worn by the medical teams would suggest a low risk of infection for our health care workers using appropriate personal protective equipment (PPE).
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".