Incidence of COVID-19 after pulmonary function tests: a retrospective cohort study
Bibliographic record
Abstract
INTRODUCTION: It has been proposed that exposure to pulmonary function tests (PFT) could be associated with a higher risk of viral transmission. The risk of the Coronavirus Disease 2019 (COVID-19) transmission after performing PFT is unknown. We aimed to assess the incidence of COVID-19 after a PFT at an academic teaching facility in Buenos Aires, Argentina. MATERIALS AND METHODS: We conducted a retrospective cohort study including all consecutive adult patients that performed PFT between April 1, 2020 and September 30, 2020. Patients with prior COVID-19 were excluded. We defined a 15-day time window to ascertain PFT related COVID-19. The primary outcome was ascertained by consulting a national database, which has information on all patients with nasopharyngeal swabs for SARS-CoV-2 in Argentina. RESULTS: We included 278 patients who performed a PFT. Fifty percent were women, the mean age was 54 years (SD 18), and the main comorbidities were obesity (31%), smoking (31%), hypertension (29%), and chronic lung disease (28%). The main indication for performing PFT was anesthetic preoperative risk assessment. Swabs were collected from 27 patients (10%). Twenty-two swabs (8%) were taken according to surgical protocols; five swabs (2%) were taken due to clinical suspicion of COVID-19, with only one testing positive. The cumulative incidence of COVID-19 after PFT was 0.36% (95% CI 0.01-20%). None of the technicians developed symptomatic disease. CONCLUSION: Given the right setting and strict adherence to international recommendations, the SARS-CoV-2 infection after having a PFT appears to be low, which follows that these procedures can be performed safely for both patients and staff.
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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 | 0.006 | 0.155 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".