Experience of COVID-19 universal screening in obstetrical units in Quebec, Canada
Bibliographic record
Abstract
Background: During the COVID-19 pandemic, some jurisdictions used universal screening for SARS-CoV-2 infection at obstetrical units. This study evaluated the utility of this screening strategy. Methods: We assessed the asymptomatic infection rate and test positivity rate at six obstetrical units in Quebec, Canada. Results: 32,663 parturients were admitted to the six obstetrical units, of which 77.5% were tested for SARS-CoV-2 on admission. Among all six sites, 388 parturients (1.2% [95% CI 1.07% to 1.31%]) tested positive for SARS-CoV-2. Of these, 74.2% were asymptomatic. Rates of positive asymptomatic admissions were similar across sites, ranging from 0.5% to 1.3%. Test positivity rates among parturients varied across the pandemic, ranging from 0.0% to 9.0%. Three nosocomial SARS-CoV-2 infections occurred, with two occurring at the same site. Conclusions: Non-universal strategies such as symptom-based screening and personal protective equipment may be more practical and cost effective for future respiratory pandemics.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".