Available medications used as potential therapeutics for COVID-19: What are the known safety profiles in pregnancy
Bibliographic record
Abstract
BACKGROUND: Medications already available to treat other conditions are presently being studied in clinical trials as potential treatments for COVID-19. Given that pregnant women are excluded from these trials, we aimed to investigate their safety when used during pregnancy within a unique population source. METHODS: Using the population-based Quebec Pregnancy Cohort, we identified women who delivered a singleton liveborn (1998-2015). Taking potential confounders into account including indications for use, the risk of prematurity, low birth weight (LBW), small for gestational age (SGA), and major congenital malformation (MCM) associated with COVID-19 repurposed drug use during pregnancy were quantified using generalized estimation equations. RESULTS: Of the 231,075 eligible pregnancies, 107 were exposed to dexamethasone (0.05%), 31 to interferons (0.01%), 1,398 to heparins (0.60%), 24 to angiotensin-receptor blockers (ARB) (0.01%), 182 to chloroquine (0.08%), 103 to hydroxychloroquine (0.05%), 6,206 to azithromycin (2.70%), 230 to oseltamivir (0.10%), and 114 to HIV medications (0.05%). Adjusting for potential confounders, we observed an increased risk of prematurity related to dexamethasone (aOR 1.92, 95%CI 1.11-3.33; 15 exposed cases), anti-thrombotics (aOR 1.58, 95%CI 1.31-1.91; 177 exposed cases), and HIV medications (aOR 2.04, 95%CI 1.01-4.11; 20 exposed cases) use. An increased risk for LBW associated with anti-thrombotics (aOR 1.72, 95%CI 1.41-2.11; 152 exposed cases), and HIV medications (aOR 2.48, 95%CI 1.25-4.90; 21 exposed cases) use were also found. Gestational exposure to anti-thrombotics (aOR 1.20, 95%CI 1.00-1.44; 176 exposed cases), and HIV medications (aOR 2.61, 95%CI 1.51-4.51; 30 exposed cases) were associated with SGA. First-trimester dexamethasone (aOR 1.66, 95%CI 1.02-2.69; 20 exposed cases) and azithromycin (aOR 1.10, 95%CI 1.02-1.19; 747 exposed cases) exposures were associated with MCM. CONCLUSIONS: Many available medications considered as treatments for COVID-19 are associated with adverse pregnancy outcomes. Caution is warranted when considering these medications during the gestational period.
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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 | 0.004 | 0.016 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".