Management of allergic diseases in pregnancy
Bibliographic record
Abstract
Allergic diseases like asthma, allergic rhinitis, food allergy, hymenoptera allergy, or atopic dermatitis are highly prevalent in women of childbearing age and may affect up to 30% of this age group. This review focuses on the management of allergic diseases during pregnancy. Furthermore, we discuss the challenges of counseling women with allergic diseases in the reproductive age, including considerations relevant to the ongoing SARS-CoV-2 pandemic. To create the optimal milieu for the unborn child, a multitude of immunological changes occur during pregnancy which may favor type 2 responses and aggravate disease phenotypes. In co-occurrence with suboptimal preconception disease control, this elevated Th2 responses may aggravate allergic disease manifestations during pregnancy and pose a risk for mother and child. Due to limitations in conducting clinical trials in pregnant women, safety data on anti-allergic drugs during pregnancy are limited. The lack of information and concerns among pregnant patients demands counseling on the benefits of anti-allergic drugs and the potential and known risks. This includes information on the risk for mother and child of disease aggravation in the absence of treatment. By doing so, informed decisions and shared decision-making can take place.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".