Asthma in pregnancy: An update
Bibliographic record
Abstract
AIM: To update obstetric care providers about asthma management. SUMMARY: Asthma is the most frequent comorbid chronic illness in pregnancy. Convincing evidence shows that uncontrolled asthma magnifies the risk of maternal, fetal and neonate complications. Unfortunately, one in four women take no inhaler during pregnancy, and it is likely that decreased adherence, rather than changes in pathology, explains uncontrolled maternal asthma. Patient surveys reveal a need for information and reassurance. Although some molecules are preferred in pregnancy, there is currently no basis to withhold any asthma medication - old or new. Biomarkers such as blood eosinophils and fractional exhaled nitric oxide are an effective way to assess the risk of asthma attacks and the likelihood of responding to inhaled steroids. Furthermore, practice-changing trials in mild asthma show that switching reliever-only regimens to as-needed 'controller-and-reliever' therapy is effective. We suggest that applying these changes can alleviate women's concerns and improve outcomes.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".