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Record W4405484892 · doi:10.1016/j.clinme.2024.100277

Management of asthma in pregnancy

2024· review· en· W4405484892 on OpenAlexaff
CE Jones, Yasmin Jamil

Bibliographic record

VenueClinical Medicine · 2024
Typereview
Languageen
FieldMedicine
TopicPregnancy and Medication Impact
Canadian institutionsSt. Thomas Hospital
Fundersnot available
KeywordsMedicineAsthmaPregnancyAsthma managementObstetricsIntensive care medicineInternal medicine

Abstract

fetched live from OpenAlex

Asthma is the most common chronic disease to affect pregnant women and can have a significant effect on pregnancy outcomes, with increased rates of preterm birth, premature delivery and caesarean section observed if poorly controlled. Pregnancy can also influence asthma control. Prescribing in pregnancy causes anxiety for patients and healthcare professionals and can result in alteration or undertreatment of asthma. Good asthma control with prompt and adequate management of exacerbations is key to reducing adverse pregnancy outcomes for both mother and fetus. The majority of asthma treatment can be continued as normal in pregnancy and there is emerging evidence of the safety of biologic medications also. This article aims to summarise the current evidence about asthma in pregnancy and guide the appropriate management of this population.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.873
Threshold uncertainty score0.915

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.210
GPT teacher head0.535
Teacher spread0.325 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
Domainnot available
GenreReview

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".

Quick stats

Citations5
Published2024
Admission routes1
Has abstractyes

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