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Record W2067307795 · doi:10.3109/14767058.2014.947575

Impact of amniotic fluid “sludge” on the risk of preterm delivery

2014· article· en· W2067307795 on OpenAlexaff
F. Fuchs, Isabelle Boucoiran, Audrey Picard, Johanne Dubé, S. Wavrant, Emmanuel Bujold, François Audibert

Bibliographic record

VenueThe Journal of Maternal-Fetal & Neonatal Medicine · 2014
Typearticle
Languageen
FieldMedicine
TopicPreterm Birth and Chorioamnionitis
Canadian institutionsUniversité LavalCentre Hospitalier Universitaire Sainte-JustineUniversité de Montréal
Fundersnot available
KeywordsMedicineAzithromycinOdds ratioCervical cerclageObstetricsLogistic regressionAmniotic fluidGestationGestational ageAntibioticsPregnancyBody mass indexGynecologyFetusInternal medicine

Abstract

fetched live from OpenAlex

OBJECTIVE: To evaluate the impact of amniotic fluid "sludge" (AFS) on the risk of preterm delivery and to describe the effect of antibiotic treatment in that situation. METHODS: Case-control study including singleton pregnancies with or without AFS, between 15-32 weeks of gestation. Factors associated with preterm delivery before 32 weeks, 34 weeks and 37 weeks were evaluated with univariate and multivariate logistic regression. Since all women with AFS in this study were treated with antibiotics, a historical comparison was performed with similar patients with AFS found before 2007 and not treated with antibiotics. RESULTS: AFS was observed in 90/1220 patients (7.4%). AFS was associated with shorter cervical length, greater body mass index, cervical cerclage and preterm birth before 28 weeks. However, after adjustment, AFS did not remain associated with preterm delivery before 32 or 34 weeks. The historical comparison suggested that azithromycin could significantly reduce the risk of preterm delivery before 34 weeks (odds ratio: 0.2; 95% CI: 0.04-0.92). CONCLUSIONS: AFS, treated with azithromycin, was associated with a higher risk of prematurity, but not independently after adjustment for cervical length and second trimester vaginal bleeding. Further studies need to evaluate the effect of antibiotics in pregnancies with AFS.

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)0.002
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.545
Threshold uncertainty score0.563

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.010
GPT teacher head0.254
Teacher spread0.244 · 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 designObservational
Domainnot available
GenreEmpirical

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

Citations28
Published2014
Admission routes1
Has abstractyes

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