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Record W4402360629 · doi:10.1002/uog.28677

EP17.20: Amniocentesis and therapeutic amnioreduction prior to “Rescue Cerclage” (AARC Protocol)

2024· article· en· W4402360629 on OpenAlexaff
Angela De Simone, Glenn Jones, Ana Werlang

Bibliographic record

VenueUltrasound in Obstetrics and Gynecology · 2024
Typearticle
Languageen
FieldMedicine
TopicPreterm Birth and Chorioamnionitis
Canadian institutionsOttawa HospitalUniversity of Ottawa
Fundersnot available
KeywordsAmniocentesisProtocol (science)MedicinePregnancyBiologyFetusPrenatal diagnosisGenetics

Abstract

fetched live from OpenAlex

To determine whether amniotic fluid tests would identify patients who would benefit from rescue cerclage. This was a prospective observational study conducted between December 2021-2023. We included pregnancies involving singleton and twins, gestational age (GA) between 14-24 weeks, cervical dilation <4cm, with membranes at or beyond the external os and no labour signs. Risk of intra-amniotic inflammation or infection (IAI) was assessed using amniotic fluid white cell count, interleukin-6, glucose, gram-stain and culture. Amniocentesis to delivery interval (ADI) was the primary outcome. Secondary outcomes included GA at delivery and perinatal survival. A total of 26 patients were included, with five undelivered at abstract submission. The mean amniocentesis GA was 20.9 weeks. Nine patients (42.8%) had low-risk amniocentesis results, all of whom had rescue cerclage. The mean ADI among those with low-risk amniotic fluid tests was 78.8 days with mean GA at delivery of 32.8 weeks. Among this group, perinatal survival was 100%. Twelve patients (57.2%) had high-risk amniocentesis results, of which three patients had rescue cerclage. The mean ADI among those with high-risk amniotic fluid tests was 18.1 days with mean GA at delivery of 23.0 weeks. Among this group, perinatal survival was 41.7%. There were no survivors among those who underwent rescue cerclage, whose mean ADI was 22.7 days. Our AARC protocol identifies low-risk patients for IAI who would benefit from rescue cerclage.

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)0.000
metaresearch head score (Gemma)0.005
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.908
Threshold uncertainty score0.747

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.013
GPT teacher head0.285
Teacher spread0.272 · 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
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

Citations0
Published2024
Admission routes1
Has abstractyes

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