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Record W2176825014 · doi:10.1002/uog.15314

P01.05: Serial cervical length determination in twin pregnancies reveals four distinct patterns with prognostic significance for preterm birth

2015· article· en· W2176825014 on OpenAlexaff
Nir Melamed, Alex Pittini, Ori Nevo, Phyllis Glanc, J. Barrett

Bibliographic record

VenueUltrasound in Obstetrics and Gynecology · 2015
Typearticle
Languageen
FieldMedicine
TopicAssisted Reproductive Technology and Twin Pregnancy
Canadian institutionsSunnybrook Health Science Centre
Fundersnot available
KeywordsMedicineCervixGestationGestational ageObstetricsGynecologyPregnancyInternal medicineCancer

Abstract

fetched live from OpenAlex

To identify distinct patterns of change in sonographic cervical length(CL) as a function of gestational age in twin gestations and to determine their prognostic value. Retrospective study of women with twins who had serial sonographic cervical examinations at 18–32 weeks. Changes in CL as a function of GA were analysed to identify distinct patterns of cervix behaviour and to determine their relationship to the likelihood of preterm birth (PTB). 1) We identified 441 women with twins with serial measurements of CL (median = 6); 2). There were 4 distinct patterns of changes in CL (figure): I) stable cervix-cervix remained long until 32 weeks; II) early shortening-persistent shortening of CL starting at mid-gestation; III) delayed shortening-persistent shortening of CL starting at late 2nd trimester; IV) transient shortening-transient early shortening of CL until reaching a new stable plateau; 3) The rate of PTB < 34 weeks was lowest for Pattern I (11.7%) and was highest for pattern II (44.4%,p < 0.001) (figure); 4) For pattern II, the main factor affecting the risk of PTB was the shortening rate (AUC 0.67), while for pattern III it was the week at which shortening began (AUC 0.74). The main factors that affected the risk of PTB in cases of pattern IV were the initial shortening rate (AUC 0.63) and the new final plateau of CL (AUC 0.68) (figure). Supporting information can be found in the online version of this abstract Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.

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)0.041
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.041
Threshold uncertainty score0.967

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.041
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.028
GPT teacher head0.266
Teacher spread0.237 · 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.

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

Citations0
Published2015
Admission routes1
Has abstractyes

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