MétaCan
Menu
Back to cohort

P14Sonographic features of the cervix in the midtrimester as a predictor of preterm delivery

2000· article· en· W2086771640 on OpenAlexfundno aff
Tatsuki Fukami, T Sekiya, Kazuhiko Yoshimatsu, Tohru Otabe, K. Tsukada, K. Ishihara, Tsutomu Araki

Bibliographic record

VenueUltrasound in Obstetrics and Gynecology · 2000
Typearticle
Languageen
FieldMedicine
TopicPreterm Birth and Chorioamnionitis
Canadian institutionsnot available
FundersUniversity Health Network
KeywordsMedicineGestationCervixGestational ageObstetricsPredictive valuePreterm deliveryPregnancyGynecologyProspective cohort studyUltrasoundPredictive value of testsRadiologySurgeryInternal medicineCancer

Abstract

fetched live from OpenAlex

Background The purpose of this study was to predict preterm delivery by transvaginal ultrasound in the midtrimester. Method This prospective study was conducted on 568 outpatients with normal pregnancy up to 16 gestational weeks. After the patient's consent was obtained, serial transvaginal ultrasound scanning (TVS) was planned at 2–4 weekly intervals from 16 to 27 gestational weeks, and used to assess cervical length, cervical gland area and internal os dilatation. Results (1) The preterm delivery (37 weeks gestation) rate of the patients was 3.0% (17/568). (2) Of the three predictive factors of preterm delivery namely shortened cervical length (30 mm), absence of cervical gland area, and internal os dilatation, the most useful monographic feature of the cervix was absence of cervical gland area examined at 16–19 weeks gestation. (3) The combination of these factors at 16–19 weeks gestation improved the predictive value (sensitivity 35%, specificity 99%, positive predictive value 88%, negative predictive value 96%). Conclusion For the prediction of preterm delivery by TVS in the midtrimester, the most appropriate gestational period was at 16–19 weeks, and the best predictive factor was a combination of the absence of cervical gland area with shortened cervix and internal osdilatation.

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)0.004
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 score0.036
Threshold uncertainty score0.482

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.004
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 head0.007
GPT teacher head0.225
Teacher spread0.218 · 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

Citations0
Published2000
Admission routes1
Has abstractyes

Explore more

Same venueUltrasound in Obstetrics and GynecologySame topicPreterm Birth and ChorioamnionitisFrench-language works237,207