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Diagnosis of low‐lying placenta: can migration in the third trimester predict outcome?

2001· article· en· W2003337149 on OpenAlexaff
Lawrence Oppenheimer, Paul Holmes, Nigel Simpson, A. Dabrowski

Bibliographic record

VenueUltrasound in Obstetrics and Gynecology · 2001
Typearticle
Languageen
FieldMedicine
TopicMaternal and fetal healthcare
Canadian institutionsOttawa HospitalUniversity of Ottawa
Fundersnot available
KeywordsMedicinePlacenta previaPlacentaObstetricsGestationGynecologyUltrasoundObstetrics and gynaecologyPregnancyFetusRadiology

Abstract

fetched live from OpenAlex

OBJECTIVES: To investigate the relationship between the rate of migration of a low-lying placenta during the third trimester and the eventual route of delivery. METHODS: All patients with a placenta lying within 3 cm of the internal cervical os or overlapping it on transvaginal ultrasound at > or = 26 weeks' gestation were included in the study. The exact distance between the center of the internal cervical os and the leading edge of the placenta was measured by transvaginal sonography, repeated at approximately 4-week intervals until delivery. RESULTS: The mean rates of migration in patients who had (n = 7) and who did not have (n = 29) Cesarean section for placenta previa were +0.3 mm/week and +5.4 mm/week, respectively (P < 0.0001). When the placental edge was initially > 20 mm from the internal os, migration occurred in all cases and no Cesarean section for placenta previa was performed. For those between -20 mm and +20 mm, sufficient migration to avoid Cesarean section occurred in 88.5% of cases. Beyond a 20 mm overlap, significant placental migration did not occur and all patients required Cesarean section. CONCLUSION: Placental migration may occur progressively throughout the third trimester. The initial position of the placental edge and the subsequent rate of migration can be used to predict the eventual route of delivery.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.027
GPT teacher head0.295
Teacher spread0.268 · 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 source (direct Gemma or distilled Codex), 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

Citations102
Published2001
Admission routes1
Has abstractyes

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