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Sonographic Lower Uterine Segment Thickness After Prior Cesarean Section to Predict Uterine Rupture: A Systematic Review and Meta-analysis

2020· review· en· W3030157609 on OpenAlexaff
Brenna Swift, Prakesh S. Shah, D. Farine

Bibliographic record

VenueObstetric Anesthesia Digest · 2020
Typereview
Languageen
FieldMedicine
TopicMaternal and Perinatal Health Interventions
Canadian institutionsMount Sinai Hospital
Fundersnot available
KeywordsMedicineUterine ruptureMeta-analysisUltrasoundObstetricsPredictive valueGynecologyUterusRadiologyInternal medicine

Abstract

fetched live from OpenAlex

( Anaesthesia . 2019;74:850–855) The rate of trial of labor after cesarean (TOLAC) in the United States has markedly dropped over the past few decades. Uterine rupture is the most serious complication associated with TOLAC, with the risk ranging from 0.52% for women in spontaneous labor to 2.45% for women undergoing labor induction with prostaglandin. This risk may be contributing to the declining rate of TOLAC. Sonographic measurement of the lower uterine segment thickness has been evaluated by several prospective studies, but the cutoff values for recommending TOLAC in these studies have differed due to varying ultrasound methodologies. This study analyzed the ultrasound methodology used in each study and then conducted a meta-analysis of the predictive value of sonographic measurement of the lower uterine segment thickness for uterine rupture during labor.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.918
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0090.004
Bibliometrics0.0010.004
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.049
GPT teacher head0.344
Teacher spread0.294 · 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 designSystematic review
Domainnot available
GenreReview

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
Published2020
Admission routes1
Has abstractyes

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