Sonographic Lower Uterine Segment Thickness After Prior Cesarean Section to Predict Uterine Rupture: A Systematic Review and Meta-analysis
Bibliographic record
Abstract
(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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.016 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.011 | 0.021 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".