Effect of Uterine Cavity Measurements on Medical Management Failure in Early Pregnancy Loss [296]
Bibliographic record
Abstract
INTRODUCTION: The purpose of our study was to evaluate the predictive value of uterine content ultrasound measurements in predicting medical management failure of early pregnancy loss. METHODS: We conducted a retrospective cohort study in a single university-affiliated hospital center on all women discharged from the emergency department with a diagnosis of early pregnancy failure who were managed with misoprostol. Only women with ultrasonographic data available for review between 2011 and 2013 were included. Exposure of interest consisted of uterine cavity measurements including: anteroposterior distance, longitudinal distance, transverse distance, and uterine cavity volume. Outcome was defined as need for dilatation and curettage (D&C) or unplanned return to the emergency department. Logistic regression was used to identify ultrasonographic measurements independently associated with failed medical management. RESULTS: Among 823 women presenting to the emergency department with first-trimester bleeding, 226 met inclusion criteria. Of all measurements evaluated, anteroposterior distance was found to be independently associated with D&C and unplanned return to the emergency department. When using an anteroposterior distance cutoff of 15 mm, women were more likely to require D&C, 2.58 (1.27–5.24; P=.01) and to have an unplanned return to the emergency department, 2.63 (1.41–4.88; P=.002). In women with an anteroposterior distance below 15 mm, 87.7% had successful medical management of early pregnancy loss and 80.0% did not require an unplanned return to the emergency department. CONCLUSION: Although there is a need for further validation, using an anteroposterior distance cutoff of 15 mm in a hospital-based population of women with early pregnancy failure may be helpful in selecting patients who can safely be managed medically.
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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 | 0.002 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".