Pregnancy outcome after loop electrosurgical excision procedure: a systematic review
Bibliographic record
Abstract
OBJECTIVE: To examine the association of loop electrosurgical excision procedure (LEEP) and subsequent pregnancy outcomes. DATA SOURCES: A computerized search of MEDLINE and PubMed was conducted using the keys words "pregnancy" and "loop electrosurgical excision procedure," "LEEP," "LETZ," "LLETZ," or "loop excision." References from identified publications were manually searched and cross referenced to identify additional relevant articles. METHODS OF STUDY SELECTION: Studies were included that compared women who had had LEEP to women who had not had the procedure and that reported on subsequent pregnancy outcomes. Studies were excluded if there was no control group, if the LEEP was performed during the pregnancy, or if only an abstract was available. Five of 36 articles identified met the criteria for systematic review. TABULATION, INTEGRATION, AND RESULTS: Women who had had LEEP were more likely to have preterm birth (odds ratio [OR] 1.81, 95% confidence interval [CI] 1.18, 2.76; P = .006) and low birth weight infants (<2500 g) (OR 1.60, 95% CI 1.01, 2.52; P = .04), but there was no difference in cesarean delivery, precipitous labor, labor induction, or neonatal intensive care unit admission. A subgroup analysis including only studies matching for smoking status revealed that preterm birth was still more common in women who had had LEEP (OR 2.53, 95% CI 1.42, 4.49; P = .001), but birth weight under 2500 g was no longer significantly different. CONCLUSION: LEEP appears to be associated with subsequent preterm birth, even when smoking status is matched. Studies with adequate sample size are needed to further evaluate the relationship of LEEP and preterm birth, controlling for potential confounders, including depth of the tissue sample.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".