Loop Electrosurgical Excision Procedure in Managing Persistent Low-Grade Abnormality or Human Papillomavirus Positivity
Bibliographic record
Abstract
OBJECTIVES: The aims of the study were to estimate the rate and to identify predictors of high-grade abnormalities among women with persistent low-grade abnormalities or high-risk human papillomavirus (hrHPV) positivity for at least 2 years stratified by presence (high risk) or absence (low risk) of previous high-grade results or HPV 16/18. MATERIALS AND METHODS: A retrospective cohort study of patients who underwent a loop electrosurgical excision procedure (LEEP) for persistent low-grade or hrHPV positivity was performed. Patients were stratified based on whether they had a history of high-grade and/or HPV 16/18 positivity. Rates of high-grade or worse abnormalities on LEEP were compared using Fisher exact tests. Logistic regression was used to evaluate the associations between patient characteristics and high-grade results on the LEEP. RESULTS: Three hundred eleven LEEPs were performed for persistent low-grade or hrHPV positivity. The rates of occult high grade were 12% and 22% among the low- and high-risk groups, respectively. Compared with those 45 years and older, the adjusted odds of high grade was 3.79 (95% CI = 1.19-12.1) for women aged 25-29 years. The odds of high grade was higher among current versus never smokers (6.40; 95% CI = 2.01-20.4) and those with a history of high-grade abnormality (2.23; 95% CI = 1.12-4.43). At 2 years, approximately half had an abnormal cytology and/or hrHPV positivity result independent of whether high grade was identified on their LEEP specimen. CONCLUSIONS: Patients with persistent low-grade abnormalities or persistent hrHPV should be counseled on the risks and benefits of a LEEP given that 12%-22% have a risk of occult high grade, especially if they have a history of high-grade dysplasia.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".