Population‐based evaluation of the effectiveness of two regimens for emergency contraception
Bibliographic record
Abstract
OBJECTIVE: To estimate and compare the effectiveness of the levonorgestrel and Yuzpe regimens for hormonal emergency contraception in routine clinical practice. METHODS: A retrospective population-based study included women who accessed emergency contraceptives for immediate use prescribed by community pharmacists in British Columbia, Canada, between December 2000 and December 2002. Linked administrative healthcare data were used to discern the timings of menses, unprotected intercourse, and any pregnancy-related health services. A panel of experts evaluated the compatibility of observed pregnancies with the timing of events. The two regimens were compared with statistical adjustments for potential confounding. RESULTS: Among 7493 women in the cohort, 4470 (59.7%) received levonorgestrel and 3023 (40.3%) the Yuzpe regimen. There were 99 (2.2%) compatible pregnancies in the levonorgestrel group and 94 (3.1%) in the Yuzpe group (P=0.017). The estimated odds ratio for levonorgestrel compared with the Yuzpe regimen after adjusting for potential confounders was 0.64 (95% confidence interval 0.47-0.87). Against an expected pregnancy rate of approximately 5%, the relative and absolute risk reductions were 56.0% and 2.8%, respectively, for levonorgestrel and 36.7% and 1.8% for the Yuzpe regimen. CONCLUSION: The levonorgestrel regimen is more effective than the Yuzpe regimen in routine use. The data suggest that both regimens are less effective than has been observed in randomized trials.
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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 | 0.010 | 0.034 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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 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".