Effectiveness of vasectomy using cautery
Bibliographic record
Abstract
BACKGROUND: Little evidence supports the use of any one vas occlusion method. Data from a number of studies now suggest that there are differences in effectiveness among different occlusion methods. The main objectives of this study were to estimate the effectiveness of vasectomy by cautery and to describe the trends in sperm counts after cautery vasectomy. Other objectives were to estimate time and number of ejaculations to success and to determine the predictive value of success at 12 weeks for final status at 24 weeks. METHODS: A prospective, non-comparative observational study was conducted between November 2001 and June 2002 at 4 centers in Brazil, Canada, the UK, and the US. Four hundred men who chose vasectomy were enrolled and followed for 6 months. Sites used their usual cautery vasectomy technique. Earlier and more frequent than normal semen analyses (2, 5, 8, 12, 16, 20, and 24 weeks after vasectomy) were performed. Planned outcomes included effectiveness (early failure based on semen analysis), trends in sperm counts, time and number of ejaculations to success, predictive value of success at 12 weeks for the outcome at 24 weeks, and safety evaluation. RESULTS: A total of 364 (91%) participants completed follow-up. The overall failure rate based on semen analysis was 0.8% (95% confidence interval 0.2, 2.3). By 12 weeks 96.4% of participants showed azoospermia or severe oligozoospermia (< 100,000 sperm/mL). The predictive value of a single severely oligozoospermia sample at 12 weeks for vasectomy success at the end of the study was 99.7%. One serious unrelated adverse event and no pregnancies were reported. CONCLUSION: Cautery is a very effective method for occluding the vas. Failure based on semen analysis is rare. In settings where semen analysis is not practical, using 12 weeks as a guideline for when men can rely on their vasectomy should lessen the risk of failure compared to using a guideline of 20 ejaculations after vasectomy.
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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 | 0.004 | 0.020 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".