Microscopic evaluation of the vasal fluid for sperm at the time of vasectomy reversal: Do we really need to check?
Bibliographic record
Abstract
INTRODUCTION: During vasectomy reversal, intraoperative microscopic evaluation of the vasal fluid for sperm presence/quality can inform of the possibility of epididymal obstruction and need for a vasoepididymostomy (VE). In an effort to validate the utility of microscopic vasal fluid evaluation, the current initiative correlates gross vasal fluid characteristics with sperm presence and quality in a large series of VRs. METHODS: A total of 1267 vasectomy reversals yielded a total of 2522 vasal-units (right/left sides) for analysis. During vasectomy reversal, vasal fluid was sampled from the testicular-end vas and the fluid was characterized (thick-paste/opaque/translucent/clear). Each aspirate underwent microscopic evaluation for sperm quality and was categorized as: motile sperm/intact-non-motile sperm/sperm parts/no sperm. The predictive utility of the gross vasal fluid characteristics with respect to microscopic sperm presence and quality was analyzed. RESULTS: Among the 2522 vasal units analyzed, the side-to-side (left-right) concordance of vasal fluid quality and microscopic vasal sperm quality was 72% and 52%, respectively. When thick-pasty fluid was observed, no sperm were seen in the samples in 53% of cases, and if present, only non-motile sperm were observed. Even in the setting of more favorable vasal fluid characteristics (clear, translucent, and opaque fluid), no sperm were seen in 6-11% of cases, suggesting the possibility of epididymal obstruction and the need for VE. CONCLUSIONS: Intraoperative microscopic evaluation of the vasal fluid for sperm is a necessary practice during vasectomy reversal to optimize surgical outcomes. Reliance on gross vasal fluid characteristics in isolation may lead to unrecognized epididymal obstruction, and the need for a VE, in approximately 11% of cases.
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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 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".