Varicocelectomy: microsurgical subinguinal technique is the treatment of choice.
Bibliographic record
Abstract
It is reported that 35% to 40% of infertile men have a palpable varicocele (dilated testicular veins), whereas the prevalence of a varicocele in the general male population is about 15%.1,2,3 Although varicoceles have been associated with impaired male fertility potential, it is also clear that a significant proportion of men with a varicocele (about 75%) are fertile.2,4,5 As such, a cause and effect relationship between varicocele and male infertility has not been conclusively established.6 The effect of varicocelectomy on male fertility is also controversial.6–10 Uncontrolled studies have generally shown improved semen quality and pregnancy outcome after surgery.11 On the other hand, the results of randomized controlled studies of varicocelectomy for clinical varicocele (only a few such studies are published) are equivocal.12–15 Despite the absence of clear evidence for a positive effect of varicocelectomy, many clinicians consider the data sufficient to support the practice of this surgery, and varicocele is the most commonly treated condition in men with infertility in North America.8 The benefit of varicocele repair must be balanced by the risk associated with the procedure itself. As such, it is important to select the procedure with the highest success and lowest complication rate. Also, it is important to consider assisted reproductive technologies (ARTs) as an alternative to varicocelectomy in infertile couples.16
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.020 | 0.007 |
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".