Comparison of sperm parameters and fertility rate in subclinical varicocele patients treated with varicocelectomy versus no varicocelectomy: a systematic review
Bibliographic record
Abstract
Introduction: Subclinical varicocele is defined as non-palpable varicocele which diagnosed solely through imaging examination, namely ultrasonography. Despite the current high prevalence of subclinical varicocele as one of the most common cause of men infertility, there is still lack of evidence regarding the need to perform varicocelectomy among these patients. This systematic review aims to evaluate and compare the sperm parameters and fertility rate of subclinical varicocele patients treated with varicocelectomy versus no treatment. Methods: A systematic literature search was conducted on the international databases PubMed, Scopus, Cochrane, EMBASE, EBSCOHost, and Google Scholar published in the last ten years up to August 21st, 2022. Risk of bias assessment was performed using the Newcastle-Ottawa Scale tools for cohort study and converted regarding the AHRQ standards. Results: Three cohort studies were conducted in three different countries with 363 patients. The risk of bias assessment revealed that all of the three studies included in this review have good quality and low risk of bias. Varicocelectomy significantly improves sperm parameters in terms of sperm concentration (p<0.05) and sperm motility (p<0.05) while its effects on sperm morphology are not significant (p>0.05). The effects of varicocelectomy on fertility rate are reported by one study by Cantoro et al. as significant (p=0.011). Conclusion: Varicocelectomy correction has been proved to significantly improve sperm parameters in terms of sperm concentration and motility, while its effect on fertility rate remains unclear and no conclusion can be drawn yet. Therefore, this study recommends further randomized controlled studies with larger sample size in the future to prove the effectiveness of varicocelectomy in subclinical varicocele patients before its implementation in clinical settings.
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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 | 0.006 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.011 | 0.012 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".