Prognostic factors for a favorable outcome after varicocele repair in adolescents and adults
Bibliographic record
Abstract
The effect of varicocele repair on male fertility remains controversial. It would be helpful to determined which men would benefit most from varicocele repair, and target repair efforts at those individuals. A detailed review of the literature on prognostic factors for varicocele repair was performed using the PubMed NLM database. We found that the best predictor of postvaricocelectomy semen parameters is the preoperative semen parameters. The greatest improvements in semen parameters were found in men with larger varicoceles. While there is controversy, higher testosterone, younger age and larger testis size, in some studies predict for improvements in semen parameters postvaricocelectomy. A nomogram has been developed to predict the postvaricocelectomy semen parameters based on the preoperative semen parameters, varicocele grade and the age of the man (www.fertilitytreatmentresults.com). Limited data consistently demonstrates the greatest improvements in DNA fragmentation rates in men with higher baseline DNA fragmentation rates. With respect to reproductive outcomes, higher baseline sperm density consistently predicts for natural pregnancy or assisted reproductive technology (ART) pregnancy rates. In addition, varicocele repair does seem to reduce the need for more invasive modalities of ART. In conclusion, we can now start to use specific parameters such as baseline semen quality, varicocele grade and patient age to predict post-repair semen quality and fertility potential following varicocelectomy.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".