Aromatase inhibitors in the treatment of oligozoospermic or azoospermic men: a systematic review of randomized controlled trials
Bibliographic record
Abstract
The aim of this study as to analyze published evidence regarding the effectiveness of aromatase inhibitor therapy on improving spermatogenesis in infertile men. We carried out a systematic review of randomized controlled trials. The date of the most recent search was October 4, 2015. Two authors independently selected relevant clinical trials, assessing their methodological quality and extracting data. Three studies were included in this review with a total of 100 participants; however, we were able to include data from only 54 participants in the analysis. In the representation of meta-analysis with a single study comparing testolactone versus placebo, related to the hormone concentrations, there was a statistically significance difference favoring the use of testolactone for Luteinizing Hormone (LH); Estrogen (E2); free Testosterone (free T); free Estrogen (free E2); 17-Hydroxyprogesterone (17OHP); prolactin (PRL). In another analysis from a single study comparing letrozole versus anastrozole, there was also a statistically significance difference favoring the use of letrozole for the increase in both the sperm count and LH. There is only low quality evidence regarding the effectiveness of aromatase inhibitor therapy in infertile men. Further trials are needed with standardized interventions and outcomes.
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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 | 0.009 | 0.026 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.011 | 0.010 |
| Bibliometrics | 0.006 | 0.006 |
| 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) | 0.005 | 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".