Time to improvement in semen parameters after microsurgical varicocelectomy in men with severe oligospermia
Bibliographic record
Abstract
INTRODUCTION: We aimed to determine the time and predictive factors of semen quality improvement in men with severe oligospermia after microsurgical varicocelectomy. METHODS: Men with total motile sperm count (TMSC) <5 million on two semen analyses were identified from May 2015 to August 2017. Postoperative semen analysis was collected at 3-6 months and >6 months. We evaluated preoperative factors for successful semen quality upgrading based on assisted reproductive technology (ART) eligibility: in vitro fertilization [IVF] (<5 million), intrauterine insemination (IUI) (5-9 million), and natural pregnancy (>9 million). We compared men with TMSC <5 million to those with TMSC 5-9 million. Data are reported as means and standard error of the mean (SEM). Pregnancy data was collected by phone interview at >6 months postoperatively RESULTS: A total of 33 men were included. TMSC improved from 1.5±0.2 to 7.3±1.8 million at 3-6 months (p<0.05) and 12.2±3.6 million at >6 months (p<0.05). There was no statistical difference in TMSC between 3-6 months and >6 months. Sixteen (48.5%) men upgraded semen quality into the range of natural pregnancy. Preoperative TMSC from 2-5 million was predictive of upgrading semen quality. Twenty-four couples were contacted by phone; 20 were attempting pregnancy in the postoperative period and five (25%) of them had achieved natural pregnancy. CONCLUSIONS: Men with TMSC <5 million can expect the largest improvement in TMSC from 3-6 months postoperatively with minimal improvement thereafter. Preoperative TMSC >2 million was most predictive of semen quality upgrading.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.002 | 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".