Prevalence of Y-chromosomal microdeletions and karyotype abnormalities in a cohort of Lebanese infertile men
Bibliographic record
Abstract
BACKGROUND: Male infertility is the main issue that accounts for 50% of infertility in couples. There are about 25% of men suffering from nonobstructive infertility with chromosomal abnormalities and/or microdeletions of the long arm of the Y-chromosome. MATERIALS AND METHODS: A retrospective chart review was performed on 241 men who performed Y-chromosome microdeletions and karyotype testing. RESULTS: Six patients had microdeletions. Three patients had AZFc microdeletion, of which one had both AZFc/d microdeletions. Three patients had AZFb/c microdeletion. There was no AZFa microdeletion. One out of the six patients had abnormal karyotype (mos, X[17]/46, XY[13]). Four patients were azoospermic, two had severe oligospermia, with sperm count <5 million/ml, and two patients had small size testicles on ultrasound. All were advised microsurgical testicular sperm extraction. Three were done, and one was successful resulting in sperm retrieval. The most common karyotype abnormalities were 47, XXY (Klinefelter syndrome) in 27% of cases. CONCLUSION: Laboratory genetic testing is advised for males with nonobstructive infertility. Any abnormal finding can yield substantial consequences to assisted reproductive techniques or fertility treatment. It can offer a stable diagnosis for those with infertility issues. It is important to conduct counseling and routine genetic testing before assisted reproductive techniques.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.000 |
| 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 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".