Sperm DNA fragmentation: threshold value in male fertility
Bibliographic record
Abstract
BACKGROUND: The extent of sperm DNA fragmentation, which can be measured by the TUNEL assay, is one of the determinants of male fertility. However, the clinical application of this test to in-vivo situations is difficult owing to the absence of a statistically validated threshold value. METHODS: The aim of this study was to compare the results of TUNEL assay applied to semen samples from men of proven fertility (n = 47) and patients from an infertile population (n = 66), in order to establish a discriminating threshold value. RESULTS: Infertile patients had a higher mean level of DNA fragmentation than men of proven fertility (40.9 +/- 14.3% versus 13.1 +/- 7.3%, respectively; P < 0.001). The area under the receiver operating characteristics curve was 0.93 for 20% sperm DNA fragmentation. The calculated threshold value for TUNEL assay to distinguish between fertile controls and infertile men was 20%. At this threshold, specificity was 89.4 [95% confidence interval (CI) 83.7-95.1] and sensitivity was 96.9% (95% CI 93.8-100). The positive and negative predictive values of the 20% sperm DNA fragmentation threshold were high: 92.8% (95% CI 87.9-97.5) and 95.5% (95% CI 91.6-99.3), respectively. CONCLUSION: This study demonstrates that sperm DNA fragmentation, as measured by TUNEL assay, is a highly valuable indicator of male fertility.
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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 | 0.007 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".