Sperm DNA fragmentation index does not correlate with blastocyst aneuploidy or morphological grading
Bibliographic record
Abstract
High DNA fragmentation index (DFI) may be associated with poor outcome after IVF. Our aim was to determine whether DFI impacts blastocyst quality or clinical outcome. This retrospective study included 134 couples who underwent 177 IVF-ICSI and pre-implantation genetic screening (PGS) cycles during January 1st, 2014-March 31st, 2016 and had documented previous DFI. Group 1 (DFI>30%) encompassed 25 couples who underwent 36 cycles; Group 2 (DFI 15-30%) included 45 couples and 57 cycles; group 3 (DFI<15%) included 64 couples and 83 cycles. Male partners within group 1 were older (45.1 compared to 40.6 and 38.3 years, respectively, p<0.05), had higher BMI (32.4 compared to 26.6 and 25.8 respectively, p<0.05) and lower sperm count and motility (46*106/ml and 35.5%, respectively) compared to groups 2 (61.8*106/ml and 46.6%, respectively) and 3 (75.8*106/ml and 55.1%, respectively, p<0.05). Female parameters including ovarian reserve and response and embryo development were similar. Total numbers of biopsied blastocysts were 116, 175 and 259 in groups 1, 2 and 3, respectively. PGS for 24 chromosomes revealed comparable euploidy rate of 46-50.4%, with a similar morphological classification. No significant differences were found regarding pregnancy rates or pregnancy loss. It seems that DFI doesn't correlate with blastocyst aneuploidy or morphological grading.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 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".