Effect of sperm DNA fragmentation on embryo euploidy rate in assisted reproductive technologies: a systematic review and meta-analysis
Bibliographic record
Abstract
To quantitatively evaluate the association between sperm DNA fragmentation (SDF) and embryo euploidy rates in assisted reproductive technology (ART) cycles through a systematic review and meta-analysis. Following the PRISMA 2020 guidelines, a comprehensive search of PubMed, Web of Science, Embase, Scopus, and the Cochrane Library was conducted from inception to August 5, 2025. Eligible studies included infertile couples undergoing in vitro fertilization (IVF) or intracytoplasmic sperm injection (ICSI), in which SDF was assessed using validated assays and embryo euploidy was determined via preimplantation genetic testing for aneuploidy (PGT-A). The Newcastle–Ottawa Scale was used for quality assessment. Pooled odds ratios (ORs) with 95% confidence intervals (CIs) were calculated using random- or fixed-effects models based on heterogeneity. Six studies involving 1,516 ART cycles met the inclusion criteria. All studies measured SDF using the sperm chromatin structure assay (SCSA), with cutoff values ranging from 15 to 30%. Embryo chromosomal status was evaluated at the blastocyst stage using PGT-A platforms, such as next-generation sequencing (NGS), array comparative genomic hybridization (aCGH), or single nucleotide polymorphism (SNP) arrays, with whole genome amplification (WGA) applied as a pre-analytical step rather than a detection method. Meta-analysis revealed no significant association between high SDF and embryo euploidy when using the 15% cutoff (pooled OR = 0.897; 95% CI 0.741–1.085; I 2 = 0.0%). At the 30% cutoff, high SDF (DFI ≥ 30%) was associated with lower embryo euploidy rates (pooled OR = 0.742; 95% CI 0.558–0.988; I 2 = 62.2%). Elevated SDF, particularly above 30%, is associated with a reduced likelihood of obtaining euploid embryos in ART cycles, suggesting a potential threshold-dependent effect of sperm DNA integrity on embryo chromosomal normality. These findings support the integration of SDF assessment into the evaluation of selected couples, especially in cases of recurrent ART failure or advanced maternal age. Further prospective studies with standardized SDF protocols and uniform PGT-A methods are warranted to validate these results.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.012 | 0.028 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.017 | 0.035 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".