Comparative analysis of sperm preparation techniques on DNA fragmentation and clinical outcomes: a network meta-analysis

Introduction: Elevated sperm DNA fragmentation negatively affects assisted reproductive technology outcomes. Although multiple sperm preparation techniques are used, existing evidence is largely limited to pairwise comparisons. We performed a systematic review and network meta-analysis to investigate the most effective technique for reducing sperm DNA fragmentation and improving clinical outcomes. Methods: PubMed, Embase and Cochrane Central Register of Controlled Trials were searched to July 26, 2025. Due to the limited randomized studies for sperm DNA fragmentation (N=2), both randomized and non-randomized studies comparing at least two preparation techniques were included for sperm DNA fragmentation analyses, while only randomized controlled trials were included for clinical outcomes to ensure the highest stringency for treatment efficacy. Data were synthesized using frequentist random-effect network meta-analysis. Results: ), network estimates indicated that microfluidic sperm sorting (MFSS) was associated with a significant showed the greatest reduction in DNA fragmentation (SMD -2.64; 95%CI -3.53 to -1.75), followed by magnetic-activated cell sorting (MACS) combined with density gradient centrifugation (DGC; SMD, -1.53; 95%CI -2.93 to -0.12). Fifteen randomized controlled trials reported clinical outcomes. Magnetic-activated cell sorting combined with density gradient centrifugation was associated with a higher clinical pregnancy rate compared with density gradient centrifugation alone (OR1.93; 95% CI 1.23 --3.02), and pairwise meta-analysis showed a lower miscarriage rate (OR 0.65; 95% CI 0.46 -0.91). Discussion: While MFSS and MACS-based combinations showed the greatest numerical reduction in sperm DNA fragmentation, these findings are characterized by high heterogeneity and low certainty of evidence. Although some improvements in clinical pregnancy and miscarriage rates were observed with the combination of MACS and DGC, the lack of robust, large-scale data prevents a definitive clinical recommendation outcomes. Systematic Review Registration: https://www.crd.york.ac.uk/PROSPERO/view/CRD420251181955, identifier CRD420251181955.