Personalized prediction model for miscarriage: in-depth sperm DNA fragmentation

流产个性化预测模型:深入的精子DNA碎片化分析

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Abstract

PURPOSE: We investigated how different types of sperm DNA fragmentation (SDF) in males, in conjunction with varying levels of female reproductive potential, jointly impact ICSI outcomes. METHODS: We retrospectively analyzed 195 couples undergoing ICSI, categorizing them by normal or poor prognosis according to POSEIDON criteria. Female factors included age, anti-Müllerian hormone (AMH), and oocyte retrieval numbers. Male factors included semen parameters, total SDF, and specific double-strand breaks (DSBs). Reproductive outcomes were followed up at different gestational stages, including clinical pregnancy, early gestation failure, live birth, and miscarriage. Risk factors were identified using univariate and multivariable logistic regression, and their predictive power was assessed via the receiver operating characteristic (ROC) curve. RESULTS: In the normal group, female factors were primarily associated with reproductive failures. Non-pregnancy cases had lower AMH (4 ng/mL vs. 3.2 ng/mL), and miscarriage cases had fewer oocytes retrieved (15 vs. 10.5). However, the risk factor profile was distinct in poor prognosis. Male factors, including reduced sperm motility (68% vs. 54.5%), lower normal sperm morphology (5.5% vs. 2.5%), and elevated DSBs (7.5% vs. 18.8%) were linked to miscarriage. DSBs presented as the independent predictor of miscarriage risk (odds ratio: 1.19, 95% CI: 1.04-1.36), with a DSB cutoff of 19% providing 81% accuracy in predicting miscarriage. CONCLUSION: Paternal effect is pronounced in women with poor prognosis, where elevated DSBs are linked to an increased risk of miscarriage. We propose a refined pipeline in which DSB testing is considered as initial evaluation before assisted reproductive treatments, especially for infertile couples with poor prognosis.

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