Interpretable machine learning models for predicting clinical pregnancies associated with surgical sperm retrieval from testes of different etiologies: a retrospective study.

Background: The relationship between surgical sperm retrieval of different etiologies and clinical pregnancy is unclear. We aimed to develop a robust and interpretable machine learning (ML) model for predicting clinical pregnancy using the SHapley Additive exPlanation (SHAP) association of surgical sperm retrieval from testes of different etiologies.

Methods: A total of 345 infertile couples who underwent intracytoplasmic sperm injection (ICSI) treatment with surgical sperm retrieval due to different etiologies from February 2020 to March 2023 at the reproductive center were retrospectively analyzed.

[Impacts of different procedures of testicular sperm retrieval on testicular function and antisperm antibodies in azoospermia patients].

Objective: To investigate the influence of different procedures of testicular sperm retrieval on the levels of serum inhibin B (INHB), antisperm antibodies (AsAb), follicle-stimulating hormone (FSH), and testosterone (T) in patients with azoospermia.

Methods: We randomly assigned 210 azoospermia patients to receive testicular sperm extraction (TESE, n = 50), testicular sperm aspiration (TESA, n = 56), testicular fine needle aspiration (TEFNA, n = 64), or microscopic TESE (micro-TESE, n = 40). We measured the levels of serum INHB, FSH, and T and the positive rate of AsAb before and at 1 and 3 months after surgery.