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BACKGROUND: Unexplained infertility remains a diagnostic and therapeutic challenge. Dual trigger, combining gonadotropin-releasing hormone (GnRH) agonist and human chorionic gonadotropin (hCG), has been proposed to more closely mimic the physiological mid-cycle gonadotropin surge than hCG alone in gonadotropin-stimulated intrauterine insemination (IUI) cycles. OBJECTIVES: To evaluate whether dual trigger improves biochemical pregnancy outcomes compared with hCG-only trigger in gonadotropin-stimulated IUI cycles DESIGN: Retrospective cohort study SETTINGS: Single-center, tertiary referral center PATIENTS AND METHODS: Between April 2021 and September 2022, 96 patients underwent IUI after ovarian stimulation with gonadotropins (53 hCG-only, 43 dual trigger). Baseline demographic and clinical characteristics included female age (29.5±2.5 vs. 27.2±3.5 years), male age (33.3±4.0 vs. 31.6±3.5 years), body mass index (BMI) (24.0 vs. 25.0 kg/m 2 ), gonadotropin dose (median 675 IU), treatment duration (median 9 days), dominant follicle size (18 mm vs. 17 mm), and endometrial thickness (9 mm vs. 8 mm). MAIN OUTCOME MEASURES: Biochemical pregnancy, defined as serum β-hCG ≥5 mIU/mL. SAMPLE SIZE: 96 patients (53 hCG-only, 43 dual trigger) RESULTS: Biochemical pregnancy occurred in 18.6% of the dual trigger group and 11.3% of the hCG-only group ( P =.315). The odds of biochemical pregnancy were higher with dual trigger but not statistically significant (OR=1.8, 95% CI: 0.6–5.6). Subgroup analysis revealed a significant association between infertility duration and biochemical pregnancy ( P =.04), with 76.9% of conceptions occurring in women with 2–3 years of infertility. CONCLUSIONS: Dual trigger did not significantly improve biochemical pregnancy rates compared with hCG-only trigger (OR=1.8, 95% CI: 0.6–5.6). Infertility duration was the only significant predictor of treatment success. Larger multi-center trials are required due to the current study's limited power. LIMITATIONS: Retrospective design, single-center setting, and limited sample size may restrict generalizability.
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Efe et al. (2026) studied this question.
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