Age and dual trigger were found to be significant predictors of live birth in POSEIDON group 3 and 4 women treated with the GnRH antagonist protocol: a retrospective cohort study.

OBJECTIVE

Despite recent advancements in assisted reproductive technology (ART), the effective management of patients with poor ovarian response (POR) remains a formidable challenge. While various treatment strategies and predictors of live births have been documented to provide guidance to fertility specialists in managing poor responders, research efforts have predominantly encompassed all POSEIDON groups. In this study, our objective was to analyze the factors correlated with live births (LB) within a subset of the POSEIDON groups, with a particular focus on POSEIDON groups 3 and 4.

PATIENTS AND

METHODS

Charts of 406 patients belonging to POSEIDON groups 3 and 4 who underwent ART treatment at a university-affiliated infertility clinic following a gonadotropin-releasing hormone (GnRH) antagonist cycle between January 2016 and December 2021 were analyzed. Clinically significant factors associated with live births were incorporated into a logistic regression model for multivariate analysis to ascertain independent predictors of LB. Additionally, a receiver operating characteristic (ROC) curve analysis was conducted to establish the optimal cut-off values.

RESULTS

Live births were achieved in 48 cycles (8.7%). Female age (OR, 0.930; 95% CI: 0.874-0.991; p < 0.024), baseline serum luteinizing hormone (LH) levels (OR, 0.854; 95% CI: 0.741-0.984; p < 0.029), and dual triggers (OR, 4.004; 95% CI: 1.290-12.426; p < 0.016) were identified as independent factors associated with LB following multivariate logistic regression analysis. The optimal age cut-off was determined to be 33 years, with a sensitivity of 70.8% and specificity of 75%.

CONCLUSIONS

Younger age, lower baseline serum LH levels, and dual-trigger administration appear to enhance the likelihood of live birth in POSEIDON groups 3 and 4 following treatments with the GnRH antagonist protocol.