Natural Cycle In Vitro Fertilization Outcomes

Natural cycle IVF (NC-IVF) refers to the retrieval of a single mature oocyte in an unstimulated menstrual cycle, avoiding the exogenous gonadotropin regimens characteristic of conventional protocols. This method has gained traction for its minimal intervention profile, reduced risk of ovarian hyperstimulation and lower medication costs. Although per-cycle live birth rates are generally lower than those achieved with stimulated cycles, patient selection and cumulative treatment strategies can yield comparable overall success, especially in women with diminished ovarian reserve or poor response to stimulation. Recent work has illuminated the roles of follicular growth dynamics, hormonal markers and precise timing of oocyte retrieval in optimising fertilisation rates and embryo quality. Computational models have also been developed to predict cycle outcomes, enhancing clinician–patient counselling. As interest grows in more physiological approaches to assisted reproduction, NC-IVF is emerging as a globally significant option that combines safety, patient comfort and practical applicability within varied healthcare settings.

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Natural Cycle In Vitro Fertilization Outcomes publication trend

The graph below shows the total number of articles in natural cycle in vitro fertilization outcomes across all publications each year (not limited to Nature Index journals).

Technical terms

Natural cycle IVF (NC-IVF): In vitro fertilisation conducted without pharmacological ovarian stimulation, retrieving a single naturally selected oocyte.

Controlled ovarian hyperstimulation: Use of exogenous gonadotropins to induce development of multiple follicles in conventional IVF protocols.

Diminished ovarian reserve (DOR): A clinical condition marked by reduced quantity and quality of oocytes, often assessed by anti-Müllerian hormone levels and antral follicle count.

Follicular diameter: Ultrasound measurement of follicle size, which correlates with oocyte maturity and fertilisation potential.

Machine learning prediction model: A computational algorithm trained on historical cycle data to estimate the probability of live birth in NC-IVF.

Area under the curve (AUC): A statistical metric evaluating a model’s overall discriminative performance between successful and unsuccessful outcomes.

References

1. The potential influence of follicle diameter on natural cycle in vitro fertilization among women with diminished ovarian reserve: a retrospective cohort study. Journal of Ovarian Research (2023).
2. Comparison of embryo quality and pregnancy outcomes for patients with low ovarian reserve in natural cycles and mildly stimulated cycles: a cohort study. Journal of Obstetrics and Gynaecology (2024).
3. Live-Birth Prediction of Natural-Cycle In Vitro Fertilization Using 57,558 Linked Cycle Records: A Machine Learning Perspective. Frontiers in Endocrinology (2022).
4. Gonadotropin Stimulation Reduces the Implantation and Live Birth Rate but Not the Miscarriage Rate of Embryos Transferred When Compared to Unstimulated In Vitro Fertilization. Reproductive Sciences (2022).