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Assisted reproductive technology failures
Laura Rienzi1, Dominique de Ziegler2
1IVIRMA Global Research Alliance, IVRMA Italy, Rome, Italy; University of Urbino, Department of Biomolecular Sciences, Urbino, Italy.
Fertility and Sterility
|May 18, 2026
Summary
Assisted reproductive technologies (ART) face failures despite advancements. This review examines biological and clinical factors causing ART failures to improve future success rates.
Area of Science:
- Reproductive medicine
- Infertility research
- Clinical embryology
Background:
- Assisted reproductive technologies (ART) have significantly advanced, improving success rates for infertility treatment.
- Despite progress, recurrent implantation failures and treatment cancellations remain a challenge in ART.
- Understanding the root causes of ART failures is crucial for optimizing patient outcomes.
Purpose of the Study:
- To comprehensively review biological and clinical factors contributing to assisted reproductive technology failures.
- To assess the predictive value of identified factors on the success of future ART attempts.
- To explore potential strategies for improving ART outcomes and reducing failure rates.
Main Methods:
- Systematic literature review of studies on assisted reproductive technology failures.
- Analysis of biological factors (e.g., gamete quality, uterine environment).
- Evaluation of clinical factors (e.g., protocols, patient characteristics).
Main Results:
- Identified key biological factors include oocyte quality, sperm parameters, and endometrial receptivity.
- Clinical factors such as stimulation protocols, laboratory procedures, and patient age significantly influence ART success.
- Specific factors demonstrate varying predictive values for future ART attempt success.
Conclusions:
- ART failures are multifactorial, involving complex interactions between biological and clinical elements.
- Tailoring treatment strategies based on individual patient profiles and identified risk factors can enhance ART success.
- Further research is needed to refine predictive models and develop targeted interventions for ART failure.
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