Evaluation of clinical usability and reproducibility of the American Society for Reproductive Medicine Müllerian Anomalies Classification.

OBJECTIVE

To study the usability, reproducibility and practicality of the revised American Society for Reproductive Medicine Müllerian Anomalies Classification (ASRM MAC2021) compared to the formerly used American Fertility Society (AFS) classification. The main focus of this paper is to present clinicians' assessment when using these classification systems and to explore possible benefits and disadvantages of the transformation of the AFS into the more recently published ASRM classification. To incorporate all commonly used classification systems, all cases were additionally classified using the ESHRE/ESGE and the VCUAM classification.

METHODS

An observational study using a questionnaire and opinion survey was conducted with the goal of comparing clinicians' subjective usability and reproducibility of the AFS classification with the newly presented ASRM MAC2021 classification. Cases of female genital malformations encompassed a wide range of various anomalies, including vaginal, cervical and adnexal conditions and associated malformations.

RESULTS

The study investigators rated the ASRM MAC2021 classification better in relation to usability and reproducibility compared to the AFS classification. It significantly improved diagnostic precision for vaginal and cervical anomalies and expanded recognition of adnexal malformations. However, challenges remain in addressing associated malformations. Clinicians ranked the ASRM MAC2021 higher than the AFS classification. However, investigators rated the ESHRE/ESGE and VCUAM classifications better in the overall assessment of female genital malformations.

CONCLUSION

The ASRM MAC2021 classification offers substantial improvements in diagnosing and managing female genital malformations, addressing limitations of the AFS system. With better usability and subjective reproducibility, further refinements are needed to fully address complex associated anomalies - emphasizing the importance of evolving classification systems.