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Journal of Assisted Reproduction and Genetics
Erschienen in:

27.01.2022 | Assisted Reproduction Technologies

The (decision) tree of fertility: an innovative decision-making algorithm in assisted reproduction technique

verfasst von: Maria Teresa Villani, Daria Morini, Giorgia Spaggiari, Chiara Furini, Beatrice Melli, Alessia Nicoli, Francesca Iannotti, Giovanni Battista La Sala, Manuela Simoni, Lorenzo Aguzzoli, Daniele Santi

Erschienen in: Journal of Assisted Reproduction and Genetics | Ausgabe 2/2022

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Abstract

Purpose

Several mathematical models have been developed to estimate individualized chances of assisted reproduction techniques (ART) success, although with limited clinical application. Our study aimed to develop a decisional algorithm able to predict pregnancy and live birth rates after controlled ovarian stimulation (COS) phase, helping the physician to decide whether to perform oocytes pick-up continuing the ongoing ART path.

Methods

A single-center retrospective analysis of real-world data was carried out including all fresh ART cycles performed in 1998–2020. Baseline characteristics, ART parameters and biochemical/clinical pregnancies and live birth rates were collected. A seven-steps systematic approach for model development, combining linear regression analyses and decision trees (DT), was applied for biochemical, clinical pregnancy, and live birth rates.

Results

Of fresh ART cycles, 12,275 were included. Linear regression analyses highlighted a relationship between number of ovarian follicles > 17 mm detected at ultrasound before pick-up (OF17), embryos number and fertilization rate, and biochemical and clinical pregnancy rates (p < 0.001), but not live birth rate. DT were created for biochemical pregnancy (statistical power–SP:80.8%), clinical pregnancy (SP:85.4%), and live birth (SP:87.2%). Thresholds for OF17 entered in all DT, while sperm motility entered the biochemical pregnancy’s model, and female age entered the clinical pregnancy and live birth DT. In case of OF17 < 3, the chance of conceiving was < 6% for all DT.

Conclusion

A systematic approach allows to identify OF17, female age, and sperm motility as pre-retrieval predictors of ART outcome, possibly reducing the socio-economic burden of ART failure, allowing the clinician to perform or not the oocytes pick-up.
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Metadaten
Titel
The (decision) tree of fertility: an innovative decision-making algorithm in assisted reproduction technique
verfasst von
Maria Teresa Villani
Daria Morini
Giorgia Spaggiari
Chiara Furini
Beatrice Melli
Alessia Nicoli
Francesca Iannotti
Giovanni Battista La Sala
Manuela Simoni
Lorenzo Aguzzoli
Daniele Santi
Publikationsdatum
27.01.2022
Verlag
Springer US
Erschienen in
Journal of Assisted Reproduction and Genetics / Ausgabe 2/2022
Print ISSN: 1058-0468
Elektronische ISSN: 1573-7330
DOI
https://doi.org/10.1007/s10815-021-02353-4

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