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ORIGINAL RESEARCH article

Front. Endocrinol.
Sec. Reproduction
Volume 15 - 2024 | doi: 10.3389/fendo.2024.1432943

Development and validation of a clinical prediction model for blastocyst formation during IVF/ICSI-ET

Provisionally accepted
Xingnan Liu Xingnan Liu 1Zhang Na Zhang Na 1*Jingyun Zhao Jingyun Zhao 1Yi Zhang Yi Zhang 1Zhaoyan Nie Zhaoyan Nie 1Qiaoxia Li Qiaoxia Li 1Lina Guo Lina Guo 1Chunhui Fan Chunhui Fan 1Jianfeng Zhang Jianfeng Zhang 2
  • 1 Fourth Hospital of Hebei Medical University, Shijiazhuang, China
  • 2 Third Hospital of Hebei Medical University, Shijiazhuang, Hebei Province, China

The final, formatted version of the article will be published soon.

    Purpose: This study aims to create and validate a clinical model that predict the probability of blastocyst formation in IVF/ICSI-ET cycles.: This study employed a retrospective methodology, gathering data from 4961 cleavage-stage embryos that cultured in the reproductive center's of the Fourth Hospital of Hebei Medical University between June 2020 and March 2024. 3472 were in the training set and 1489 were in the validation set when it was randomly split into the training set and validation set in a 7:3 ratio. The study employed both univariate and multivariate logistic regression analysis to determine the factors those influence in the process of blastocyst formation. Based on the multiple regression model, a predictive model of blastocyst formation during IVF was created. The calibration and decision curves were used to assess the effectiveness and therapeutic usefulness of this model.The following factors independently predicted the probability of blastocyst formation: the method of insemination, number of oocytes retrieved, pronuclear morphological score, the number of cleavage ball, cleavage embryo symmetry, fragmentation rate and morphological score and basal P levels of female.The receiver operating characteristic curve's area under the curve (AUC) in the training set is 0.742 (95% CI: 0.724,0.759), while the validation set's AUC is 0.729 (95% CI: 0.703,0.755), indicating a rather high clinical prediction capacity.Our generated nomogram has the ability to forecast the probability of blastocyst formation in IVF, hence can assist clinical staff in making informed decisions.

    Keywords: in vitro fertilization, Clinical prediction model, Blastocyst formation, Cleavage embryos, nomogram

    Received: 15 May 2024; Accepted: 04 Nov 2024.

    Copyright: © 2024 Liu, Na, Zhao, Zhang, Nie, Li, Guo, Fan and Zhang. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence: Zhang Na, Fourth Hospital of Hebei Medical University, Shijiazhuang, China

    Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.