Objective <p>This study aimed to develop a predictive model for the risk of no usable blastocyst formation in patients with normal ovarian reserve undergoing IVF.</p> Methods <p>The model was derived from 7,901 patients who underwent their first oocyte retrieval and subsequent blastocyst culture, of which 446 cases have no usable blastocysts formed. Univariate regression analyses, least absolute shrinkage and selection operator regression analysis were used to identify the association of patient and cycle characteristics with the presence of no available blastocyst and to create a nomogram. The performance of the nomogram was assessed using the receiver operating characteristic (ROC) curve and calibration curve, the net benefit threshold of prediction was determined using decision curve analysis (DCA).</p> Results <p>Multivariate analysis identified three independent predictors: the number of day 3 (D3) embryos, the number of high-quality D3 embryos, and the number of embryos used for blastocyst culture. A nomogram model was developed and internally validated using bootstrapping, demonstrating good discriminative ability with an area under the receiver operating characteristic curve (AUC) of 0.879(95%CI: 0.861–0.890).</p> Conclusions <p>The cycle-based nomogram can anticipate the probability of no available blastocyst formation in IVF/ICSI treatment. This can help doctors make appropriate clinical judgments and assist patients in managing their expectations effectively.</p>

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A cycle-based model to predict no usable blastocyst formation following cycles of in vitro fertilization in patients with normal ovarian reserve

  • Xue Wang,
  • Chen-yue Dong,
  • Cui-lian Zhang,
  • Shao-di Zhang

摘要

Objective

This study aimed to develop a predictive model for the risk of no usable blastocyst formation in patients with normal ovarian reserve undergoing IVF.

Methods

The model was derived from 7,901 patients who underwent their first oocyte retrieval and subsequent blastocyst culture, of which 446 cases have no usable blastocysts formed. Univariate regression analyses, least absolute shrinkage and selection operator regression analysis were used to identify the association of patient and cycle characteristics with the presence of no available blastocyst and to create a nomogram. The performance of the nomogram was assessed using the receiver operating characteristic (ROC) curve and calibration curve, the net benefit threshold of prediction was determined using decision curve analysis (DCA).

Results

Multivariate analysis identified three independent predictors: the number of day 3 (D3) embryos, the number of high-quality D3 embryos, and the number of embryos used for blastocyst culture. A nomogram model was developed and internally validated using bootstrapping, demonstrating good discriminative ability with an area under the receiver operating characteristic curve (AUC) of 0.879(95%CI: 0.861–0.890).

Conclusions

The cycle-based nomogram can anticipate the probability of no available blastocyst formation in IVF/ICSI treatment. This can help doctors make appropriate clinical judgments and assist patients in managing their expectations effectively.