The Development of Nomograms to Predict Blastulation Rate Following Cycles of In Vitro Fertilization in Patients With Tubal Factor Infertility, Polycystic Ovary Syndrome, or Endometriosis
It is well known that the transfer of embryos at the blastocyst stage is superior to the transfer of embryos at the cleavage stage in many respects. However, the rate of blastocyst formation remains low in clinical practice. To reduce the possibility of wasting embryos and to accurately predict the...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2021-11-01
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| Series: | Frontiers in Endocrinology |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fendo.2021.751373/full |
| _version_ | 1818738302283415552 |
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| author | Haixia Jin Xiaoxue Shen Wenyan Song Yan Liu Lin Qi Fuli Zhang |
| author_facet | Haixia Jin Xiaoxue Shen Wenyan Song Yan Liu Lin Qi Fuli Zhang |
| author_sort | Haixia Jin |
| collection | DOAJ |
| description | It is well known that the transfer of embryos at the blastocyst stage is superior to the transfer of embryos at the cleavage stage in many respects. However, the rate of blastocyst formation remains low in clinical practice. To reduce the possibility of wasting embryos and to accurately predict the possibility of blastocyst formation, we constructed a nomogram based on range of clinical characteristics to predict blastocyst formation rates in patients with different types of infertility. We divided patients into three groups based on female etiology: a tubal factor group, a polycystic ovary syndrome group, and an endometriosis group. Multiple logistic regression was used to analyze the relationship between patient characteristics and blastocyst formation. Each group of patients was divided into a training set and a validation set. The training set was used to construct the nomogram, while the validation set was used to test the performance of the model by using discrimination and calibration. The area under the curve (AUC) for the three groups indicated that the models performed fairly and that calibration was acceptable in each model. |
| first_indexed | 2024-12-18T01:06:47Z |
| format | Article |
| id | doaj.art-9817bff34ca04c959d440f5e2323e8df |
| institution | Directory Open Access Journal |
| issn | 1664-2392 |
| language | English |
| last_indexed | 2024-12-18T01:06:47Z |
| publishDate | 2021-11-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Endocrinology |
| spelling | doaj.art-9817bff34ca04c959d440f5e2323e8df2022-12-21T21:26:13ZengFrontiers Media S.A.Frontiers in Endocrinology1664-23922021-11-011210.3389/fendo.2021.751373751373The Development of Nomograms to Predict Blastulation Rate Following Cycles of In Vitro Fertilization in Patients With Tubal Factor Infertility, Polycystic Ovary Syndrome, or EndometriosisHaixia JinXiaoxue ShenWenyan SongYan LiuLin QiFuli ZhangIt is well known that the transfer of embryos at the blastocyst stage is superior to the transfer of embryos at the cleavage stage in many respects. However, the rate of blastocyst formation remains low in clinical practice. To reduce the possibility of wasting embryos and to accurately predict the possibility of blastocyst formation, we constructed a nomogram based on range of clinical characteristics to predict blastocyst formation rates in patients with different types of infertility. We divided patients into three groups based on female etiology: a tubal factor group, a polycystic ovary syndrome group, and an endometriosis group. Multiple logistic regression was used to analyze the relationship between patient characteristics and blastocyst formation. Each group of patients was divided into a training set and a validation set. The training set was used to construct the nomogram, while the validation set was used to test the performance of the model by using discrimination and calibration. The area under the curve (AUC) for the three groups indicated that the models performed fairly and that calibration was acceptable in each model.https://www.frontiersin.org/articles/10.3389/fendo.2021.751373/fullin vitro fertilizationblastocysttubal factor infertilityendometriosispolycystic ovary syndrome (PCOS)predictive models |
| spellingShingle | Haixia Jin Xiaoxue Shen Wenyan Song Yan Liu Lin Qi Fuli Zhang The Development of Nomograms to Predict Blastulation Rate Following Cycles of In Vitro Fertilization in Patients With Tubal Factor Infertility, Polycystic Ovary Syndrome, or Endometriosis Frontiers in Endocrinology in vitro fertilization blastocyst tubal factor infertility endometriosis polycystic ovary syndrome (PCOS) predictive models |
| title | The Development of Nomograms to Predict Blastulation Rate Following Cycles of In Vitro Fertilization in Patients With Tubal Factor Infertility, Polycystic Ovary Syndrome, or Endometriosis |
| title_full | The Development of Nomograms to Predict Blastulation Rate Following Cycles of In Vitro Fertilization in Patients With Tubal Factor Infertility, Polycystic Ovary Syndrome, or Endometriosis |
| title_fullStr | The Development of Nomograms to Predict Blastulation Rate Following Cycles of In Vitro Fertilization in Patients With Tubal Factor Infertility, Polycystic Ovary Syndrome, or Endometriosis |
| title_full_unstemmed | The Development of Nomograms to Predict Blastulation Rate Following Cycles of In Vitro Fertilization in Patients With Tubal Factor Infertility, Polycystic Ovary Syndrome, or Endometriosis |
| title_short | The Development of Nomograms to Predict Blastulation Rate Following Cycles of In Vitro Fertilization in Patients With Tubal Factor Infertility, Polycystic Ovary Syndrome, or Endometriosis |
| title_sort | development of nomograms to predict blastulation rate following cycles of in vitro fertilization in patients with tubal factor infertility polycystic ovary syndrome or endometriosis |
| topic | in vitro fertilization blastocyst tubal factor infertility endometriosis polycystic ovary syndrome (PCOS) predictive models |
| url | https://www.frontiersin.org/articles/10.3389/fendo.2021.751373/full |
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