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Nomogram to predict the number of oocytes retrieved in controlled ovarian stimulation

OBJECTIVE: Ovarian reserve tests are commonly used to predict ovarian response in infertile patients undergoing ovarian stimulation. Although serum markers such as basal follicle-stimulating hormone (FSH) or random anti-Müllerian hormone (AMH) level and ultrasonographic markers (antral follicle coun...

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Autores principales: Moon, Kyoung Yong, Kim, Hoon, Lee, Joong Yeup, Lee, Jung Ryeol, Jee, Byung Chul, Suh, Chang Suk, Kim, Ki Chul, Lee, Won Don, Lim, Jin Ho, Kim, Seok Hyun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Korean Society for Reproductive Medicine 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4925866/
https://www.ncbi.nlm.nih.gov/pubmed/27358830
http://dx.doi.org/10.5653/cerm.2016.43.2.112
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author Moon, Kyoung Yong
Kim, Hoon
Lee, Joong Yeup
Lee, Jung Ryeol
Jee, Byung Chul
Suh, Chang Suk
Kim, Ki Chul
Lee, Won Don
Lim, Jin Ho
Kim, Seok Hyun
author_facet Moon, Kyoung Yong
Kim, Hoon
Lee, Joong Yeup
Lee, Jung Ryeol
Jee, Byung Chul
Suh, Chang Suk
Kim, Ki Chul
Lee, Won Don
Lim, Jin Ho
Kim, Seok Hyun
author_sort Moon, Kyoung Yong
collection PubMed
description OBJECTIVE: Ovarian reserve tests are commonly used to predict ovarian response in infertile patients undergoing ovarian stimulation. Although serum markers such as basal follicle-stimulating hormone (FSH) or random anti-Müllerian hormone (AMH) level and ultrasonographic markers (antral follicle count, AFC) are good predictors, no single test has proven to be the best predictor. In this study, we developed appropriate equations and novel nomograms to predict the number of oocytes that will be retrieved using patients' age, serum levels of basal FSH and AMH, and AFC. METHODS: We analyzed a database containing clinical and laboratory information of 141 stimulated in vitro fertilization (IVF) cycles performed at a university-based hospital between September 2009 and December 2013. We used generalized linear models for prediction of the number of oocytes. RESULTS: Age, basal serum FSH level, serum AMH level, and AFC were significantly related to the number of oocytes retrieved according to the univariate and multivariate analyses. The equations that predicted the number of oocytes retrieved (log scale) were as follows: model (1) 3.21–0.036×(age)+0.089×(AMH), model (2) 3.422–0.03×(age)–0.049×(FSH)+0.08×(AMH), model (3) 2.32–0.017×(age)+0.039×(AMH)+0. 03×(AFC), model (4) 2.584–0.015×(age)–0.035×(FSH)+0.038×(AMH)+0.026×(AFC). model 4 showed the best performance. On the basis of these variables, we developed nomograms to predict the number of oocytes that can be retrieved. CONCLUSION: Our nomograms helped predict the number of oocytes retrieved in stimulated IVF cycles.
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spelling pubmed-49258662016-06-29 Nomogram to predict the number of oocytes retrieved in controlled ovarian stimulation Moon, Kyoung Yong Kim, Hoon Lee, Joong Yeup Lee, Jung Ryeol Jee, Byung Chul Suh, Chang Suk Kim, Ki Chul Lee, Won Don Lim, Jin Ho Kim, Seok Hyun Clin Exp Reprod Med Original Article OBJECTIVE: Ovarian reserve tests are commonly used to predict ovarian response in infertile patients undergoing ovarian stimulation. Although serum markers such as basal follicle-stimulating hormone (FSH) or random anti-Müllerian hormone (AMH) level and ultrasonographic markers (antral follicle count, AFC) are good predictors, no single test has proven to be the best predictor. In this study, we developed appropriate equations and novel nomograms to predict the number of oocytes that will be retrieved using patients' age, serum levels of basal FSH and AMH, and AFC. METHODS: We analyzed a database containing clinical and laboratory information of 141 stimulated in vitro fertilization (IVF) cycles performed at a university-based hospital between September 2009 and December 2013. We used generalized linear models for prediction of the number of oocytes. RESULTS: Age, basal serum FSH level, serum AMH level, and AFC were significantly related to the number of oocytes retrieved according to the univariate and multivariate analyses. The equations that predicted the number of oocytes retrieved (log scale) were as follows: model (1) 3.21–0.036×(age)+0.089×(AMH), model (2) 3.422–0.03×(age)–0.049×(FSH)+0.08×(AMH), model (3) 2.32–0.017×(age)+0.039×(AMH)+0. 03×(AFC), model (4) 2.584–0.015×(age)–0.035×(FSH)+0.038×(AMH)+0.026×(AFC). model 4 showed the best performance. On the basis of these variables, we developed nomograms to predict the number of oocytes that can be retrieved. CONCLUSION: Our nomograms helped predict the number of oocytes retrieved in stimulated IVF cycles. The Korean Society for Reproductive Medicine 2016-06 2016-06-23 /pmc/articles/PMC4925866/ /pubmed/27358830 http://dx.doi.org/10.5653/cerm.2016.43.2.112 Text en Copyright © 2016. The Korean Society for Reproductive Medicine http://creativecommons.org/licenses/by-nc/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Original Article
Moon, Kyoung Yong
Kim, Hoon
Lee, Joong Yeup
Lee, Jung Ryeol
Jee, Byung Chul
Suh, Chang Suk
Kim, Ki Chul
Lee, Won Don
Lim, Jin Ho
Kim, Seok Hyun
Nomogram to predict the number of oocytes retrieved in controlled ovarian stimulation
title Nomogram to predict the number of oocytes retrieved in controlled ovarian stimulation
title_full Nomogram to predict the number of oocytes retrieved in controlled ovarian stimulation
title_fullStr Nomogram to predict the number of oocytes retrieved in controlled ovarian stimulation
title_full_unstemmed Nomogram to predict the number of oocytes retrieved in controlled ovarian stimulation
title_short Nomogram to predict the number of oocytes retrieved in controlled ovarian stimulation
title_sort nomogram to predict the number of oocytes retrieved in controlled ovarian stimulation
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4925866/
https://www.ncbi.nlm.nih.gov/pubmed/27358830
http://dx.doi.org/10.5653/cerm.2016.43.2.112
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