Predictors of success after in vitro fertilization

Laxmi Shingshetty; Natalie Cameron; David McLernon; Siladitya Bhattacharya

doi:10.1016/j.fertnstert.2024.03.003

Predictors of success after in vitro fertilization

Laxmi Shingshetty^* (Corresponding Author), Natalie Cameron^* (Corresponding Author), David McLernon^* (Corresponding Author), Siladitya Bhattacharya^* (Corresponding Author)

^*Corresponding author for this work

Research output: Contribution to journal › Review article › peer-review

1 Citation (Scopus)

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Abstract

The last few decades have witnessed a rise in the global uptake of in vitro fertilization (IVF) treatment. To ensure optimal use of this technology, it is important for patients and clinicians to have access to tools that can provide accurate estimates of treatment success and understand the contribution of key clinical and laboratory parameters that influence the chance of conception after IVF treatment. The focus of this review was to identify key predictors of IVF treatment success and assess their impact in terms of live birth rates. We have identified 11 predictors that consistently feature in currently available prediction models, including age, duration of infertility, ethnicity, body mass index, antral follicle count, previous pregnancy history, cause of infertility, sperm parameters, number of oocytes collected, morphology of transferred embryos, and day of embryo transfer.

Original language	English
Pages (from-to)	742-751
Number of pages	10
Journal	Fertility and Sterility
Volume	121
Issue number	5
Early online date	16 Mar 2024
DOIs	https://doi.org/10.1016/j.fertnstert.2024.03.003
Publication status	Published - May 2024

Bibliographical note

Open access via Elsevier agreement

Data Availability Statement

No new data have been generated or analysed in support of this publication.

Keywords

Prediction Models
Invitro Fertilisation(IVF)
Intra-Cytoplasmic Sperm injection(ICSI)
Predictors
live birth
predictors
intracytoplasmic sperm injection (ICSI)
Prediction models
in vitro fertilization (IVF)
Predictive Value of Tests
Humans
Live Birth
Embryo Transfer/methods
Risk Factors
Fertilization in Vitro/methods
Infertility/therapy
Treatment Outcome
Male
Pregnancy
Female
Pregnancy Rate

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10.1016/j.fertnstert.2024.03.003Licence: CC BY

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This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
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Cite this

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title = "Predictors of success after in vitro fertilization",

abstract = "The last few decades have witnessed a rise in the global uptake of in vitro fertilization (IVF) treatment. To ensure optimal use of this technology, it is important for patients and clinicians to have access to tools that can provide accurate estimates of treatment success and understand the contribution of key clinical and laboratory parameters that influence the chance of conception after IVF treatment. The focus of this review was to identify key predictors of IVF treatment success and assess their impact in terms of live birth rates. We have identified 11 predictors that consistently feature in currently available prediction models, including age, duration of infertility, ethnicity, body mass index, antral follicle count, previous pregnancy history, cause of infertility, sperm parameters, number of oocytes collected, morphology of transferred embryos, and day of embryo transfer.",

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author = "Laxmi Shingshetty and Natalie Cameron and David McLernon and Siladitya Bhattacharya",

note = "Open access via Elsevier agreement ",

year = "2024",

month = may,

doi = "10.1016/j.fertnstert.2024.03.003",

language = "English",

volume = "121",

pages = "742--751",

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AU - Cameron, Natalie

AU - McLernon, David

AU - Bhattacharya, Siladitya

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PY - 2024/5

Y1 - 2024/5

N2 - The last few decades have witnessed a rise in the global uptake of in vitro fertilization (IVF) treatment. To ensure optimal use of this technology, it is important for patients and clinicians to have access to tools that can provide accurate estimates of treatment success and understand the contribution of key clinical and laboratory parameters that influence the chance of conception after IVF treatment. The focus of this review was to identify key predictors of IVF treatment success and assess their impact in terms of live birth rates. We have identified 11 predictors that consistently feature in currently available prediction models, including age, duration of infertility, ethnicity, body mass index, antral follicle count, previous pregnancy history, cause of infertility, sperm parameters, number of oocytes collected, morphology of transferred embryos, and day of embryo transfer.

AB - The last few decades have witnessed a rise in the global uptake of in vitro fertilization (IVF) treatment. To ensure optimal use of this technology, it is important for patients and clinicians to have access to tools that can provide accurate estimates of treatment success and understand the contribution of key clinical and laboratory parameters that influence the chance of conception after IVF treatment. The focus of this review was to identify key predictors of IVF treatment success and assess their impact in terms of live birth rates. We have identified 11 predictors that consistently feature in currently available prediction models, including age, duration of infertility, ethnicity, body mass index, antral follicle count, previous pregnancy history, cause of infertility, sperm parameters, number of oocytes collected, morphology of transferred embryos, and day of embryo transfer.

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KW - Intra-Cytoplasmic Sperm injection(ICSI)

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KW - Prediction models

KW - in vitro fertilization (IVF)

KW - Predictive Value of Tests

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KW - Live Birth

KW - Embryo Transfer/methods

KW - Risk Factors

KW - Fertilization in Vitro/methods

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JO - Fertility and Sterility

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ER -

Predictors of success after in vitro fertilization

Abstract

Bibliographical note

Data Availability Statement

Keywords

Access to Document

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Cite this