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Janne Meije van Weert

Researcher at University of Amsterdam

Publications -  6
Citations -  290

Janne Meije van Weert is an academic researcher from University of Amsterdam. The author has contributed to research in topics: Pregnancy rate & Pregnancy. The author has an hindex of 6, co-authored 6 publications receiving 275 citations.

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Performance of the postwash total motile sperm count as a predictor of pregnancy at the time of intrauterine insemination: a meta-analysis.

TL;DR: The postwash TMC at insemination could potentially be used in counseling patients for either IUI or IVF, however, to enable patient counseling before the start of treatment, further studies are needed to establish the accuracy of a postwashing TMC during the fertility workup rather than at inSEmination.
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Use of the total motile sperm count to predict total fertilization failure in in vitro fertilization

TL;DR: The use of both models, one before start of the IVF cycle and one at the time of OPU, allows an accurate prediction of the chance of TFF and is useful in counseling patients on whether to opt for IVF or ICSI.
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The INeS study: prevention of multiple pregnancies: a randomised controlled trial comparing IUI COH versus IVF e SET versus MNC IVF in couples with unexplained or mild male subfertility

TL;DR: Whether alternative treatments such as IVF elective Single Embryo Transfer (IVF e SET) or Modified Natural Cycle IVF (MNC IVF) can reduce the number of multiple pregnancy rates, but uphold similar pregnancy rates as IUI COH in couples with mild male or unexplained subfertility is revealed.
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Patients' preferences for intrauterine insemination or in-vitro fertilization

TL;DR: The majority of couples undergoing IUI preferred continuation of IUI over IVF, and a clear shift in preference towards IVF occurred after six cycles, with decreasing probability of ongoing pregnancy after IUI.
Journal Article

A prediction model for ongoing pregnancy after in vitro fertilization in couples with male subfertility.

TL;DR: In couples with male subfertility, the use of a prediction model including ASA improves the efficiency of IVF.