Evidence map›Paper›PMID 38573535›Full record

ArticleJournal of assisted reproduction and genetics2024

Exploring gonadotropin dosing effects on MII oocyte retrieval in ovarian stimulation.

Krystian Zieliński, Anna Kloska, Piotr Wygocki, Marcin Zieleń, Michał Kunicki

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In one paragraph

Article in Journal of assisted reproduction and genetics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

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0cells of the map it votes in
4citing papers in PubMed
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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Krystian ZielińskiINVICTA Research and Development Center, Sopot, Poland.
Anna KloskaINVICTA Research and Development Center, Sopot, Poland. anna.kloska@ug.edu.pl.ORCID http://orcid.org/0000-0002-5168-0232
Piotr WygockiMIM Solutions, Warsaw, Poland.
Marcin ZieleńMIM Solutions, Warsaw, Poland.
Michał KunickiINVICTA Research and Development Center, Sopot, Poland.

Funding

European Regional Development Fund under the Pomorskie Voivodeship Regional Operational Programmee for 2014-2020 RPPM.01.01.01-22-0060/17
6 · The paper itself

Abstract

purposeOvarian stimulation with gonadotropins is crucial for obtaining mature oocytes for in vitro fertilization (IVF). Determining the optimal gonadotropin dosage is essential for maximizing its effectiveness. Our study aimed to develop a machine learning (ML) model to predict oocyte counts in IVF patients and retrospectively analyze whether higher gonadotropin doses improve ovarian stimulation outcomes.

methodsWe analyzed the data from 9598 ovarian stimulations. An ML model was employed to predict the number of mature metaphase II (MII) oocytes based on clinical parameters. These predictions were compared with the actual counts of retrieved MII oocytes at different gonadotropin dosages.

resultsThe ML model provided precise predictions of MII counts, with the AMH and AFC being the most important, and the previous stimulation outcome and age, the less important features for the prediction. Our findings revealed that increasing gonadotropin dosage did not result in a higher number of retrieved MII oocytes. Specifically, for patients predicted to produce 4-8 MII oocytes, a decline in oocyte count was observed as gonadotropin dosage increased. Patients with low (1-3) and high (9-12) MII predictions achieved the best results when administered a daily dose of 225 IU; lower and higher doses proved to be less effective.

conclusionsOur study suggests that high gonadotropin doses do not enhance MII oocyte retrieval. Our ML model can offer clinicians a novel tool for the precise prediction of MII to guide gonadotropin dosing.

Indexed as

Fertilization in VitroGonadotropinsOocyte RetrievalOocytesOvulation InductionAdultFemaleHumansMetaphasePregnancyPregnancy RateRetrospective StudiesGonadotropinsGonadotropin dosageIVFMachine learning modelMII oocytesOvarian stimulation

Identifiers

PMID38573535
PMCPMC11224171

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.