Evidence map›Paper›PMID 41177891›Full record

ArticleReproductive biology and endocrinology : RB&E2025

Predicting the optimal timing for triggering in controlled ovarian stimulation: mature oocytes retrieval predictor.

Masato Kobanawa

Abstract read
In one paragraph

Article in Reproductive biology and endocrinology : RB&E, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

1 author.

Masato KobanawaKobanawa Clinic, 169-3 Tagiya, Omitama-shi, Ibarak-ken, Japan. masato.kobanawa@gmail.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe development of assisted reproductive technology (ART) has revolutionized infertility treatment; however, its success largely depends on effective controlled ovarian stimulation (COS) and the timing of oocyte retrieval. This study aimed to develop a regression equation model to optimize the timing of ovulation trigger in COS..

methodsWe retrospectively analyzed 503 COS cycles (380 with follitropin alfa, 123 with follitropin delta) as training data. We modified the Follicle-To-Oocyte Index (FOI) and developed the Follicle-To-mature Oocyte Index (FmOI), which indicates how many mature oocytes (MII) were obtained for each antral follicle count. This index was used as an indicator for the retrieval of mature oocytes. When using FmOI as the objective variable, we selected relevant factors through Lasso regression analysis. Based on the obtained regression equations, the accuracy was compared and verified by predicting the number of MII in the test data.

resultsLasso regression analysis resulted in the creation of an FmOI prediction model using Initial serum FSH, number of follicles ≥ 14 mm, and total gonadotropin dose as explanatory variables. The regression equation model achieved Median Absolute Error values of 1.90 and 1.80 MII counts in the test data for the Alfa and Delta groups, respectively. Concordance index for MII prediction were 0.98 for follitropin alfa and 0.87 for follitropin delta. Use of the model showed higher CLBR in Alfa and non-inferiority in Delta than control group.

conclusionThis model reliably predicts the number of MII and optimizes trigger timing in COS. By considering key predictors, it provides a precise tool to enhance clinical outcomes in assistedreproductive technology .

Indexed as

Oocyte RetrievalOocytesOvulation InductionFemaleFollicle Stimulating Hormone, HumanHumansOvarian FollicleRecombinant ProteinsRetrospective StudiesTime FactorsFollicle Stimulating Hormone, Humanfollitropin alfafollitropin deltaRecombinant ProteinsAssisted reproductive technologyControlled ovarian stimulationFollicle-stimulating hormoneMature oocytesOocyte retrieval timing

Identifiers

PMID41177891
PMCPMC12581242

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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.