ArticleClinical and experimental reproductive medicine2022
Correlation of oocyte number with serum anti-Müllerian hormone levels measured by either Access or Elecsys in fresh in vitro fertilization cycles.
Article in Clinical and experimental reproductive medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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3 citing papers in PubMed, 4 citations in OpenAlex.
- An explainable machine learning model for identifying the risk of suboptimal oocyte maturation in patients with polycystic ovary syndrome undergoing GnRH-antagonist protocol.Journal of ovarian research · 2026Article
- Fibroblast Activation Protein (FAP) as a Serum Biomarker for Fibrotic Ovarian Aging: A Clinical Validation Study Based on Translational Transcriptomic Targets.International journal of molecular sciences · 2025Article
- Investigation of the Prevalence of Diminished Ovarian Reserve in Korean Women of Reproductive Age.Journal of clinical medicine · 2023Article
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Authors and funding
4 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveThe aim of this study was to assess the correlation of oocyte number with serum anti-Müllerian hormone (AMH) levels measured by two automated methods (Access or Elecsys) in fresh stimulated in vitro fertilization (IVF) cycles.
methodsIn this retrospective study at a university hospital, data were collected from 243 fresh stimulated IVF cycles performed from August 2016 to December 2020. The serum AMH level was measured by Access in 120 cycles and by Elecsys in 123 cycles. The cut-off of serum AMH for prediction of poor responders (three or fewer oocytes) or high responders (15 or more oocytes) was calculated by the receiver operating characteristic curve analysis.
resultsFor the two automated methods, the following equations were derived: total oocyte number=2.378+1.418×(Access-AMH) (r=0.645, p<0.001) and total oocyte number=2.417+2.163×(Elecsys-AMH) (r=0.686, p<0.001). The following combined equation could be derived: (Access-AMH)=0.028+1.525×(Elecsys-AMH). To predict poor responders, the cut-off of Access-AMH was 1.215 ng/mL (area under the curve [AUC], 0.807; 95% confidence interval [CI], 0.730-0.884; p<0.001), and the cut-off of Elecsys-AMH was 1.095 ng/mL (AUC, 0.848; 95% CI, 0.773-0.923; p<0.001). To predict high responders, the cut-off of Access-AMH was 3.450 ng/mL (AUC, 0.922; 95% CI, 0.862-0.981; p<0.001), and the cut-off of Elecsys-AMH was 2.500 ng/mL (AUC, 0.884; 95% CI, 0.778-0.991; p<0.001).
conclusionBoth automated methods for serum AMH measurement showed a good correlation with oocyte number and good performance for predicting poor and high responders in fresh stimulated IVF cycles. The Access method usually yielded higher measured serum AMH levels than the Elecsys method.
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