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Anti-Mullerian hormone (AMH) is one of the direct indicators of follicular pool but no standard cutoff has been defined for diagnosis of polycystic ovary syndrome (PCOS). The present study evaluated the serum AMH levels among different PCOS phenotypes and correlated the AMH levels with clinical, hormonal, and metabolic parameters among Indian PCOS women. Mean serum AMH was 12.39 ± 5.3ng/mL in PCOS cohort and 3.83 ± 1.5 ng/mL in non-PCOS cohort (P < 0.01). Out of 608 PCOS women, 273 (44.9%) women belonged to phenotype A, 230 (37.8%) women were phenotype D. Phenotypes C and B were 12.17% and 5.10% respectively. Among those with the highest AMH group (AMH>20ng/ml; 8.05%), majority belonged to phenotype A. Menstrual cycle length, serum testosterone, fasting total cholesterol levels, and follicle number per ovary had positive correlation with serum anti-Mullerian levels (P < 0.05). AMH cutoff for the diagnosis of PCOS was calculated as ≥ 6.06 ng/mL on ROC analysis with sensitivity and specificity of 91.45% and 90.71% respectively. The study shows high serum AMH levels in PCOS are associated with worse clinical, endocrinological, and metabolic parameters. These levels may be used to counsel patients regarding treatment response, help in individualized management and prediction of reproductive and long-term metabolic outcomes.
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http://dx.doi.org/10.1007/s43032-023-01195-y | DOI Listing |
Background And Aims: The role of anti-Müllerian hormone (AMH), a potential marker of the hypothalamic-pituitary-ovarian axis, is not well established in adolescent females. Typical epidemiologic studies use secondary sexual characteristics or chronological age as predictors for AMH. Skeletal maturity, an indicator of bone development, however, has not been examined in association with AMH in adolescent females.
View Article and Find Full Text PDFEpilepsy Behav
September 2025
The Epilepsy Clinic, Department of Neurology, Copenhagen University Hospital - Rigshospitalet, Copenhagen, Denmark.
Objective: The objective of this study was to examine ovarian reserve parameters in women with epilepsy compared to women without epilepsy.
Methods: A total of 80 women with epilepsy (WWE) from the epilepsy clinic at Rigshospitalet, Denmark, participated and completed the study between 2018-2022. A historical cohort collected from 2008 to 2010 of 418 women without epilepsy and no prior diagnosis of infertility was used as control.
Study Question: Can patient age and ovarian reserve tests predict the number of cryopreserved oocytes in patients undergoing one or more ovarian stimulation cycles for elective oocyte cryopreservation (EOC)?
Summary Answer: A predictive model incorporating patient age, antral follicle count (AFC), anti-Müllerian hormone (AMH), and FSH levels achieved the greatest predictive accuracy.
What Is Known Already: As a consequence of societal evolution, women are increasingly delaying starting a family. However, the natural decline in ovarian reserve and oocyte quality as age advances can increase the risk of age-related fertility decline (ARFD) and involuntary childlessness.
J Assist Reprod Genet
September 2025
Department of Reproductive Medicine, General Hospital of Northern Theater Command, No. 83, Wenhua Road, Shenhe District, Shenyang, 110016, China.
Objective: The association between anti-Müllerian hormone (AMH) levels and embryonic aneuploidy rates was investigated by analyzing clinical and embryo laboratory data from patients with preimplantation genetic testing for aneuploidy (PGT-A). However, the nonlinear relationship and threshold effect of AMH on aneuploidy risk remain poorly understood.
Methods: This retrospective study analyzed the clinical data of 819 PGT-A cycles performed between January 2018 and August 2024 at the General Hospital of Northern Theater Command.
Comput Struct Biotechnol J
August 2025
Department of Obstetrics, Gynecology and Reproductive Medicine, Foch Hospital, Suresnes, France.
Background: The dynamic interplay of ovarian hormones is central to reproductive physiology, yet the complexity of their cyclic variations poses challenges for analysis, simulation, and teaching. This study presents a framework for generating physiologically constrained, multi-hormone synthetic time series that capture intra- and inter-individual variability across phenotypes.
Methods: We developed a semi-mechanistic mathematical framework to generate synthetic multi-hormone profiles (estradiol, FSH, LH, AMH, testosterone, GnRH) using parametric equations embedding known physiological feedbacks (e.