Correlation between biochemical, ultrasonographic and demographic parameters with ovarian response to IVF/ICSI treatments in Mexican women
| Autor: | José Modesto Alfredo Góngora Rodríguez, Alfredo Cortes Vázquez, Alfredo Cortes Algara, Jesús Daniel Moreno García |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
Oncology
medicine.medical_specialty endocrine system mexican Pregnancy Rate Ovarian hyperstimulation syndrome Fertilization in Vitro Hormone antagonist Spearman's rank correlation coefficient Correlation Gonadotropin-Releasing Hormone 03 medical and health sciences Ovarian Hyperstimulation Syndrome 0302 clinical medicine Ovulation Induction Pregnancy Internal medicine Linear regression Medicine ovarian Humans 030212 general & internal medicine Sperm Injections Intracytoplasmic Ovarian reserve Retrospective Studies parameters 030219 obstetrics & reproductive medicine response business.industry prediction Ivf icsi medicine.disease female genital diseases and pregnancy complications IVF Original Article Female business Hormone |
| Zdroj: | JBRA Assisted Reproduction |
| ISSN: | 1518-0557 1517-5693 |
| Popis: | Objective Ovarian response from a conventional ovarian stimulation protocol is a crucial step in IVF/ICSI treatments. This ovarian response encompasses a wide range of outcomes at the extremes, leading to either excessive responses with the risk of life-threatening conditions like ovarian hyperstimulation syndrome (OHSS), or poor ovarian response (POR) with poor outcomes. This study aims to integrate biochemical, ultrasonographic and demographic parameters into a mathematical formula able to predict ovarian response to stimulation in IVF/ICSI in gonadotropin-releasing hormone (GnRH) antagonist protocols. Methods This retrospective analysis included 147 patients submitted to an ovarian stimulation protocol combining recombinant FSH and gonadotropin-releasing hormone antagonist. All the parameters were correlated with the Spearman Rho and Pearson´s correlation coefficient. Once the data was normalized, we used the multiple linear regression models, checking the results with the progressive discriminating analysis. Results We classified the database according to the correlation with the number of oocytes retrieved; the progressive discriminating analysis resulted in the following equation: oocytes retrieved = 2.312-0.130 (FSH) + 0.562 (AFC). Conclusions The incorporation of 2 ovarian reserve parameters into a regression equation enables knowing the number of retrieved oocytes in each patient with 80.5% sensitivity and 55.4% specificity. |
| Databáze: | OpenAIRE |
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