medigraphic.com
Federación Mexicana de Ginecología y Obstetricia, A.C.

2018, Number 12

<< Back Next >>

Ginecol Obstet Mex 2018; 86 (12)

Value of the antral follicular count as a predictor of success in in vitro fertilization cycles

Sánchez-Aranda A, Campos-Cañas JA, Roque-Sánchez AM, López-Rioja MJ, Astorga-Acevedo ÁA, Recio-López Y

Language: Spanish
References: 17
Page: 769-778
PDF size: 340.83 Kb.


ABSTRACT

Background: The association between ovarian reserve test and ovarian response is well established, however, its ability to predict clinical pregnancy and the live birth is limited.
Objective: Evaluate the clinical usefulness of the antral follicle count (AFC) to predict clinical pregnancy and live newborn.
Materials and Methods: Retrospective cohort study was made. In fresh IVF cycles, performed at INPer between 2011-2016. Including patients diagnosed with infertility, who underwent in vitro fertilization with fresh embryo transfer. The study variables were age, antral follicle count, basal FSH concentration and number of oocytes captured. A binary logistic regression model was performed. Statistical Package for Social Sciences (SPSS) was used for the statistical analysis. The probability of error alpha ‹ 5% was considered significant.
Results: A total of 923 in vitro fertilization cycles were included. The antral follicle count has a prediction for clinical pregnancy (ABC 0.59) and live birth (ABC 0.57). The optimal cut-off value with the highest percentage of clinical pregnancy (9%) and live birth (10.4%) was presented with a CFA ≥ 8. A higher pregnancy rate is reported when there is a follicular count above≥≥8 follicles.
Conclusions: It is expected the highest number of clinical pregnancy and live birth when the antr al follicle count is for ≥8 follicles.


REFERENCES

  1. Jinguan J, et al. The optimum number of oocytes in IVF treatment: an analysis of 2455 cycles in China. Hum Reprod 2013; 28:2728-34. https://doi.org/10.1093/humrep/det303

  2. Lee Y, et al. Predictive value of antral follicle count and serum anti-Müllerian hormone: Which is better for live birth prediction in patients aged over 40 with their first IVF treatment? Eur J Obstet Gynecol Reprod Biol 2018;221:151- 55. https://doi.org/10.1016/j.ejogrb.2017.12.047

  3. Brodin T, et al. Comparing four ovarian reserve markersassociations with ovarian response and live births after assisted reproduction. Acta Obstet Gynecol Scand 2015; 10:1056-63. https://doi.org/10.1111/aogs.12710

  4. Broer SL, et al. Prediction of an excessive response in in vitro fertilization from patient characteristics and ovarian reserve tests and comparison in subgroups: an individual patient data meta-analysis. Fertil Steril 2013; 100:420-29. https://doi.org/10.1016/j.fertnstert.2013.04.024

  5. Lukaszuk K, et al. Use of ovarian reserve parameters for predicting live births in women undergoing in vitro fertilization. Eur J Obstet Gynecol Reprod Biol 2013; 168:173-77. https://doi.org/10.1016/j.ejogrb.2013.01.013

  6. Mutlu MF, et al. Antral follicle count determines poor ovarian response better than anti-müllerian hormone but age is the only predictor for live birth in in vitro fertilization cycles. J Assist Reprod Genet 2013; 30:657-65. https://doi. org/10.1007/s10815-013-9975-3

  7. Dhillon RK, et al. Predicting the chance of live birth for women undergoing IVF: a novel pretreatment counselling tool. Hum Reprod 2016; 31:84-92. https://doi.org/10.1093/ humrep/dev268

  8. Polat M, et al. Best Protocol for Controlled Ovarian Hyperstimulation in Assisted Reproductive Technologies: Fact or Opinion? Semin Reprod Med 2014;32:262-271. doi:10.1055/s-0034-1375178

  9. Sarais V, et al. Predicting the success of IVF: external validation of the van Loendersloot's model. Hum Reprod 2016; 31:1245-52. https://doi.org/10.1093/humrep/dew069

  10. Ferraretti AP, et al. ESHRE consensus on the definition of 'poor response' to ovarian stimulation for in vitro fertilization: The Bologna criteria. Hum Reprod 2011; 26:1616-24. https://doi.org/10.1093/humrep/der092

  11. Broekmans FJ, et al. A systematic review of tests predicting ovarian reserve and IVF outcome. Hum Reprod Update 2006; 12:685-718. https://doi.org/10.1093/humupd/ dml034

  12. Vaiarelli A, et al. What is new in the management of poor ovarian response in IVF? Curr Opin Obstet Gynecol 2018; 30:155-62. https://doi.org/10.1097/ GCO.0000000000000452

  13. Sunkara SK, et al. Association between the number of eggs and live birth in IVF treatment: an analysis of 400 135 treatment cycles. Hum Reprod 2011; 26:1768-1774. https://doi.org/10.1093/humrep/der106

  14. Kably A, et al. Análisis comparativo de la tasa de embarazoovocitos capturados en un programa de fertilización in vitro (FIV-TE). Ginecol Obstet Mex 2008; 76:256-60.

  15. López MJ, et al. Número óptimo de ovocitos: modelo de predicción para fertilización in vitro. Ginecol Obstet Mex. 2017; 85:735-47.

  16. Nardo LG, Gelbaya TA, Wilkinson H, Roberts SA, Yates A, Pemberton P et al. Circulating basal anti-Müllerian hormone levels as predictor of ovarian response in women undergoing ovarian stimulation for in vitro fertilization. Fertil Steril 2009; 92:1586-93. https://doi.org/10.1016/j. fertnstert.2008.08.127

  17. Verhagen TE, et al. The accuracy of multivariate models predicting ovarian reserve and pregnancy after in vitro fertilization: a meta-analysis. Hum Reprod Update 2008; 14:95-100. https://doi.org/10.1093/ humupd/dmn001




2020     |     www.medigraphic.com