The combined use of antimullerian hormone and age to predict the ovarian response to controlled ovarian hyperstimulation in poor responders: A novel approach

• Autore principale: Yadava Bapurao Jeve (Autore)
• Natura: Libro
• Pubblicazione: Wolters Kluwer Medknow Publications, 2013-01-01T00:00:00Z.
• Soggetti: article
• Accesso online: Connect to this object online.
• Notes: 0974-1208; 1998-4766; 10.4103/0974-1208.126298
• Keywords: Ovarian hyperstimulation; poor responders; serum antimullerian hormone; Gynecology and obstetrics; RG1-991
• Source: Journal of Human Reproductive Sciences, Vol 6, Iss 4, Pp 259-262 (2013)

Context: Reduced ovarian response to stimulation represents one of the most intractable problems in infertility treatment. As failed cycle can cause considerable amount of emotional and economical loss, there are various attempts made to predict ovarian response. Aims: To evaluate different factors influencing outcome of assisted reproduction in women with predicted reduced response (antimullerian hormone between 1 and 5 pmol/L) and to develop a model using of AMH and age to predict the number of oocytes in poor responders. Settings and Design: Retrospective study in a teaching hospital. Materials and Methods: We analyzed 85 cycles (57 women) with predicted reduced response with serum AMH value between 1 and 5 pmol/L. Standard ovarian stimulation protocol was used. Primary outcome measures were clinical pregnancy rates and oocytes retrieved. Statistical Analysis Used: Data were analyzed using Microsoft excel and MetlabR software. Results: Clinical pregnancy rate/ET was 20.33%, in this group. AMH and age was analyzed using linear regression model which produced an equation to give predicted oocyte count if AMH and age are known. (Oocytes = age × (-ß) + Serum AMH × α) (Constant ß=0.0102 and α = 1.0407). Conclusions: Combined use of serum AMH and age to predict ovarian response within reduced responder group should be further evaluated. For first time, we suggested combining both factors to predict ovarian response using a simple equation which allow developing tailored strategy.