A prediction model to select PCOS patients suitable for IVM treatment based on anti-Müllerian hormone and antral follicle count

plexes (COC) yield were performed to assess the efficiency of the prediction model to select suitable candidates for IVM. main results and the role of chance: Using multivariate regression analysis, circulating baseline AMH, AFC and baseline total testosterone serum concentration were incorporated into a model to predict the number of COC retrieved in an IVM cycle, with unstandardized coefficients [95% confidence interval (CI)] of 0.03 (0.02–0.03) (P , 0.001), 0.012 (0.008–0.017) (P , 0.001) and 0.37 (0.18– 0.57) (P , 0.001), respectively. Logistic regression analysis shows that a prediction model based on AMH and AFC, with unstandardized coefficients (95% CI) of 0.148 (0.03–0.25) (P , 0.001) and 0.034 (20.003–0.07) (P ¼ 0.025), respectively, is a useful patient selection tool to predict the probability to yield at least eight COCs for IVM in patients with PCOS. In this population, patients with at least eight COC available for IVM have a statistically higher number of embryos of good morphological quality (2.9+ 2.3; 0.9+ 0.9; P , 0.001) and cumulative ongoing pregnancy rate [30.4% (24 out of 79); 11% (5 out of 45); P ¼ 0.01] when compared with patients with less than eight COC. ROC curve analysis showed that this prediction model has an area under the curve of 0.7864 (95% CI ¼ 0.6997 –0.8732) for the prediction of oocyte yield in IVM.