The ovarian response prediction index (ORPI) as a clinical internal quality control to prevent ovarian hyperstimualtion syndrome

Predicting the ovarian response: towards a determinant model and implications for practice

OBJECTIVE

To improve the reliability of prediction models for ovarian response to stimulation in ART.

DESIGN

A multicenter retrospective cohort study.

SETTING

Twelve reproductive centers.

PATIENTS

A total of 25,854 controlled ovarian stimulations between 2005 and 2016, including cycles cancelled for inadequate response, were included.

INTERVENTION(S)

None.

MAIN OUTCOME MEASURE(S)

Precision of the prediction of the number of oocytes at ovarian pickup and of cancellation rate for poor ovarian response.

RESULTS

Both AMH and antral follicle count exhibit a non-linear effect on the oocyte yield, with a linear relationship after log-transformation. After adjustment for age, BMI, and center, ovarian response observed in a previous stimulation was found to be the best predictor, followed by AMH and AFC. The zero-inflated binomial negative model showed that predictors of cycle cancellation and number of oocytes at retrieval were different, and assimilating cancellation to zero oocyte greatly reduces the determination of the model. Our model was characterized by the best ever reached determination (R2=0.505 for non-naïve women, 0.313 for all the women) and provided evidence of a very strong difference among centers. The results can be easily converted in the prediction of response levels (poor-medium-good-high). Finally, in case of partial report of the above predictors, we show that the univariate prediction based on the best predictor provides a good approximation.

CONCLUSION(S)

A substantial improvement of the ovarian response prediction is possible in modelling the possible cancellation decision, followed by the oocyte retrieval itself, according to an appropriate model based on previous stimulation and non-linear effects of AMH and AFC.

Evaluative effectiveness of follicular output rate, ovarian sensitivity index, and ovarian response prediction index for the ovarian reserve and response of low-prognosis patients according to the POSEIDON criteria: a retrospective study

The aim was to explore the implications of follicular output rate (FORT), ovarian sensitivity index (OSI), ovarian response prediction index (ORPI), and follicle-to-oocyte index (FOI) in low-prognosis patients defined by POSEIDON criteria. In total, 4030 fresh in vitro fertilization (IVF) cycles from January 2013 to October 2021 were included in this retrospective cohort analysis and were categorized into four groups based on the POSEIDON criteria. The FORT between Groups 1 and 2 (0.61 ± 0.34 vs. 0.65 ± 0.35, P = 0.081) and Groups 3 and 4 (1.08 ± 0.82 vs. 1.09 ± 0.94, P = 0.899) were similar. The OSI in the order from the highest to the lowest were 3.01 ± 1.46 in Group 1, 2.28 ± 1.09 in Group 2, 1.54 ± 1.04 in Group 3, and 1.34 ± 0.96 in Group 4 (P < 0.001). The trend in the ORPI values was consistent with that in the OSI. FORT, OSI, ORPI, and FOI complemented each other and offered excellent effectiveness in reflecting ovarian reserve and response, but they were not good predictors of clinical pregnancy rate (CPR) from IVF.

The comparison of evaluative effectiveness between antral follicle count/age ratio and ovarian response prediction index for the ovarian reserve and response functions in infertile women

Aim of the present study was to explore the evaluative effectiveness of age, ovarian volume (OV), antral follicle count (AFC), serum follicle-stimulating hormone (FSH), anti-Müllerian hormone (AMH), AFC/Age ratio, AMH/Age ratio, FSH/luteinizing hormone (LH) ratio, and ovarian response prediction index (ORPI) to determine which could more advantageously assess ovarian reserve and response.This research enrolled 319 consecutive infertile women who had undergone in vitro fertilization-ET/intracytoplasmic sperm injection (IVF-ET/ICSI) treatments. Abovementioned variables were measured and calculated. Receiver operating characteristic (ROC) curve analysis was used to analyze the predictive accuracy of variables and to calculate cut-off values and corresponding sensitivity and specificity.Our study revealed that the significant variables for evaluating a decline in ovarian reserve include age, OV, FSH, AFC/Age ratio, AMH/Age ratio, and ORPI. Moreover, the area under the curve (AUC) of AFC/Age ratio was higher than other 5 variables (AUC = 1.000), and the cut-off value of AFC/Age ratio was 0.111 (sensitivity 100.00%, specificity 100.00%). The significant variables forecasting excessive ovarian response were age, AFC, AMH, FSH, AFC/Age ratio, AMH/Age ratio, FSH/LH ratio, and ORPI, and the significant variables forecasting poor ovarian response were AMH, LH, OV, AFC/Age ratio, AMH/Age ratio, and FSH/LH ratio. When ORPI was used to predict excessive response, the cut-off value of ORPI was 0.880 (sensitivity 84.72%, specificity 67.32%) and ORPI presented better effectiveness. When used to predict poor response, the evaluative effectiveness of 6 variables was almost similar, although the AUC of AFC/Age ratio presented the largest value.Regarding the infertile women, AFC/Age ratio performed better than did the other variables in evaluating ovarian reserve, and it offered excellent effectiveness in predicting poor ovarian response, however, ORPI presented better effectiveness in predicting excessive ovarian response.

Clinical Application of AMH Measurement in Assisted Reproduction

Anti-Müllerian hormone reflects the continuum of the functional ovarian reserve, and as such can predict ovarian response to gonadotropin stimulation and be used to individualize treatment pathways to improve efficacy and safety. However, consistent with other biomarkers and age-based prediction models it has limited ability to predict live birth and should not be used to refuse treatment, but rather to inform counselling and shared decision making. The use of absolute clinical thresholds to stratify patient phenotypes, assess discordance and individualize treatment protocols in non-validated algorithms combined with the lack of standardization of assays may result in inappropriate classification and sub-optimal clinical decision making. We propose that holistic baseline phenotyping, incorporating antral follicle count and other patient characteristics is critical. Treatment decisions driven by validated algorithms that use ovarian reserve biomarkers as continuous measures, reducing the risk of misclassification, are likely to improve overall outcomes for our patients.

Randomized comparison of two commercial culture media (Cook and Vitrolife) for embryo culture after IMSI

OBJECTIVE

A variety of studies randomizing women/cycles or oocytes/embryos has been carried out to compare different culture media for culturing embryos up to cleavage or blastocyst stages showing controversial results. A recent systematic review suggested that data in the literature are insufficient to conclude the best culture medium for embryo quality, pregnancy and implantation. The objective of this study was to evaluate whether there is any difference between two commercial culture media regarding clinical outcomes after IMSI cycles.

METHODS

A total of 120 patients, ≤39 years of age, undergoing ART treatment submitted to the IMSI program were prospectively broken down and randomized into two groups: Group I (Cook media) and Group II (Vitrolife media).

RESULTS

Our data demonstrated that there was no difference using all the media from Cook or all the media from Vitrolife, for culturing embryos till day 2, in the bench incubator at low O2 concentration, in relation to fertilization, embryo quality, pregnancy and implantation rates (p>0.05).

CONCLUSION

Both culture media used, Cook medium and Vitrolife medium, for the IMSI procedure and for later embryo culture with transfer on the second day, are equally effective and can be used depending on the ease and availability of acquisition.