IN-VITRO ACTIVATION OF OVARIAN FOLLICULAR RESIDUAL RESERVE

The newly developed in-vitro activation (IVA) method provides a novel fertility treatment for patients with premature ovarian insufficiency. The IVA method pretends to promote growth of residual ovarian follicles at early stages of their development. Based on preliminary data, poor ovarian response (POR) patients with decreased ovarian reserve (DOR) who have multiple secondary follicles, IVA is a promising technique to promote growth of secondary follicle as well.

Prediction of sperm extraction in non-obstructive azoospermia patients: a machine-learning perspective

STUDY QUESTION

Can a machine-learning-based model trained in clinical and biological variables support the prediction of the presence or absence of sperm in testicular biopsy in non-obstructive azoospermia (NOA) patients?

SUMMARY ANSWER

Our machine-learning model was able to accurately predict (AUC of 0.8) the presence or absence of spermatozoa in patients with NOA.

WHAT IS KNOWN ALREADY

Patients with NOA can conceive with their own biological gametes using ICSI in combination with successful testicular sperm extraction (TESE). Testicular sperm retrieval is successful in up to 50% of men with NOA. However, to the best of our knowledge, there is no existing model that can accurately predict the success of sperm retrieval in TESE. Moreover, machine-learning has never been used for this purpose.

STUDY DESIGN, SIZE, DURATION

A retrospective cohort study of 119 patients who underwent TESE in a single IVF unit between 1995 and 2017 was conducted. All patients with NOA who underwent TESE during their fertility treatments were included. The development of gradient-boosted trees (GBTs) aimed to predict the presence or absence of spermatozoa in patients with NOA. The accuracy of these GBTs was then compared to a similar multivariate logistic regression model (MvLRM).

PARTICIPANTS/MATERIALS, SETTING, METHODS

We employed univariate and multivariate binary logistic regression models to predict the probability of successful TESE using a dataset from a retrospective cohort. In addition, we examined various ensemble machine-learning models (GBT and random forest) and evaluated their predictive performance using the leave-one-out cross-validation procedure. A cutoff value for successful/unsuccessful TESE was calculated with receiver operating characteristic (ROC) curve analysis.

MAIN RESULTS AND THE ROLE OF CHANCE

ROC analysis resulted in an AUC of 0.807 ± 0.032 (95% CI 0.743–0.871) for the proposed GBTs and 0.75 ± 0.052 (95% CI 0.65–0.85) for the MvLRM for the prediction of presence or absence of spermatozoa in patients with NOA. The GBT approach and the MvLRM yielded a sensitivity of 91% vs. 97%, respectively, but the GBT approach has a specificity of 51% compared with 25% for the MvLRM. A total of 78 (65.3%) men with NOA experienced successful TESE. FSH, LH, testosterone, semen volume, age, BMI, ethnicity and testicular size on clinical evaluation were included in these models.

LIMITATIONS, REASONS FOR CAUTION

This study is a retrospective cohort study, with all the associated inherent biases of such studies. This model was used only for TESE, since micro-TESE is not performed at our center.

WIDER IMPLICATIONS OF THE FINDINGS

Machine-learning models may lay the foundation for a decision support system for clinicians together with their NOA patients concerning TESE. The findings of this study should be confirmed with further larger and prospective studies.

STUDY FUNDING/COMPETING INTEREST(S)

The study was funded by the Division of Obstetrics and Gynecology, Soroka University Medical Center, there are no potential conflicts of interest for all authors.

Idiopathic bleeding during the second half of pregnancy as a risk factor for adverse perinatal outcome

OBJECTIVE

To investigate pregnancy outcome in women suffering from idiopathic vaginal bleeding (IVB) during the second half of pregnancy.

METHODS

A comparison between patients admitted to the hospital due to bleeding during the second half of pregnancy and patients without bleeding was performed. Patients lacking prenatal care as well as multiple gestations were excluded from the analysis. Stratified analyses using the Mantel-Haenszel technique and a multiple logistic regression model were performed to control for confounders.

RESULTS

During the study period, 173,621 singleton deliveries occurred at our institute. Of these, 2077 (1.19%) were complicated with bleeding upon admission during the second half of pregnancy. After excluding cases with bleeding due to placental abruption, placenta previa, cervical problems, etc., 67 patients were classified as having IVB (0.038%). Independent risk factors associated with IVB, using a backward, stepwise multivariable analysis were oligohydramnios (OR=6.2; 95% CI 3.1-12.7; p < 0.001), premature rupture of membranes (OR=3.4; 95% CI 1.8-6.2; p < 0.001), intrauterine growth restriction (IUGR, OR 5.6; 95% CI 2.5-12.2; p < 0.001), and Jewish ethnicity (OR=1.9; 95% CI 1.0-3.5; p=0.036). These patients subsequently were more likely to deliver preterm (<37 weeks, 56.7% vs. 7.3%; mean gestational age of 33.6+/-5.7 weeks vs. 39.2+/-2.1 weeks; p < 0.001) and by cesarean delivery (CD, 35.8% vs. 12.1%, OR=4.0; 95% CI 2.4-6.6; p < 0.001). Higher rates of low Apgar scores (<7) at 1 and 5 minutes were noted in these patients (OR=10.3; 95% CI 5.9-17.8; p < 0.001 and OR=17.8; 95% CI 7.1-44.5; p < 0.001, respectively). Moreover, perinatal mortality rate among patients admitted due to idiopathic bleeding was significantly higher as compared to patients without bleeding (9.6% vs. 1.2%, OR=8.4; 95% CI 3.3-21.2; p < 0.001). However, when controlling for preterm delivery, using the Mantel-Haenszel technique, the association lost its significance.

CONCLUSION

Idiopathic vaginal bleeding during the second half of pregnancy is a risk factor for adverse perinatal outcome, mostly due to its significant association with preterm delivery. Careful surveillance, including fetal monitoring, is suggested in these cases in order to reduce the adverse perinatal outcome.