Development of a risk model for low oocyte retrieval in first-cycle IVF patients with diminished ovarian reserve: a...

Low oocyte retrieval (LOR), defined as oocytes retrieved from <50% of mature follicles, significantly impacts IVF success, especially in patients with diminished ovarian reserve (DOR). Predictive models tailored for this population are limited. This retrospective cohort study developed a predictive nomogram for LOR risk in first-cycle IVF/ICSI patients with DOR. The data from 2,594 eligible patients were analyzed. LOR was defined as oocyte retrieval rate <50% (oocytes/follicles ≥14 mm on trigger day). Least absolute shrinkage and selection operator (LASSO) regression identified predictors from clinical/endocrine parameters. A multivariate logistic model was built, visualized as a nomogram, and internally validated (bootstrap resampling). Performance was assessed via AUC, calibration, and decision curve analysis. Eight independent predictors were identified: age, basal FSH, AFC, AMH, LH on hCG day, progesterone (P) on hCG day, number of large follicles (≥14 mm) on hCG day, and trigger-to-retrieval time (TR-OPU). The model demonstrated moderate yet acceptable discrimination (AUC = 0.721, 95% CI: 0.678-0.772) and calibration. TR-OPU was significantly shorter in the LOR group (34.85 vs 35.05 h, P < 0.001). DCA confirmed clinical utility. This study establishes a clinical-endocrine nomogram predicting LOR risk in first-cycle DOR patients. Incorporating key factors, such as TR-OPU, ovarian reserve markers (AMH, AFC, and bFSH), and trigger-day hormones, it may help stratify risk but requires external validation before clinical application.

Women with naturally lower egg reserves often face extra challenges with IVF. A common problem is retrieving fewer eggs than expected during the procedure ('low oocyte retrieval' or LOR), which significantly lowers the chance of pregnancy. Doctors lack good tools to predict who is most at risk. Our study analyzed data from 2,594 women with low egg reserves undergoing their first IVF cycle. We created a simple prediction chart that combines key information easily available to doctors: the woman's age, standard hormone blood tests (AMH and FSH), an ultrasound count of egg sacs (follicles), hormone levels on the day of the final IVF trigger shot, and critically - the exact number of hours between the trigger and the egg collection surgery. This chart accurately estimates an individual woman's risk of LOR. Knowing this risk beforehand helps doctors personalize treatment timing and medication, aiming to collect more eggs and improve the chances of a successful pregnancy, while helping patients avoid unnecessary emotional and financial strain.