Nomogram to Predict Pregnancy Outcomes of Emergency Oocyte Freeze – Thaw Cycles

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Nomogram to Predict Pregnancy Outcomes of Emergency Oocyte Freeze-Thaw Cycles

In recent decades, assisted reproductive technology (ART) has evolved significantly, with oocyte cryopreservation emerging as a critical tool for fertility preservation. However, predicting pregnancy outcomes following emergency oocyte freezing—often necessitated by unexpected sperm collection failures—remains challenging. This study introduces a novel nomogram-based predictive model to address this gap, offering clinicians and patients a data-driven tool for individualized decision-making.

Clinical Context and Rationale

Emergency oocyte cryopreservation is frequently required in clinical scenarios such as sudden unavailability of sperm donors, procedural failures in sperm extraction (e.g., microdissection testicular sperm extraction [MESA] or testicular sperm aspiration [TESA]), or masturbation difficulties. Abandoning oocyte retrieval in such cases wastes prior ovarian stimulation efforts and increases risks like ovarian hyperstimulation syndrome (OHSS). However, proceeding with freezing introduces uncertainties related to thawing success, fertilization, and embryo viability. Existing prediction models for in vitro fertilization (IVF) focus on fresh oocyte cycles, leaving a critical gap for frozen-thawed oocyte outcomes.

Study Design and Methodology

The study retrospectively analyzed 418 women undergoing emergency oocyte cryopreservation at Peking University Third Hospital (2007–2019). After excluding cycles with incomplete data or non-emergent freezing reasons, 211 patients (215 cycles) were included. Key outcomes were “no transferable embryo cycles” (no viable embryos post-thawing) and “cumulative live birth” (≥1 live birth from thawed oocytes).

Oocyte Retrieval and Cryopreservation Protocol
Ovarian stimulation involved gonadotropins (Gn) adjusted based on follicular growth. Triggering with recombinant human chorionic gonadotropin (hCG) occurred when ≥2 follicles reached ≥18 mm. Mature oocytes were vitrified using ethylene glycol and dimethyl sulfoxide solutions, thawed stepwise with sucrose dilution, and assessed for survival. Intracytoplasmic sperm injection (ICSI) was performed, with embryos cultured for 3 days before transfer or cryopreservation.

Predictors and Statistical Analysis
Variables included female age, body mass index (BMI), infertility duration, basal hormone levels (follicle-stimulating hormone [FSH], luteinizing hormone [LH], estradiol [E2]), antral follicle count (AFC), semen parameters, and sperm source (ejaculated, MESA, TESA). Multivariable logistic regression identified significant predictors, with model performance evaluated via area under the receiver operating characteristic curve (AUC), Hosmer-Lemeshow tests, and calibration plots.

Key Findings

Baseline Characteristics

The cohort had a mean female age of 29.9±4.95 years, infertility duration of 3.44±3.24 years, and basal FSH of 6.11±2.82 mIU/mL. Azoospermia accounted for 73.5% of semen cases, with MESA/TESA used in 19.5% of cycles. The oocyte survival rate was 75.4%, fertilization rate 69.5%, and cumulative live birth rate 39.6% (65/164). Notably, 20% (43/215) of cycles yielded no transferable embryos.

Predictors of “No Transferable Embryo Cycles”

Multivariable analysis identified five significant predictors:

  1. Female Age: Each year increased odds by 9.9% (OR=1.099; 95% CI:1.003–1.205; P=0.044).
  2. Infertility Duration: Each additional year raised odds by 14% (OR=1.140; 95% CI:1.018–1.276; P=0.024).
  3. Basal FSH: Higher levels correlated with increased risk (OR=1.205 per mIU/mL; 95% CI:1.051–1.382; P=0.008).
  4. Basal E2: Elevated E2 marginally increased risk (OR=1.006 per pmol/L; 95% CI:1.001–1.010; P=0.012).
  5. Sperm Source: MESA-derived sperm had 7.74-fold higher odds of no embryos vs. ejaculated sperm (95% CI:2.91–20.63; P<0.001).

The nomogram demonstrated excellent discrimination (AUC=0.799; 95% CI:0.722–0.875) and calibration (Hosmer-Lemeshow P=0.721), indicating robust predictive accuracy.

Predictors of Cumulative Live Birth

Two factors significantly influenced live birth likelihood:

  1. Follicles >10 mm on hCG Day: Each additional follicle increased odds by 8.8% (OR=1.088; 95% CI:1.030–1.149; P=0.002).
  2. Endometriosis: Reduced odds by 82.8% (OR=0.172; 95% CI:0.035–0.853; P=0.031).

The model showed moderate discrimination (AUC=0.724; 95% CI:0.647–0.801) and good calibration (P=0.562).

Clinical Implications and Model Utility

The nomogram provides a visual scoring system to quantify individual risks and benefits. For example, a 32-year-old with 3 years of infertility, basal FSH=7.5 mIU/mL, E2=131 pmol/L, and 8 follicles >10 mm would have a 25.3% risk of no transferable embryos if using ejaculated sperm, rising to 48.9% with MESA-derived sperm. Live birth probability under these conditions is 39.4%. Such precision aids in counseling patients on whether to proceed with retrieval or avoid futile interventions.

Strengths and Limitations

Strengths:

  • First prediction model specifically for emergency oocyte freeze-thaw cycles.
  • Incorporates novel predictors like sperm source and follicular count.
  • High methodological rigor, adhering to TRIPOD guidelines (self-evaluated score=90.9%).

Limitations:

  • Single-center, retrospective design with potential selection bias.
  • Small sample size (n=211) limits generalizability.
  • External validation pending due to rarity of emergency freezing scenarios.

Comparative Insights

Unlike existing IVF models focused on fresh cycles, this study highlights unique challenges in frozen oocyte contexts. Sperm source emerged as a critical factor, likely due to higher aneuploidy rates in surgically retrieved sperm from non-obstructive azoospermia (NOA) patients. Similarly, endometriosis—known to impair implantation—showed profound effects on live birth rates, aligning with prior literature.

Future Directions

Prospective multicenter studies are needed to validate the model across diverse populations. Integrating oocyte quality metrics (e.g., spindle integrity) and expanding predictors (e.g., genetic factors) could enhance accuracy. Development of a web-based calculator or mobile app would facilitate real-time clinical application.

Conclusion

This nomogram represents a paradigm shift in managing emergency oocyte cryopreservation, empowering patients and clinicians with evidence-based prognostic tools. By quantifying risks associated with age, ovarian reserve, sperm source, and endometriosis, it bridges a critical gap in ART counseling, optimizing resource utilization and patient outcomes.

doi.org/10.1097/CM9.0000000000001731

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