P-106 Total motile sperm count and oral ovulation induction protocols are not predictors of success in donor insemination cycles: Results from a large retrospective cohort study
Bibliographic record
Abstract
Abstract Study question to investigate the effect of total motile sperm (TMS) count, and ovulation induction on clinical pregnancy rate in artificial insemination with donor (AID) cycles. Summary answer TMS count is not a predictor of sucess, and natural cycles are as effective as oral ovulation induction in donor inseminations What is known already There are inconsistent results regarding the effect of sperm parameters on success rates of artificial insemination with donor (AID). Besides, the use of gonadotropin stimulation for ovulation induction in this category of patients is questionable, and its effectiveness over natural cycles is not yet confirmed in the literature. Study design, size, duration Patients who underwent AID cycles at the university-affiliated fertility center-OVO clinic in Montreal, Canada between 2011 and 2015 were retrospectively selected. A total of 4333 AID cycles were performed on 1179 patients, resulting in 744 pregnancies. Participants/materials, setting, methods Cycles were divided into 8 groups based on TMS count: <0.5, [0.5-1[, [1-5[, [5-10[, [10-20[, [20-40[, [40-80[, and ≥80. A TMS of 10 to 20 million was selected as a reference level. Ovulation induction was divided into oral stimulation, combined oral and gonadotropin stimulation and gonadotropin-only stimulation, and compared to natural cycles. Regression analysis and a predictive model of clinical pregnancy in AID cycles were generated from patient demographic and cycle characteristics. Main results and the role of chance There was no significant difference in positive β-hCG result, clinical pregnancy, multiple pregnancy and miscarriage rates when comparing all ranges of TMS count to a reference of 10 to 20 million. When dividing patients based on the protocol for ovulation induction, clinical pregnancy rate was significantly higher in the gonadotropin-only stimulation group (OR 4.116,[1.379,12.287]) but not in other types of stimulation, as compared to natural cycles. hCG triggering resulted in a similar clinical pregnancy and miscarriage rates, but a higher multiple pregnancy rate when compared to urinary LH testing (7.7% versus 1.3%, p = 0.045). A multivariate logistic regression analysis for predictors of clinical pregnancy accounting for relevant demographic and cycle characteristics was conducted. No significant difference was noted in different ranges of TMS and the groups of ovulation induction. In this model, age was found to be a significant predictor. In particular, with every one-year increase in age, the odds of clinical pregnancy decreases by 6.4% (Adjusted OR 0.936; 95%CI [0.914, 0.958]). Limitations, reasons for caution In our study, cycles with TMS count below 1 million are limited. Thus, results should be viewed with caution in this group, without cycle cancellation, since clinical pregnancy can be achieved. Moreover, our results cannot be generalized on infertile couples given the characteristics of our population of interest. Wider implications of the findings Minimal or maximal cut-off values for TMS in AID cycles should not be used as indicators for cycle cancellation. Natural cycles are as successful as oral ovulation induction. hCG trigger, unless indicated, should not be used as it is associated with higher risk of multiple pregnancy without increasing clinical pregnancy. Trial registration number not applicable
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".