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Record W4411751770 · doi:10.1093/humrep/deaf097.363

P-054 Optimization of pregnancy rates in donor intrauterine insemination: impact of age, protocol, and number of cycles: analysis of 1961 cycles

2025· article· en· W4411751770 on OpenAlexaffabout
Naameh Moussaoumay, Robert Hemmings, Camille Sylvestre

Bibliographic record

VenueHuman Reproduction · 2025
Typearticle
Languageen
FieldMedicine
TopicAssisted Reproductive Technology and Twin Pregnancy
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsIntrauterine inseminationPregnancyInseminationDonor inseminationAndrologyMedicineProtocol (science)GynecologyPregnancy rateObstetricsArtificial inseminationBiologyGeneticsSperm

Abstract

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Abstract Study question What are the factors optimizing pregnancy rates in donor intrauterine insemination (IUI) for the women who is not exposed to natural or spontaneous pregnancy? Summary answer Donor IUI is most effective for women under age 35, remains acceptable up to 42, and is optimized with natural cycles and ≤5 cycle attempts. What is known already Donor artificial insemination (AID) is widely used for single women and same-sex female couples. Maternal age, ovarian stimulation protocols, and the number of insemination cycles influence success rates. It is well established that pregnancy rates decrease with advancing maternal age due to diminished ovarian reserve and declining oocyte quality. Stimulation protocols are commonly employed to time ovulation, yet their effectiveness remains debated, particularly in older women. Limited data exist on the comparative benefits of natural versus stimulated cycles and the optimal number of insemination cycles required to achieve pregnancy. Study design, size, duration A retrospective observational study analyzed 745 women undergoing 1,961 donor IUI cycles between January 2023 and August 2024 at a university-affiliated fertility clinic in Montreal, Canada. The variables studied included age, protocol type, and the number of insemination attempts. The primary outcome was a positive pregnancy test. Participants/materials, setting, methods A total of 745 women undergoing 1,961 donor intra-uterine insemination cycles were categorized into five age groups (<35, 35–38, 38–40, 40–42, and ≥42 years). Cycle protocols were classified as natural or stimulated (letrozole, letrozole + gonadotropins, or gonadotropins alone). The study assessed pregnancy rates based on age, protocol type, and the number of insemination cycles performed. Main results and the role of chance A total of 1,961 cycles were analyzed, yielding 262 pregnancies. Pregnancy rates significantly declined with advancing age. For women <35 years (n = 1048), the pregnancy rate was 16.5%, which was significantly higher compared to women aged 35–38 years (11.2%, p = 0.01), 38–40 years (10.9%, p = 0.02), 40–42 years (7.4%, p = 0.006), and ≥42 years (3.4%, p = 0.001). No pregnancies were observed in women aged 43 or older. In ovarian stimulation methods, natural cycles (n = 570) showed a pregnancy rate of 15.4%, with a trend toward higher pregnancy rates compared to letrozole alone (n = 971, 12.8%), letrozole + Gonadotropins (n = 384, 11.9%), and Gonadotropins alone (n = 36, 11.1%). However, no statistically significant differences were found (p = 0.15, p = 0.12, p = 0.47, respectively). Most pregnancies (84%) occurred within the first four cycles, with 92% of pregnancies achieved by the fifth cycle (241/262). No statistically significant improvements in pregnancy rates were observed beyond five cycles (p = 0.22). Limitations, reasons for caution The retrospective study design and the reliance on positive pregnancy tests rather than live birth rates were the main limitations of our study. A randomized controlled study should be performed to confirm these findings. Wider implications of the findings Donor IUI is most effective under 35 and remains acceptable up to 42, with natural cycles reducing costs and risks without compromising outcomes. Success rates plateau after five cycles, suggesting an optimal limit. Detailed counseling is crucial for single women and same-sex couples to guide informed decisions on fertility treatments. Trial registration number No

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.086
Threshold uncertainty score0.477

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.021
GPT teacher head0.371
Teacher spread0.350 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes2
Has abstractyes

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