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Record W4283717827 · doi:10.1093/humrep/deac107.180

P-187 Post-thaw embryo quality is not predictive of live birth rates in frozen embryo transfer cycles: a retrospective cohort study

2022· article· en· W4283717827 on OpenAlexaffabout
Chieh-Chen Wu, Vincent Nguyen, Marie-Claude Léveillé, Jenna Gale

Bibliographic record

VenueHuman Reproduction · 2022
Typearticle
Languageen
FieldMedicine
TopicReproductive Biology and Fertility
Canadian institutionsOttawa Fertility CentreUniversity of Ottawa
Fundersnot available
KeywordsEmbryo transferLive birthEmbryo qualityMiscarriageEmbryoPregnancyObstetricsMedicineLogistic regressionRetrospective cohort studyEmbryo cryopreservationGynecologyPregnancy rateAndrologyBiologyIn vitro fertilisationSurgeryInternal medicineGenetics

Abstract

fetched live from OpenAlex

Abstract Study question To determine whether post-thaw change in embryo quality is associated with live birth outcomes. Summary answer Post-thaw embryo morphology is not predictive of live birth rates in single frozen embryo transfer cycles. What is known already Embryo quality is typically evaluated via morphological assessment of embryos based on the Gardner criteria. For medical or elective reasons, embryos are commonly frozen for future use through the vitrification process. Research has shown that embryo quality pre-vitrification correlates highly with freeze-thaw survival, implantation, pregnancy, and subsequent live birth rates. Good-quality embryos are therefore more likely to be selected for vitrification. However, it is not unusual to find a decline in the quality of these vitrified embryos upon thawing them for embryo transfer. Study design, size, duration We retrospectively identified a patient cohort based out of the Ottawa Fertility Centre in Ottawa, Ontario, Canada, between 2016 and 2020. Participants/materials, setting, methods Frozen single embryo transfer (FET) cycles involving good-quality expanded blastocysts deriving from autologous oocytes were selected for inclusion. We compared FET cycles involving good post-thaw embryo quality to those with worsened/poor post-thaw embryo quality. The primary outcome was live birth after FET. Secondary outcomes included rates of positive serum human chorionic gonadotropin, clinical intrauterine pregnancy, miscarriage, and ectopic pregnancy. We fit a multivariate logistic regression model, adjusting for patient and cycle characteristics. Main results and the role of chance A total of 962 single FET cycles were analyzed. There were 826 embryos that preserved their pre-vitrification quality post-thaw and 136 embryos that exhibited poorer quality on post-thaw assessment. Baseline characteristics were mostly comparable between the two groups under study. In the multivariate regression model, the adjusted odds of live birth was not significantly different in the group with good post-thaw embryo quality compared to that in the group with worse/poor post-thaw embryo quality (odds ratio [OR] 1.30, 95% confidence interval [CI] 0.86-1.96, p = 0.21). Similarly, no significant associations were found between post-thaw embryo quality and the secondary outcomes of positive BhCG (OR 1.19, 95% CI 0.81-1.75), clinical intrauterine pregnancy (OR 1.29, 95% CI 0.87-1.87), miscarriage (OR 0.97, 95% CI 0.53-1.77), and ectopic pregnancy rates (OR 0.41, 95% CI 0.14-1.24). Limitations, reasons for caution Although a multivariate regression model was used to adjust for clinically relevant confounders, there remains the possibility for residual confounding given the observational nature of our study. Wider implications of the findings The results of our study suggest that, after adjusting for patient and cycle characteristics, post-thaw embryo quality does not impact live birth outcomes. Trial registration number Not applicable

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)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.070
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.035
GPT teacher head0.325
Teacher spread0.291 · 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.

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
Published2022
Admission routes2
Has abstractyes

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