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Record W4416273492 · doi:10.1016/j.rbmo.2025.105373

Approaches to frozen embryo transfer: a Canadian Fertility and Andrology Society guideline

2025· article· en· W4416273492 on OpenAlexaffabout
Julio Saumet, Elias M. Dahdouh, Camille Sylvestre, Heather Shapiro, Jason Min, Jeff Roberts, Kimberly Liu, Maria P. Vélez, Neal Mahutte, Sony Sierra, William Buckett

Bibliographic record

VenueReproductive BioMedicine Online · 2025
Typearticle
Languageen
FieldMedicine
TopicOvarian function and disorders
Canadian institutionsOttawa Fertility CentreSinai Health SystemWomen's College HospitalPacific Centre for Reproductive MedicineCentre Hospitalier Universitaire Sainte-JustineMcGill UniversityUniversity of CalgaryUniversité de Montréal
Fundersnot available
KeywordsGuidelinePregnancyEmbryo transferFertilityLive birthReproductive medicineRandomized controlled trialIncidence (geometry)

Abstract

fetched live from OpenAlex

This guideline provides evidence-based recommendations, drawn exclusively from recent randomized control trials, for the clinical management of frozen embryo transfers (FET). In Canada, the incidence of freeze-all cycles has increased from 24.0% to 78.4% over the last decade. While a freeze-all strategy can be a pivotal tool for preventing ovarian hyperstimulation syndrome, the available data do not support its routine use for improving live birth rates, reducing pregnancy loss or enhancing obstetric outcomes in the general IVF population. Similarly, ovulatory FET cycles do not offer advantages over artificial FET cycles for live birth or pregnancy loss, and current evidence remains conflicting for obstetric and perinatal outcomes. The route of progesterone administration in artificial FET cycles does not significantly affect live birth or pregnancy loss rates. FET approaches should be individualized based on patient characteristics and clinical context, and further research is necessary to optimize outcomes and inform best practices.

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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.384
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 integrity0.0000.000
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 head0.056
GPT teacher head0.290
Teacher spread0.234 · 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 designNot applicable
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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