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Record W2913170133 · doi:10.1002/ijgo.12768

Dual oocyte retrieval and embryo transfer in the same cycle for women with premature ovarian insufficiency

2019· article· en· W2913170133 on OpenAlexaff
Şafak Hatırnaz, Barış Ata, Ebru Hatırnaz, Alper Başbuğ, Samer Tannus

Bibliographic record

VenueInternational Journal of Gynecology & Obstetrics · 2019
Typearticle
Languageen
FieldMedicine
TopicOvarian function and disorders
Canadian institutionsMcGill University Health Centre
Fundersnot available
KeywordsOocyteFollicular phaseEmbryo transferMedicinePremature ovarian insufficiencyStimulationMenstrual cycleAndrologyEmbryoOvarian follicleGynecologyInternal medicineBiologyHormone

Abstract

fetched live from OpenAlex

OBJECTIVE: To compare dual oocyte retrieval with minimal ovarian stimulation and embryo transfer in the same menstrual cycle versus conventional ovarian stimulation among women with premature ovarian insufficiency (POI). METHODS: A retrospective study of 51 women with POI attending a reproductive center in Turkey between 2013 and 2015. Women with an ovarian follicle of 12 mm or larger early in the follicular phase who underwent oocyte retrieval followed by an immediate cycle of ovarian stimulation (group 1, n=14) were compared with those who received conventional ovarian stimulation (group 2, n=37). Both groups underwent subsequent ovarian stimulation cycles to obtain optimally two embryos for transfer. RESULTS: The groups had similar baseline parameters. Serum estradiol was higher in group 1 (P<0.001); total number of oocyte retrievals was higher in group 2 (P<0.001); and total number of oocytes retrieved was similar (P=0.192). Group 1 had more higher-quality embryos (P=0.031). There was a non-significant trend toward higher live birth rates in the dual trigger group (28% vs 8%, P=0.08). CONCLUSION: Rescuing growing follicles early in the follicular phase combined with subsequent ovarian stimulation and embryo transfer in the same cycle resulted in fewer oocyte retrieval cycles and might potentially improve reproductive outcomes.

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)0.001
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 score0.405
Threshold uncertainty score0.270

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.009
GPT teacher head0.250
Teacher spread0.241 · 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

Citations6
Published2019
Admission routes1
Has abstractyes

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