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Record W2135720977 · doi:10.1093/humrep/dev024

A comparison of biochemical pregnancy rates between women who underwent IVF and fertile controls who conceived spontaneously

2015· article· en· W2135720977 on OpenAlexaff
Atif Zeadna, W. Y. Son, Jeong Hee Moon, Michael H. Dahan

Bibliographic record

VenueHuman Reproduction · 2015
Typearticle
Languageen
FieldMedicine
TopicOvarian function and disorders
Canadian institutionsMcGill University
Fundersnot available
KeywordsPregnancyGynecologyObstetricsMedicinePregnancy rateFertilityBiologyPopulation

Abstract

fetched live from OpenAlex

STUDY QUESTION: Does IVF affect the biochemical pregnancy rate? SUMMARY ANSWER: The likelihood of an early pregnancy loss may be lower and is certainly not higher in IVF cycles when compared with published rates of biochemical pregnancy in fertile women ≤42 years old. WHAT IS KNOWN ALREADY: The use of gonadotrophins to stimulate multi-folliculogenesis alters endometrial expression of genes and proteins, compared with unstimulated cycles. Exogenous estrogen and progesterone taken for endometrial preparation in frozen embryo transfer cycles, also cause changes in endometrial gene and protein expression .These endometrial alterations may compromise the ability of embryos to develop once implanted, possibly increasing the biochemical pregnancy rate. STUDY DESIGN, SIZE, DURATION: This is a retrospective study, involving 1636 fresh and 188 frozen, single embryo transfer (SET) IVF cycles performed between August 2008 and December 2012. The biochemical pregnancy rate of the 1824 combined IVF and frozen cycles were compared with fertile controls, derived from the three prospective studies in the medical literature that evaluate this rate. PARTICIPANTS/MATERIALS, SETTING, METHODS: Subjects ≤42-years old, who underwent a SET, as part of a fresh or thawed IVF cycle were considered for inclusion. Each subject is represented only once. The biochemical pregnancy rates were compared with those of historical standard, fertile populations with spontaneous conceptions. MAIN RESULTS AND THE ROLE OF CHANCE: The pregnancy rates per transfer for fresh and frozen IVF cycles were similar at 39 and 40%, respectively. There was also no significant difference in the likelihood of pregnancy outcomes (clinical, biochemical and ectopic pregnancy) between fresh IVF and frozen cycles (85.4 versus 85.6%, 13.8 versus 14.8%, 0.5 versus 0%, P = 0.82). However, pregnancy rates decreased in older patients when compared with younger ones P < 0.0001. The biochemical pregnancy rate for fresh and frozen IVF cycles combined was 13.8% of all pregnancies. IVF and frozen cycles were combined as the IVF group treated with hormones for further comparison with the fertile control group. The biochemical pregnancy rate (14%) in the IVF group was lower than the rate based on the total fertile group (18%), P = 0.01 and differed significantly from the rate in two out of the three studies used to establish the normative rate. The age ranges of the IVF and fertile controls were 21-42 years. The mean age in the IVF population was 34.8 years, as compared with 29 years, 29, 4 years and 30.6 years (Zinaman) in the three published studies (mean: 29.4 years). LIMITATIONS, REASONS FOR CAUTION: This is a retrospective study and it was impossible to recruit an in-house biochemical pregnancy control population. WIDER IMPLICATIONS OF THE FINDINGS: Lower early pregnancy wastage after IVF may be due to the opportunity to select the embryo for transfer. This finding should be confirmed in further studies but supports the idea that embryo selection is an important step. STUDY FUNDING/COMPETING INTERESTS: None.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.072
GPT teacher head0.347
Teacher spread0.275 · 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 source (direct Gemma or distilled Codex), 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

Citations53
Published2015
Admission routes1
Has abstractyes

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