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Update on preimplantation genetic testing for aneuploidy and outcomes of embryos with mosaic results

2022· article· en· W4306728770 on OpenAlexaff
Elias M. Dahdouh, Ali Mourad, Jacques Balayla, Camille Sylvestre, Paul R. Brezina, William H. Kutteh, Ludovica Picchetta, Antonio Capalbo, Juan A. García-Velasco

Bibliographic record

VenueMinerva Obstetrics and Gynecology · 2022
Typearticle
Languageen
FieldMedicine
TopicPrenatal Screening and Diagnostics
Canadian institutionsJewish General HospitalMcGill UniversityUniversité de MontréalCentre Hospitalier Universitaire Sainte-Justine
Fundersnot available
KeywordsAneuploidyGenetic testingIn vitro fertilisationEmbryoPloidyBiologyMosaicBioinformaticsMedicineChromosomeGeneticsGene

Abstract

fetched live from OpenAlex

Preimplantation genetic testing for aneuploidy (PGT-A) is used as a frequent add-on for in-vitro fertilization (IVF) to improve clinical outcomes. The purpose is to select a euploid embryo following chromosomal testing on embryo biopsies. The current practice includes comprehensive chromosome screening (CCS) technology applied on trophectoderm (TE) biopsies. Despite its widespread use, PGT-A remains a controversial topic mainly because all of the RCTs comprised only good prognosis patients with 2 or more blastocysts available; hence the results are not generalizable to all groups of patients. Furthermore, with the introduction of the highly-sensitive platforms into clinical practice (i.e. next-generation sequencing [NGS]), a result consistent with intermediate copy number surfaced and is termed "Mosaic," consistent with a mixture of euploid and aneuploid cells within the biopsy sample. The optimal disposition and management of embryos with mosaic results is still an open question, as many 'mosaics' generated healthy live births with no identifiable congenital anomalies. The present article provides a complete and comprehensive up-to-date review on PGT-A. It discusses in detail the findings of all the published RCTs on PGT-A with CCS, comments on the subject of "mosaicism" and its current management, and describes the latest technique of non-invasive PGT-A.

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

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmano category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Observationallow
gptno category
Domain: not available · Genre: Review
About the Canadian research system: no · About a Canadian topic: no
Other designlow
models splitAgreement compares identical category sets and study designs across arms.

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)0.007
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 score0.176
Threshold uncertainty score0.881

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.007
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 head0.026
GPT teacher head0.262
Teacher spread0.236 · 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

Labeled directly by 2 models reading the full record.

The models applied no category: nothing in the taxonomy fit this work.

The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.

Study designObservational · Other design
Domainnot available
GenreEmpirical · Review

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

Citations4
Published2022
Admission routes1
Has abstractyes

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