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Record W4234104734 · doi:10.5935/1518-0557.20190025

Oral Presentations

2019· article· en· W4234104734 on OpenAlexaboutno aff

Bibliographic record

VenueJBRA · 2019
Typearticle
Languageen
FieldMedicine
TopicPrenatal Screening and Diagnostics
Canadian institutionsnot available
Fundersnot available
KeywordsComputer science

Abstract

fetched live from OpenAlex

Objective: To evaluate the use of the known implantation data algorithm KIDscore TM D5 (Vitrolife , Canad) as an additional tool to morphologic assessment and preimplantation genetic testing for aneuploidies (PGT-A) to improve implantation and ongoing pregnancy rates. Methods: Design: Retrospective Cohort Study. A total of 912 embryos from 270 patients that underwent an IVF treatment at INMATER Fertility Clinic in Lima -Per, between October 2016 and June 2018, were analyzed. All embryos were cultured for up to 5 or 6 days in the Embryoscope time-lapse incubator (Vitrolife , Canada) and evaluated using the KIDscore TM D5 algorithm (KS5). 778 (85.31%) of these embryos were also biopsied for PGT-A screening. A total of 184 single embryo transfers (68% of patients), were performed during this period and the embryos transferred were classified into four groups: 1) Euploid embryos transferred without considering their KS5 score in the selection process (n=86), 2) Euploid embryos transferred considering their KS5 score in the selection process (n=48), 3) Embryos transferred without considering their KS5 score in the selection process and that were not evaluated by PGT-A (n=40) and 4) Embryos transferred considering their KS5 score in the selection process and that were not evaluated by PGT-A (n=10). Implantation and ongoing pregnancy rates were compared between the groups and between euploid embryos with the highest/ best KS5 score (KS5=6, n=25) and euploid embryos with the lowest/worst KS5 score (KS5=1, n=51). Correlation between KS5 score and embryo euploidy rate was also evaluated. Results: Implantation rate and ongoing pregnancy rates was found to be significantly higher in euploid embryo transfers when taking into account their KS5 score in the embryo selection process compared to euploid embryo transfers where selection was based on morphology (75.00% vs. 50.00%; p=0.002 and 66.66% vs 48.83%; p=0.037 respectively). Additionally, implantation rates were significantly higher for blastocysts with highest KS5 score (KS5=6) compared to lowest (KS5=1) (80.00% vs. 49.02%; p=0.045), and ongoing pregnancy rates was not found with significantly (72.00% vs 47.06%; p=0.105). Euploidy rate was significantly higher in the group of embryos with KS5=6 than in the group of embryos with KS5=1 (61.88% vs. 48.33%; p=0.006). Conclusion: Embryo selection by the use of the KS5 algorithm score improves implantation rates of single euploid blastocysts transfers. Furthermore, embryos with the highest KS5 score have a higher probability of being euploid and implanting.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.346
Threshold uncertainty score0.493

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0050.002
Open science0.0020.003
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.6540.422

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 head0.022
GPT teacher head0.317
Teacher spread0.295 · 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

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
Published2019
Admission routes1
Has abstractyes

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