Temporal Evaluation of a Minimally Invasive Method of Preimplantation Genetic Testing for Aneuploidy (mi-PGT-A) in Human Embryos
Bibliographic record
Abstract
Preimplantation genetic testing for aneuploidy (PGT-A) has become a useful approach for embryo selection following IVF and ICSI. However, the biopsy process associated with PGT-A is expensive, prone to errors in embryo ploidy determination, and potentially damaging, impacting competence and implantation potential. Therefore, a less invasive method of PGT-A would be desirable and more cost-effective. Noninvasive methods for PGT-A (ni-PGT-A) have been well-studied but present limitations in terms of cf-DNA origin and diagnostic accuracy. Minimally invasive pre-implantation genetic testing (mi-PGT-A) for frozen-thawed embryo transfer is a promising, less studied approach that utilizes a combination of spent culture media (SCM) and blastocoelic fluid (BF)-derived cell-free (CF)-DNA for genetic testing. This study aimed to optimize the effectiveness of mi-PGT-A for aneuploidy diagnosis by investigating the optimal temporal sequence for this protocol. SCM+BF was collected at either 48 or 72 h of culture after thawing day 3 preimplantation embryos. cf-DNA in the SCM+BF was amplified, analyzed by next-generation sequencing (NGS) and compared with results from the corresponding whole embryos (WEs) obtained from human embryos donated for research. Fifty-three (42 expanded blastocysts, 9 early blastocysts, and 2 morula) WE and SCM+BF samples were analyzed and compared. The overall concordance rate between SCM+BF and WE was 60%. Gender and ploidy concordance improved with extended culture time from 48 h (73% and 45%) to 72 h (100% and 64%), respectively. These results demonstrate that SCM+BF-derived cf-DNA can be successfully used for mi-PGT-A. Our findings indicate that longer embryo culture time prior to SCM+BF-derived cf-DNA analysis improves DNA detection rate and concordance with WEs and decreases the proportion of false positive results.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".