Causes of embryo implantation failure: A systematic review and metaanalysis of procedures to increase embryo implantation potential
Bibliographic record
Abstract
Introduction: fertilization and embryo transfer (IVF-ET) are pivotal, with the quality of embryo quality essential for successful implantation. Objective: This systematic review with meta-analysis aimed to explore the prevalence of embryonic factors involved in the implantation process, concentrating on the following research inquiries: 1) the implantation rates of euploid versus untested embryo transfers; 2) the efficiency of transferring good embryos in different age groups; 3) the impact of age on good embryo transfers to gestational carriers; and 4) the transfer of donated gametes/embryos. The goal is to identify critical points in implantation to improve therapies. Methods: A comprehensive literature search identified 1474 relevant papers, 11 of which met the inclusion criteria. The information was gathered using a standardized form, and the risk of bias was evaluated. A meta-analysis of subgroups to determine euploid embryo transfer efficiency was conducted to synthesize and explore the results. Furthermore, data extracted from registries document the persistent secondary role of extraembryonic determinants in successful implantation. Results: The meta-analysis demonstrated that preimplantation genetic testing for aneuploidy (PGT-A) significantly increased the odds of implantation. Age was found to influence extraembryonic factors, with older women experiencing reduced embryo implantation as gestational carriers. However, the overall incidence of extraembryonic factors was low. This review highlights the need to focus on PGT-A, diagnostic hysteroscopy, and endometrial receptivity for improving implantation rates. Conclusion: Implantation success in ARTs largely depends on embryo euploidy. While achieving three euploid embryos greatly increases success rates, it is challenging in older women. Extraembryonic factors, although present, have a marginal impact. Subsequent studies ought to concentrate on modulating endometrial responses immunologically and developing algorithms to improve the precision of predicting implantation success; as well as the timing of endometrial receptivity and the occurrence of dormant embryo phenomena also warrants further investigation.
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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 | 0.014 | 0.041 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.013 | 0.030 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".