Does the Human Embryo Culture Media Has Any Impact on Implantation and Live Birth Rate in ART Cycles? A Comparative Study
Bibliographic record
Abstract
A BSTRACT Introduction: Culture media plays a pivotal role in the embryo culture system apart from the other crucial components as air quality, temperature, humidity etc., so that the selection of embryo culture media is a crucial step for the embryology team for the optimal blastocyst development and for achieving a viable pregnancy. There are two opposing views for the selection of embryo culture medium. One is embryo free choice’-“Let the embryo choose” (single-step media) and the other one is “back to nature” (sequential media) approach. Present study analyses the efficacy of these media in terms of embryo developments in vitro and pregnancy rates. Materials and Methods: Patients were randomly recruited for single step or sequential media culture post intracytoplasmic sperm injection. Inclusion criteria were patients with no severe male or female factors. To minimize the confounding variables, patients with surgically retrieved sperm samples were excluded from the study. Biochemical pregnancy, clinical pregnancy, implantation rate, live birth rate and miscarriage rate were analyzed. Results: Biochemical pregnancy, clinical pregnancy and live birth rate were favorable for group 2 (sequential media) but not statistically significant. None of the analyzed parameters differed significantly among the two media. Conclusion: There is a lack of solid scientific data to support the sequential media culture. However, moving embryos from one medium to another in a sequential media system probably adds significant stress to the preimplantation developing embryos in-culture apart from the unintentional humane errors. Moreover, this approach is quite labor-intensive and expensive.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".