Embryo Transfer Procedural Parameters Do Not Predict IVF Cycle Outcome
Bibliographic record
Abstract
BACKGROUND: this study aims to assess the effect of embryo transfer (ET) performance parameters of a technical nature on IVF outcome. METHODS: A total of 1417 ETs from a single IVF center were included in this prospective observational study. The parameters investigated were as follows: the presence of cervical mucus post catheter withdrawal, the presence of blood, catheter reload, the employment of a tenaculum and stylet, catheter resistance as experienced by the physician and patient discomfort. RESULTS: When ET performance parameters were associated with clinical outcomes on a singular level, none of the ET parameters presented with any statistical significance. The evaluation of covariates indicated that the number and the quality of transferred embryos, as well as maternal age, exerted a statistically significant effect on clinical outcomes. In a multivariate analysis, only the presence of mucus along with significant catheter resistance presented with statistical significance; however, when adjusting for covariates, this combination showed no statistically significant effect on clinical outcomes. CONCLUSIONS: the results indicate that the time-consuming process of recording and analyzing ET performance parameters fails to offer any additional value in predicting the cycle's outcome, while factors like embryo quality and number, as well as maternal age, seem to be the sole robust predictive factors of an IVF cycle.
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 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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".