The outcome of IVF-embryo transfer treatment in patients who develop three follicles or less
Bibliographic record
Abstract
Among 828 patients undergoing IVF-embryo transfer treatment, the implantation and pregnancy rates of patients who developed < or = 3 follicles were compared prospectively with those patients who had a normal response. Patients who developed 1 to 3 follicles during ovarian stimulation elected to proceed with oocyte collection, have intrauterine insemination if appropriate, or to have their cycle cancelled. In the group of patients who developed < or = 3 follicles and who were aged <40 years, despite a significantly lower number of oocytes collected [2 versus 7; median difference (MD) = 9; confidence interval (CI) = 7-11, and lower number of embryos developed and transferred (1 versus 3; MD = 2; CI = 1-2), no difference in either implantation rate [27.8 versus 20.4%; odds ratio (OR) = 1.58; CI = 0.46-4.54] or pregnancy rate (27.8 versus 36.7%; OR = 0.7; CI = 0.2-2.0) was noted when compared with similarly aged patients who developed >3 follicles. However, in patients aged >40 years who developed < or = 3 follicles, a moderate, albeit non-significant decrease in implantation rate (3.8 versus 7.8%; OR = 1.91; CI = 0.4-57.0) and pregnancy rate (4.2 versus 18.3%; OR = 1.92; CI = 0.38-57.0) was observed when compared with patients of a similar age who developed >3 follicles. Patients aged <40 years, unlike older patients, maintain good implantation and pregnancy rates despite a poor response to ovarian stimulation. This study indicates that for this group of women, continuation of IVF treatment is a better option than cancellation.
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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 | 0.000 | 0.003 |
| 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 | 0.001 | 0.001 |
| 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".