Quantification of ovarian power Doppler signal with three-dimensional ultrasonography to predict response during in vitro fertilization.
Bibliographic record
Abstract
OBJECTIVE: To evaluate whether power Doppler predicts ovarian response to gonadotrophin stimulation during in vitro fertilization (IVF). METHODS: Forty-five women were divided into low-reserve (n = 12) and normal-reserve (n = 33) ovarian groups, according to antral follicle count. Transvaginal three-dimensional power Doppler ultrasonographic examinations were performed after pituitary downregulation and after gonadotrophin stimulation. The antral follicle count, ovarian volume, vascularization index, flow index, vascularization flow index, and mean gray value were measured and related to the number of oocytes retrieved and the pregnancy rate. RESULTS: The number of oocytes retrieved correlated with the antral follicle count (R =.458, P =.004) and ovarian volume (R =.388, P <.016) but not with vascularization index, flow index, vascularization flow index, or mean gray value after pituitary suppression. There was an increase in vascularization index (P <.017), flow index (P <.001), and vascularization flow index (P <.007) during gonadotrophin stimulation in the normal-ovary group but not in the low-ovarian-reserve group. CONCLUSION: According to our results, quantification of power Doppler signal in the ovaries after pituitary suppression does not provide any additional information to predict the subsequent response to gonadotrophin stimulation during IVF. The increase in ovarian power Doppler signal during gonadotrophin stimulation is related to the antral follicle count observed after pituitary suppression.
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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 | 0.005 |
| 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".