Tracking of oocyte dysmorphisms for ICSI patients may prove relevant to the outcome in subsequent patient cycles
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: We determined whether oocyte dysmorphisms, especially repetition of specific dysmorphisms from cycle to cycle, had a prognostic impact on intracytoplasmic sperm injection (ICSI) outcome. METHODS: ICSI patients (n = 67) were grouped as follows: group 1 >50% phenotypically dysmorphic oocytes per cohort (cytoplasmic and extra-cytoplasmic dysmorphisms) with no repetition of a specific dysmorphism from cycle one to cycle two (36 cycles and 274 oocytes); group 2 >50% dysmorphic oocytes per cohort and repetition of the same dysmorphism from cycle one to cycle two (32 cycles and 313 oocytes); group 3 (control) <30% dysmorphic oocytes (33 cycles and 378 oocytes). RESULTS: In group 2 (repetitive), 47% of oocytes were observed to have organelle clustering versus 20.5% in group 1 and 17.3% in group 3 (P < 0.001). There was no difference between the groups in fertilization rates, cleavage rates or embryo quality. Embryos derived from normal oocytes were transferred in each group (57, 33 and 72% respectively). The clinical pregnancy and implantation rates in group 2 (3.1 and 1.7% respectively) were lower (P < 0.01, P = 0.005) than both group 1 (28 and 15% respectively) and group 3 (45.5 and 26.5% respectively). CONCLUSIONS: The low implantation rate in group 2, even though 33% of transferred embryos were derived from morphologically normal oocytes, suggests that repetitive organelle clustering may be associated with an underlying adverse factor affecting the entire follicular cohort.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| 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) | 0.000 | 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 it