Complete failed fertilization after intracytoplasmic sperm injection--analysis of 10 years' data.
Bibliographic record
Abstract
OBJECTIVE: To investigate incidence and causes of complete failed fertilization after intracytoplasmic sperm injection (ICSI) in a tertiary care facility. METHODS: A total of 1,779 cycles between February 1994 and December 2003 were analyzed. Study parameters were female age, infertility diagnosis, ovarian stimulation protocol, estradiol level on day of hCG administration, number of follicles, number of oocytes retrieved, number of oocytes injected, and semen parameters. RESULTS: Complete failed fertilization occurred in 23 cycles (1.29%) involving a total of 85 oocytes injected. Infertility causes among patients with failed fertilization included unexplained (43.6%), male factor (26%), presence of more than one factor (17.4%), hysterectomy (4.4%), premature ovarian failure (4.3%), and advanced age (4.3%). In 12 cycles (52%), fewer than 5 follicles were present. In three (13%) cycles, no mature (MII) oocyte was available and in 61% (14/23) fewer than 3 MII oocytes were available for ICSI. Immotile sperm was used for ICSI in 5 cycles (21.7%). The source of sperm in 17 (74%) cycles was from ejaculate, in 4 cycles from testicular aspiration (TESA), one from percutaneous epididymal sperm aspiration (PESA) and one from retrograde ejaculation. CONCLUSIONS: Our data indicate that major contributing factors to failed fertilization after intracytoplasmic sperm injection are number of MII oocytes retrieved and availability of viable sperm for injection. Although the incidence of complete failed fertilization is not remarkable, it may increase with increasing patient age and a lower number of follicles.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".