Clinical and economic analysis of rescue intracytoplasmic sperm injection cycles
Bibliographic record
Abstract
OBJECTIVE: To identify clinical and embryological factors that may predict success in rescue intracytoplasmic sperm injection (ICSI) cycles (after total fertilization failure has occurred) and to evaluate the cost effectiveness of rescue ICSI strategy. Additionally, follow-up of 20 rescue ICSI pregnancies is reported. DESIGN: Retrospective analysis of total fertilization failure cycles. SETTING: University-based tertiary medical center. MATERIAL AND METHODS: In total, 92 patients who had undergone conventional in-vitro fertilization (IVF) cycles with total fertilization failure were included. The patients were divided into two subgroups: those who conceived through rescue ICSI and those who did not. RESULTS: The pregnant members of the rescue ICSI subgroup were found to be significantly younger (32.9 ± 4.2 vs. 36.3 ± 4.5, respectively, p = 0.0035,) and to have better-quality embryos than those who did not conceive (cumulative embryo score: 38.3 ± 20.4 vs. 29.3 ± 14.7, p = 0.025). Cost effectiveness analysis showed 25% reduction in the cost per live birth when rescue ICSI is compared to cycle cancellation approach. The pregnancies follow-up did not show adverse perinatal outcome. CONCLUSIONS: Rescue ICSI is an option for salvaging IVF cycles complicated by total fertilization failure. Success in rescue ICSI was found to be associated with younger age and higher quality of embryos. Furthermore, the cost effectiveness of rescue ICSI in terms of total fertilization failure was found to be worthwhile.
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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 | 0.002 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| 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) | 0.003 | 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".