Outcomes comparison of IVF/ICSI among different trigger methods for final oocyte maturation: A systematic review and meta‐analysis
Bibliographic record
Abstract
During the in vitro fertilization treatment, human chorionic gonadotrophin (hCG) is routinely used as a substitute for the natural endogenous LH surge during the final stage of oocyte maturation. However, it does not provide the FSH surge observed in the mid-cycle of the natural cycle. To date, whether the FSH surge can improve oocyte quality and pregnancy outcomes remains unknown. Randomized controlled trials comparing the following four trigger methods to conventional hCG were examined: GnRH agonist (GnRHa), kisspeptin, GnRHa plus hCG (dual trigger), and FSH plus hCG (FSH co-trigger). The results showed that the use of dual triggers was associated with a significantly higher number of retrieved cumulus-oocyte complexes (COCs) (weighted mean difference [WMD] 1.625, 95% CI 0.684-2.565), retrieved mature oocytes (WMD 0.986, 95% CI 0.426-1.545) and fertilized (2PN) oocytes (WMD 0.792, 95% CI 0.083-1.501), compared with the use of hCG. However, there was no significant difference between the two groups in terms of pregnancy rate. The FSH co-trigger resulted in significantly higher rates of 2PN oocytes retrieved than the hCG trigger (WMD 0.077, 95% CI 0.028-0.126). Notably, the risk of OHSS did not differ among the three treatment groups compared to that of the hCG group. This review protocol was registered with PROSPERO (CRD 42020194201).
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How this classification was reachedexpand
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.011 | 0.005 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 teacher head, 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".