Urinary hMG versus recombinant FSH for controlled ovarian hyperstimulation following an agonist long down-regulation protocol in IVF or ICSI treatment: a systematic review and meta-analysis
Bibliographic record
Abstract
BACKGROUND: Since the most recent Cochrane review on hMG versus rFSH for controlled ovarian hyperstimulation following a long down-regulation protocol, several new trials have emerged. METHODS: We conducted a systematic review and meta-analysis of randomized trials comparing the effectiveness of hMG versus rFSH following a long down-regulation protocol in IVF-ICSI cycles, on the primary outcome of live birth per woman randomized, as well as several other secondary outcomes. Searches were conducted in MEDLINE, EMBASE, Science Direct, Cochrane Library and databases of abstracts (last search January 2007). RESULTS: Seven randomized trials, consisting of a total of 2159 randomized women, were identified. A meta-analysis of these trials showed a significant increase in live birth rate with hMG when compared with rFSH (relative risk, RR = 1.18, 95% CI: 1.02-1.38, P = 0.03). The heterogeneity test was non-significant (P = 0.97), suggesting that there was no statistical inconsistency between the seven studies. The pooled risk difference (RD) for the outcome of live birth rate was 4% (95% CI: 1-7%) for these study populations. There was an increase in clinical pregnancy rates with hMG when compared with rFSH (RR = 1.17, 95% CI 1.03-1.34). No significant differences were noted for gonadotrophin use, spontaneous abortion, multiple pregnancy, cancellation and ovarian hyperstimulation syndrome rates. CONCLUSIONS: For the populations in the randomized trials, hMG was associated with a pooled 4% increase in live birth rate when compared with rFSH in IVF-ICSI treatment following a long down-regulation protocol.
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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 | 0.014 | 0.033 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.021 | 0.030 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| 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".