Is glucocorticoid use associated with a higher clinical pregnancy rate of in vitro fertilization and embryo transfer? A meta-analysis
Bibliographic record
Abstract
Background It has been reported that the use of glucocorticoids may be able to improve clinical pregnancy rates in patients receiving in vitro fertilization and embryo transfer (IVF-ET). The purpose of this study was to investigate the association between glucocorticoid use and clinical pregnancy rate in IVF-ET patients. Methods This study has been registered on the International Register of Prospective Systems Evaluation (PROSPERO) (ID: CRD42022375427). A thorough and detailed search of databases including PubMed, Web of Science, Embase, and Cochrane Library was conducted to identify eligible studies up to October 2022. Quality assessment was conducted on the modified Jadad Scoring Scale and Newcastle-Ottawa Scale, and the inter-study heterogeneity was estimated by Q test and I 2 test. Combined hazard ratios with 95% CI were calculated using random effects or fixed effects models based on heterogeneity. Meanwhile, Begg's and Egger's tests were used to detect the existence of publication bias, the leave-one-out method was used for sensitivity analysis and multiple subgroup analyses were conducted. Results Seventeen studies involving 3056 IVF-ET cycles were included. We found that glucocorticoid use was associated with a higher IVF-ET pregnancy rate (OR = 1.86, 95% CI = 1.27–2.74, P = 0.002). In the subgroup analysis, studies of different regions and different study types all showed similar results that glucocorticoid is beneficial to improve the clinical pregnancy rate of patients with IVF-ET, and patients with positive autoantibodies and patients receiving IVF-ET multiple times also showed the same results. However, there was no significant change in clinical pregnancy rates in the seven studies with negative autoantibodies and in the seven studies with initial IVF-ET treatment. The results of the 12 medium-acting glucocorticoids and 4 long-acting glucocorticoids were also generally consistent with each other. There was no statistical difference in subgroup analysis of whether patients had endometriosis or not. Conclusion Appropriate use of glucocorticoids is beneficial for improving the clinical pregnancy rate in women receiving IVF-ET, but this result still needs to be verified by more high-quality and large sample size randomized controlled trials (RCTs).
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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 | 0.028 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.016 | 0.054 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".