Treatment outcomes of blastocysts thaw cycles, comparing the presence and absence of a corpus luteum: a systematic review and meta-analysis
Bibliographic record
Abstract
PURPOSE: This study aims to review the literature and perform a meta-analysis to determine if the presence of a corpus luteum has an impact on treatment outcomes in thaw cycles, where blastocyst embryos are transferred. METHOD: PUBMED, EMBASE, CENTRAL and CINAHL were searched for papers published between January 2017 and 27 July 2020. Additional articles were selected from the reference list of the results and previous reviews. Three reviewers independently reviewed and extracted data. The meta-analysis was conducted though RevMan V.5.4.1. Studies were quality assessed with the Cochrane risk of bias tool and the Newcastle-Ottawa Scale. RESULTS: Nine publications were included for data extraction and subsequent meta-analysis. Two studies were randomised controlled trials, and seven were cohort studies. Subgroup analysis of the different study designs was performed. While the rates of positive human chorionic gonadotropin results (relative risk, RR 1.0, 95% CI 0.95 to 1.05) and clinical pregnancies (RR 1.06, 95% CI 0.96 to 1.18) were comparable between the two groups, the rates of live births were higher in thaw cycles with a corpus luteum (RR 1.14, 95% CI 1.06 to 1.22). Analysis of pregnancy losses demonstrated that both biochemical pregnancy (early miscarriage) (RR 0.71, 95% CI 0.62 to 0.82) and miscarriages (RR 0.72, 95% CI 0.62 to 0.83) were increased in cycles without a corpus luteum. CONCLUSION: Where clinically appropriate, the use of cycle types that have a functional corpus luteum should be favoured. There were several limitations to this study, including the quality of studies and the inherent bias of retrospective cohort studies. Further, high-quality research, particularly randomised controlled trials with blastocysts embryos, is required to further explore these findings. PROSPERO REGISTRATION NUMBER: CRD42020209583.
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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 | 0.018 | 0.045 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.025 | 0.052 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| 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".