卵巢低反应患者高孕激素状态下促排卵方案与拮抗剂方案临床应用效果对比的meta分析
Bibliographic record
Abstract
目的比较高孕激素状态下促排卵(progestin-primed ovarian stimulation, PPOS)方案与拮抗剂方案对卵巢低反应(poor ovarian response, POR)患者的临床应用效果。方法通过检索Pubmed、The Cochrane Library、Embase、Web of Science、CNKI、Wanfang Data、CBM数据库, 搜集PPOS方案与拮抗剂方案应用于POR患者的队列研究和随机对照试验(randomized controlled trials, RCT), 检索时限从建库至2020年5月。严格筛选文献和提取资料后, 队列研究使用改良纽卡斯尔-渥太华量表(Newcastle-Ottawa Scale, NOS)系统评价方法、RCT研究使用Cochrane系统评价方法对文献进行质量评价, 并使用RevMan5.3软件进行meta分析。结果共纳入队列研究7篇, RCT文献3篇, 包括1977例POR患者, 其中PPOS方案组1053例, 拮抗剂方案924例。Meta分析结果显示, PPOS方案的促性腺激素(gonadotropin, Gn)使用时间延长(P=0.02), 但Gn总用量与拮抗剂方案相比差异无统计学意义(P>0.05);PPOS方案的直径≥14 mm卵泡数和获卵数与拮抗剂方案相比差异无统计学意义(P>0.05), MⅡ卵率和受精率显著高于拮抗剂方案(P=0.04, P<0.001), 但两组方案的优质胚胎率差异无统计学意义(P>0.05);PPOS方案的早发黄体生成素(luteinizing hormone, LH)峰发生率明显降低(P=0.04), 扳机日雌二醇、孕酮、卵泡刺激素、LH水平与拮抗剂方案相比差异均无统计学意义(均P>0.05);PPOS方案的临床妊娠率高于拮抗剂方案, 而流产率低于拮抗剂方案(P=0.03, P<0.001), 但周期取消率和出生率与拮抗剂方案相比差异均无统计学意义(均P>0.05)。结论 PPOS方案可明显降低POR患者促排卵中LH峰发生率, 提高MII卵率, 改善妊娠结局, 降低不良妊娠发生率, 可在POR患者中广泛安全使用。
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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 | 0.085 | 0.219 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.009 | 0.018 |
| Bibliometrics | 0.015 | 0.011 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.010 | 0.011 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".